From 139fa5f09f21c0f2d0fe2848f53752b6139e9111 Mon Sep 17 00:00:00 2001 From: Epameinondas Antonakos Date: Wed, 28 May 2014 14:04:18 +0100 Subject: [PATCH 1/3] added patch-based aam --- .../Deformable Models/AAMs Advanced.ipynb | 150322 ++++++++++++++- 1 file changed, 150118 insertions(+), 204 deletions(-) diff --git a/notebooks/Deformable Models/AAMs Advanced.ipynb b/notebooks/Deformable Models/AAMs Advanced.ipynb index be48ce1..65bad55 100644 --- a/notebooks/Deformable Models/AAMs Advanced.ipynb +++ b/notebooks/Deformable Models/AAMs Advanced.ipynb @@ -1,7 +1,7 @@ { "metadata": { "name": "", - "signature": "sha256:7ee5ef7b443b6d760bc2a63ac0e3cfbc043e276018162fd65aa6675514292838" + "signature": "sha256:86e0ed20a709910cd872022d4f1bd4b89bd7737cbca5df426d5f70305a1c8340" }, "nbformat": 3, "nbformat_minor": 0, @@ -16,13 +16,6 @@ "Active Appearance Models - Advanced" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "-----" - ] - }, { "cell_type": "heading", "level": 2, @@ -37,24 +30,9 @@ "source": [ "The aim of this notebook is to showcase some of the more advanced features that are available for building and fitting AAMs using `Menpo`. \n", "\n", - "Note that this notebook assumes that the user has previously gone through the AAMs Basic notebook and he/she is already familiar with the basic AAMs and `Menpo` concepts explained in there." - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "1.1 Building and fitting more flexible and powerful AAMs" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The AAMs Basic notebook shows us how through the use of the `AAMBuilder` and the `LucasKanadeAAMFitter` classes one can easily build and fit basic AAMs using `Menpo`. In reality, `Menpo`'s framework for AAMs is a lot more powerful and we will proceed to show how a large variety of different AAMs and different fitting algorithm can be used by simply specifying the right keyword arguments on the two previous classes.\n", + "Note that this notebook assumes that the user has previously gone through the AAMs Basic notebook and he/she is already familiar with the basic AAMs and `Menpo` concepts explained in there. The AAMs Basic notebook shows us how through the use of the `AAMBuilder` and the `LucasKanadeAAMFitter` classes one can easily build and fit basic AAMs using `Menpo`. In reality, `Menpo`'s framework for AAMs is a lot more powerful and we will proceed to show how a large variety of different AAMs and different fitting algorithms can be used by simply specifying the right keyword arguments on the two previous classes.\n", "\n", - "The complete list of the available keyword arguments for both `AAMBuilder` and `LucasKanadeAAMFitter` and their corresponding detailed explainations can be found in Menpo's documentation. Remember that their documentation can be checked at any time from the IPython Notebook by simply running:" + "The complete list of the available keyword arguments for the `AAMBuilder` and their corresponding detailed explanations can be found in Menpo's documentation. Remember that their documentation can be checked at any time from the IPython Notebook by simply running:" ] }, { @@ -70,32 +48,18 @@ "outputs": [], "prompt_number": 1 }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "from menpo.fitmultilevel.aam import LucasKanadeAAMFitter\n", - "\n", - "LucasKanadeAAMFitter??" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 2 - }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This notebook is structured in several shorts sections, each one explaining a different advanced concept related to `Menpo`'s framework for building and fitting AAMs. \n", - "\n", - "For example, the very first section explains how AAMs can be build using different appearance features (including arbitrarily apperance features defined by the user). Future section will tackle: \n", + "This notebook is structured in several short sections, each one explaining a different advanced concept related to `Menpo`'s framework for building and fitting AAMs. Specifically:\n", "\n", - "* How to use different `LucasKanade` based algorithm for fitting AAMs.\n", - "* How AAMs can also be fitted using `Menpo`'s Supervised Descent framework for cascade-regression.\n", - "* ...\n", + "* Section 2 shows how to use various feature representations for building and fitting an AAM.\n", + "* Section 3 demonstrates the different algorithms available within the `LucasKanadeAAMFitter` class.\n", + "* Section 4 presents how to perform patch-based AAM building and training.\n", + "* Section 5 shows how to use regression-based Supervised-Descent (SD) method to fit a trained AAM.\n", "\n", - "Note that, in generael, these section will be fairly detached from one another and the orther in which they are listed bellow is not specifically rellevant." + "Note that, in general, these sections are fairly detached from one another and the order in which they are listed bellow is not specifically relevant." ] }, { @@ -110,76 +74,96 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "However, all of them will rely on some training and testing data to build and fit their respective AAMs. Once again, we will rely on the training and test sets of the LFPW database for this purpose.\n", + "All the following sections will rely on some training and testing data to build and fit their respective AAMs. Once again, we will rely on the training and test sets of the LFPW database for this purpose.\n", "\n", - "Note that the necessary steps required for acquiring the LFPW database are explained in detail in the AAMs Basics notebook and the user is simply referred to that notebook for this matter." + "Note that the necessary steps required for acquiring the LFPW database are explained in detail in the AAMs Basics notebook and the user is simply referred to that notebook for this matter.\n", + "\n", + "Let us define two methods for:\n", + "* `load_database()` for loading a set of images, cropping them and converting them to greyscale\n", + "* `browse_images()` for visualizing the loaded images" ] }, { "cell_type": "code", "collapsed": false, "input": [ - "path_to_lfpw = '/Users/joan/PhD/DataBases/'" + "import menpo.io as mio\n", + "import matplotlib.pyplot as plt\n", + "from IPython.html.widgets import interact\n", + "\n", + "# method to load a database\n", + "def load_database(path_to_images, crop_percentage, max_images=None):\n", + " images = []\n", + " # load landmarked images\n", + " for i in mio.import_images(path_to_images, max_images=max_images):\n", + " # crop image\n", + " i.crop_to_landmarks_proportion_inplace(crop_percentage)\n", + " \n", + " # convert it to grayscale if needed\n", + " if i.n_channels == 3:\n", + " i = i.as_greyscale(mode='luminosity')\n", + " \n", + " # append it to the list\n", + " images.append(i)\n", + " return images\n", + "\n", + "# method to visualize a set of images\n", + "def browse_images(images, group=None, label='all'):\n", + " n = len(images)\n", + " def view_image(i):\n", + " images[i].landmarks[group][label].view()\n", + " plt.show()\n", + " interact(view_image, i=(0,n-1))" ], "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 3 + "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Training data:" + "and also define the path to the LFPW database.\n", + "\n", + "Note that the necessary steps required for acquiring the LFPW dataset used throughout this notebook were previously explained in the AAMs Basics notebook and we simply refer the user to that notebook for this matter." ] }, { "cell_type": "code", "collapsed": false, "input": [ - "import menpo.io as mio\n", - "\n", - "training_images = []\n", - "# load landmarked images\n", - "for i in mio.import_images(path_to_lfpw + 'lfpw/trainset/*.png'):\n", - " # crop image\n", - " i.crop_to_landmarks_proportion(0.1)\n", - " # convert it to grayscale if needed\n", - " if i.n_channels == 3:\n", - " i = i.as_greyscale(mode='luminosity')\n", - " # append it to the list\n", - " training_images.append(i)" + "#path_to_lfpw = '/Users/joan/PhD/DataBases/'\n", + "path_to_lfpw = '/home/nontas/Desktop/'" ], "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 22 + "prompt_number": 3 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load and visualize the __training__ images with a crop proportion of 10%:" + ] }, { "cell_type": "code", "collapsed": false, "input": [ - "import matplotlib.pyplot as plt\n", - "from IPython.html.widgets import interact\n", - "\n", - "def browse_images(images, group=None, label='all'):\n", - " n = len(images)\n", - " def view_image(i):\n", - " images[i].landmarks[group][label].view()\n", - " plt.show()\n", - " interact(view_image, i=(0,n-1))" + "training_images = load_database(path_to_lfpw + 'lfpw/trainset/*', 0.1)" ], "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 23 + "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", - "\n", "browse_images(training_images)" ], "language": "python", @@ -188,68 +172,37 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnnjiiScVKB44e+KJJ55UoPx/mbfQ9KwK3zcAAAAASUVORK5CYII=\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text": [ - "" + "" ] } ], - "prompt_number": 24 + "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Test data:" + "Load and visualize 5 __test__ images with a crop proportion of 50%:" ] }, { "cell_type": "code", "collapsed": false, "input": [ - "import menpo.io as mio\n", - "\n", - "# load test images\n", - "test_images = []\n", - "for i in mio.import_images(path_to_lfpw + 'lfpw/testset/*.png', max_images=5):\n", - " # crop image\n", - " i.crop_to_landmarks_proportion(0.5)\n", - " # convert it to grayscale if needed\n", - " if i.n_channels == 3:\n", - " i = i.as_greyscale(mode='luminosity')\n", - " # append it to the list\n", - " test_images.append(i)" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 25 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import matplotlib.pyplot as plt\n", - "from IPython.html.widgets import interact\n", - "\n", - "def browse_images(images, group=None, label='all'):\n", - " n = len(images)\n", - " def view_image(i):\n", - " images[i].landmarks[group][label].view()\n", - " plt.show()\n", - " interact(view_image, i=(0,n-1))" + "test_images = load_database(path_to_lfpw + 'lfpw/testset/*', 0.5, max_images=5)" ], "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 26 + "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", - "\n", "browse_images(test_images)" ], "language": "python", @@ -258,13 +211,13 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAAD7CAYAAABdXO4CAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wG33y4sDjQvVAAAAABJRU5ErkJggg==\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWMAAAD7CAYAAAC/gPV7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] } ], - "prompt_number": 29 + "prompt_number": 7 }, { "cell_type": "heading", @@ -278,9 +231,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "One of the most powerful and general characteristics of the `AAMBuilder` class is that it allows the user to build AAMs with arbitrarily user-defined appearance features. Instead of restricting the user to a set of predifine appearance features, `Menpo` allows him/her to define new features (perhaps simple combinations of existing image features suported by Menpo or perhaps completely new (even discriminative!) features designed by the user) and pass them to the `AAMbuilder`.\n", + "One of the most powerful and general characteristics of the `AAMBuilder` class is that it allows the user to build AAMs with arbitrarily user-defined appearance features. Instead of restricting the user to a set of predefined appearance features, `Menpo` allows him/her to define new features (perhaps simple combinations of existing image features supported by Menpo or perhaps completely new (even discriminative!) features designed by the user) and pass them to the `AAMbuilder`.\n", "\n", - "All that is required is that the user encapsulates his/her desired feature computation in an function that receives as an arguments a `Menpo` `Image` objects and that returns a `Menpo` `Image` object containing the desired features. The next cell shows a simple example of such a function, in which **igo** features are computed on an feature image that was already obtained by computing **igo** features:" + "All that is required is that the user encapsulates his/her desired feature computation in an function that receives as an arguments a `Menpo` `Image` object and that returns a `Menpo` `Image` object containing the desired features. The next cell shows a simple example of such a function, in which **igo** features are computed on an feature image that was already obtained by computing **igo** features:" ] }, { @@ -293,15 +246,13 @@ "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 7 + "prompt_number": 8 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "In order to build an AAM that uses the previous function to generate the appearance representation used by its apperance model we will first need to import some annotated images from which to build the AAM. Once again, we will use the LFPW training set for this purpose.\n", - "\n", - "Note that the necessary steps required for acquiring the LFPW dataset used throughout this notebook were previously explained in the AAMs Basics notebook and we simply refer the user to that notebook for this matter." + "We can now build an AAM using our new feature representation with the following command:" ] }, { @@ -310,7 +261,8 @@ "input": [ "from menpo.fitmultilevel.aam import AAMBuilder\n", "\n", - "aam = AAMBuilder(feature_type=my_new_features, normalization_diagonal=100).build(training_images, verbose=True)" + "aam = AAMBuilder(feature_type=my_new_features, \n", + " normalization_diagonal=100).build(training_images, verbose=True)" ], "language": "python", "metadata": {}, @@ -6819,22 +6771,6 @@ "- Normalizing images size: Done\n" ] }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Estimating RAM memory requirements..." - ] - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Approximately 123.72 MB ['94.43 MB', '23.51 MB', '5.78 MB'] of RAM required to store model.\n" - ] - }, { "output_type": "stream", "stream": "stdout", @@ -52364,7 +52300,7 @@ ] } ], - "prompt_number": 8 + "prompt_number": 9 }, { "cell_type": "code", @@ -52402,7 +52338,14 @@ ] } ], - "prompt_number": 9 + "prompt_number": 10 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us now define a method to visualize the AAM model" + ] }, { "cell_type": "code", @@ -52420,7 +52363,7 @@ "language": "python", "metadata": {}, "outputs": [], - "prompt_number": 10 + "prompt_number": 11 }, { "cell_type": "code", @@ -52436,13 +52379,20 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAD7CAYAAACc26SuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niGP+D3icX/n8XZrkAAAAAElFTkSuQmCC\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAW0AAAD7CAYAAAChScXIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] } ], - "prompt_number": 11 + "prompt_number": 12 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The trained AAM can be used to fit the loaded testing images using the following commands:" + ] }, { "cell_type": "code", @@ -52471,7 +52421,7 @@ " - Level 1 (no downscale): \n", " - Reference frame of length 14836 (3709 x 4C, 75W x 74H x 4C)\n", " - 16 motion components\n", - " - 205 active appearance components (50.13% of original variance)\n", + " - 205 active appearance components (50.14% of original variance)\n", " - Level 2 (downscale by 2): \n", " - Reference frame of length 3692 (923 x 4C, 41W x 40H x 4C)\n", " - 10 motion components\n", @@ -52495,12 +52445,16 @@ "for j, i in enumerate(test_images):\n", " # obtain original landmarks\n", " gt_s = i.landmarks['PTS'].lms\n", + " \n", " # generate perturbed landmarks\n", " s = fitter.perturb_shape(gt_s)\n", + " \n", " # fit image\n", " fr = fitter.fit(i, s, gt_shape=gt_s) \n", + " \n", " # append fitting result to list\n", " fitting_results.append(fr)\n", + " \n", " # print fitting information\n", " print 'Image: ', j\n", " print fr" @@ -52513,8 +52467,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.0748\n", - "Final error: 0.0167\n", + "Initial error: 0.0692\n", + "Final error: 0.0247\n", "Image: " ] }, @@ -52523,8 +52477,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.0321\n", - "Final error: 0.0177\n", + "Initial error: 0.1150\n", + "Final error: 0.0194\n", "Image: " ] }, @@ -52533,8 +52487,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0784\n", - "Final error: 0.0372\n", + "Initial error: 0.0631\n", + "Final error: 0.0399\n", "Image: " ] }, @@ -52543,8 +52497,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.1348\n", - "Final error: 0.0165\n", + "Initial error: 0.1182\n", + "Final error: 0.1240\n", "Image: " ] }, @@ -52553,13 +52507,20 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.1151\n", - "Final error: 0.0907\n" + "Initial error: 0.0465\n", + "Final error: 0.0163\n" ] } ], "prompt_number": 14 }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's have a look at the fitting results:" + ] + }, { "cell_type": "code", "collapsed": false, @@ -52577,9 +52538,9 @@ "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", "output_type": "pyerr", "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mu'matplotlib inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mfitted_images\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'fitted'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" ] } ], @@ -52625,16 +52586,11 @@ "* BayesianForwardCompositional [5] a link to my paper\n", "* BayesianInverseCompositional\n", "\n", - "Note that an effor has been made to generalize the original algorithms to support the common `Forward Additive`, `Forward Compositional` and `Inverse Compositional` paradigms.\n", + "Note that an effort has been made to generalize the original algorithms to support the common `Forward Additive`, `Forward Compositional` and `Inverse Compositional` paradigms.\n", "\n", - "For a further details on the algorithms the user is referred to the refences an to their actual implementations in `Menpo`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The first step to fit an AAM using a particular `LucasKanade` based fitting algorithm is to build an AAM: " + "For further details on the algorithms the user is referred to the refences and to their actual implementations in `Menpo`.\n", + "\n", + "Again, the first step to fit an AAM using a particular `LucasKanade` based fitting algorithm is to build an AAM:" ] }, { @@ -59152,22 +59108,6 @@ "- Normalizing images size: Done\n" ] }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Estimating RAM memory requirements..." - ] - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Approximately 56.69 MB ['43.25 MB', '10.78 MB', '2.67 MB'] of RAM required to store model.\n" - ] - }, { "output_type": "stream", "stream": "stdout", @@ -104697,13 +104637,13 @@ ] } ], - "prompt_number": 35 + "prompt_number": 16 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Note that the previous cell has built a multilevel AAM with 3 levels using **igo** features as the apperance representation of its 3 apperance models." + "Note that the previous cell has built a multilevel AAM with 3 levels using **igo** features (the default option) as the apperance representation of its 3 apperance models." ] }, { @@ -104742,13 +104682,13 @@ ] } ], - "prompt_number": 36 + "prompt_number": 17 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "In order to fit the previous AAM using using one of the previous `LucasKanade` based algorithm the user is simply required to:\n", + "In order to fit the previous AAM using one of the previous `LucasKanade` based algorithm the user is simply required to:\n", "\n", "* Import the algorithm that he/she wants to use. \n", "* Simply change the default value of the `algorithm` keyword argument on the `LucasKanadeAAMFitter` call.\n", @@ -104799,7 +104739,7 @@ ] } ], - "prompt_number": 39 + "prompt_number": 18 }, { "cell_type": "code", @@ -104810,12 +104750,16 @@ "for j, i in enumerate(test_images):\n", " # obtain original landmarks\n", " gt_s = i.landmarks['PTS'].lms\n", + " \n", " # generate perturbed landmarks\n", " s = fitter.perturb_shape(gt_s)\n", + " \n", " # fit image\n", " fr = fitter.fit(i, s, gt_shape=gt_s) \n", + " \n", " # append fitting result to list\n", " fitting_results.append(fr)\n", + " \n", " # print fitting information\n", " print 'Image: ', j\n", " print fr" @@ -104828,8 +104772,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.0723\n", - "Final error: 0.0226\n", + "Initial error: 0.1483\n", + "Final error: 0.1153\n", "Image: " ] }, @@ -104838,8 +104782,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.1098\n", - "Final error: 0.0225\n", + "Initial error: 0.0998\n", + "Final error: 0.0531\n", "Image: " ] }, @@ -104848,8 +104792,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0842\n", - "Final error: 0.2035\n", + "Initial error: 0.0690\n", + "Final error: 0.0678\n", "Image: " ] }, @@ -104858,8 +104802,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.0871\n", - "Final error: 0.0219\n", + "Initial error: 0.0855\n", + "Final error: 0.0697\n", "Image: " ] }, @@ -104868,12 +104812,12 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.0964\n", - "Final error: 0.1570\n" + "Initial error: 0.0614\n", + "Final error: 0.0671\n" ] } ], - "prompt_number": 40 + "prompt_number": 19 }, { "cell_type": "code", @@ -104892,26 +104836,149996 @@ "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", "output_type": "pyerr", "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mu'matplotlib inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mfitted_images\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'fitted'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" ] } ], - "prompt_number": 41 + "prompt_number": 20 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ - "4. Fitting AAMs using `Menpo's` Supervised Descent (SD) framework" + "4. Patch-Based AAM building and fitting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "All the previous AAM examples were using a holistic appearance representation, i.e. the whole face was employed as an appearance vector. Herein, we show how to build and fit a patch-based AAM. This means that the appearance representation consists of small patches extracted around each of the landmark points.\n", + "\n", + "The patch-based AAM builder, `PatchBasedAAMBuilder`, has the same parameters as the `AAMBuilder`, with the addition of the `patch_shape` parameter. " ] }, { "cell_type": "code", "collapsed": false, - "input": [], + "input": [ + "from menpo.fitmultilevel.aam import PatchBasedAAMBuilder\n", + "from menpo.fitmultilevel.featurefunctions import double_igo\n", + "\n", + "patch_base_aam = PatchBasedAAMBuilder(patch_shape=(16, 16), \n", + " feature_type=double_igo,\n", + " normalization_diagonal=140).build(training_images, verbose=True)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing reference shape" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Building model for each of the 3 pyramid levels\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Building shape model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Computing transforms" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Building appearance model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Building shape model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Computing transforms" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Building appearance model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Rescaling feature space - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Building shape model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Computing transforms" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Warping images - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Building appearance model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 3: Done\n" + ] + } + ], + "prompt_number": 23 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "print patch_base_aam" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Patch-Based Active Appearance Model\n", + " - 811 training images.\n", + " - Warp using ThinPlateSplines transform with 'scipy' interpolation.\n", + " - Gaussian pyramid with 3 levels and downscale factor of 2.\n", + " - Each level has a scaled shape model (reference frame).\n", + " - Patch size is 16W x 16H.\n", + " - Pyramid was applied on feature space.\n", + " - Feature is double_igo with 4 channels per image.\n", + " - Level 1 (no downscale): \n", + " - Reference frame of length 32524 (8131 x 4C, 134W x 134H x 4C)\n", + " - 133 shape components (100.00% of variance)\n", + " - 810 appearance components (100.00% of variance)\n", + " - Level 2 (downscale by 2): \n", + " - Reference frame of length 13764 (3441 x 4C, 86W x 86H x 4C)\n", + " - 133 shape components (100.00% of variance)\n", + " - 810 appearance components (100.00% of variance)\n", + " - Level 3 (downscale by 4): \n", + " - Reference frame of length 5652 (1413 x 4C, 62W x 62H x 4C)\n", + " - 133 shape components (100.00% of variance)\n", + " - 810 appearance components (100.00% of variance)\n" + ] + } + ], + "prompt_number": 24 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The fitting of the trained Patch-Based AAM can use any of the algorithms of the `LucasKanadeAAMFitter` presented in the previous section as:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from menpo.fit.lucaskanade.appearance import AlternatingForwardCompositional\n", + "\n", + "fitter = LucasKanadeAAMFitter(patch_base_aam, algorithm=AlternatingForwardCompositional,\n", + " n_shape=[3, 6, 12], n_appearance=50)\n", + "print fitter" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Patch-Based Active Appearance Model Fitter\n", + " - Lucas-Kanade Alternating-FC\n", + " - Transform is OrthoMDTransform and residual is SSD.\n", + " - 811 training images.\n", + " - Gaussian pyramid with 3 levels and downscale factor of 2.\n", + " - Each level has a scaled shape model (reference frame).\n", + " - Pyramid was applied on feature space.\n", + " - Feature is double_igo with 4 channels per image.\n", + " - Level 1 (no downscale): \n", + " - Reference frame of length 32524 (8131 x 4C, 134W x 134H x 4C)\n", + " - 16 motion components\n", + " - 50 active appearance components (28.98% of original variance)\n", + " - Level 2 (downscale by 2): \n", + " - Reference frame of length 13764 (3441 x 4C, 86W x 86H x 4C)\n", + " - 10 motion components\n", + " - 50 active appearance components (38.64% of original variance)\n", + " - Level 3 (downscale by 4): \n", + " - Reference frame of length 5652 (1413 x 4C, 62W x 62H x 4C)\n", + " - 7 motion components\n", + " - 50 active appearance components (51.23% of original variance)\n", + "\n" + ] + } + ], + "prompt_number": 25 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "fitting_results = []\n", + "# fit images\n", + "for j, i in enumerate(test_images):\n", + " # obtain original landmarks\n", + " gt_s = i.landmarks['PTS'].lms\n", + " \n", + " # generate perturbed landmarks\n", + " s = fitter.perturb_shape(gt_s)\n", + " \n", + " # fit image\n", + " fr = fitter.fit(i, s, gt_shape=gt_s) \n", + " \n", + " # append fitting result to list\n", + " fitting_results.append(fr)\n", + " \n", + " # print fitting information\n", + " print 'Image: ', j\n", + " print fr" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Image: 0\n", + "Initial error: 0.1062\n", + "Final error: 0.0387\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 1\n", + "Initial error: 0.0898\n", + "Final error: 0.0261\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 2\n", + "Initial error: 0.0449\n", + "Final error: 0.0334\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 3\n", + "Initial error: 0.0958\n", + "Final error: 0.0259\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 4\n", + "Initial error: 0.0661\n", + "Final error: 0.0162\n" + ] + } + ], + "prompt_number": 26 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%matplotlib inline\n", + "\n", + "fitted_images = [fr.final_fitting for fr in fitting_results]\n", + "browse_images(fitted_images, group='fitted')" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", + "output_type": "pyerr", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + ] + } + ], + "prompt_number": 27 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "5. Fitting AAMs using `Menpo's` Supervised Descent (SD) framework" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Gradient-Descent techniques are not the only ones that can be used to fit an AAM to a new image. Menpo gives to the user the ability to use the regression-based Supervised-Descent (SD) method for this task.\n", + "\n", + "Let us train a new AAM model that employs the IGO features with double angles:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from menpo.fitmultilevel.featurefunctions import double_igo\n", + "\n", + "aam = AAMBuilder(feature_type=double_igo,\n", + " normalization_diagonal=100,\n", + " n_levels=2, \n", + " downscale=1.1,\n", + " scaled_shape_models=True,\n", + " pyramid_on_features=True,\n", + " max_appearance_components=500).build(training_images, group='PTS', verbose=True)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing reference shape" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Building model for each of the 2 pyramid levels\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Rescaling feature space - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Building shape model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Computing transforms" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Warping images - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Building appearance model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 1: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Rescaling feature space - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Building shape model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Computing transforms" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Warping images - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Building appearance model" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + " - Level 2: Done\n" + ] + } + ], + "prompt_number": 28 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then the regressors of the SD method are trained using the `SDAAMTrainer` class as:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from menpo.fitmultilevel.sdm import SDAAMTrainer\n", + "from menpo.fit.regression.regressionfunctions import mlr\n", + "from menpo.fit.regression.parametricfeatures import weights, warped_image\n", + "\n", + "# build aam\n", + "sdm = SDAAMTrainer(aam, \n", + " regression_type=mlr, \n", + " regression_features=weights,\n", + " noise_std=0.04, \n", + " n_perturbations=10,\n", + " n_shape=25,\n", + " n_appearance=None).train(training_images, group='PTS', verbose=True)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing reference shape" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Normalizing images size: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Computing feature space: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 1 - Rescaling feature space - 100%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 0%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 1%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 2%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 3%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 4%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 5%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 6%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 7%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 8%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 9%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 10%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 11%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 12%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 13%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 14%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 15%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 16%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 17%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 18%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 19%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 20%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 21%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 22%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 23%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 24%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 25%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 26%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 27%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 28%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 29%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 30%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 31%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 32%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 33%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 34%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 35%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 36%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 37%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 38%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 39%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 40%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 41%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 42%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 43%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 44%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 45%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 46%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 47%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 48%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 49%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 50%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 51%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 52%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 53%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 54%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 55%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 56%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 57%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 58%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 59%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 60%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 61%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 62%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 63%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 64%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 65%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 66%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 67%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 68%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 69%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 70%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 71%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 72%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 73%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 74%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 75%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 76%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 77%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 78%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 79%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 80%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 81%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 82%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 83%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 84%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 85%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 86%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 87%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 88%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 89%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 90%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 91%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 92%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 93%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 94%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 95%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 96%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 97%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 98%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 99%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: [Level 2 - Rescaling feature space - 100%]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Apply pyramid: Done\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Building regressors for each of the 2 pyramid levels\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r\n", + "Level 1:\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Performing regression..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Regression RMSE is 24.01563.\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Perturbing shapes..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: computing mean error..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: mean error is 0.040127.\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r\n", + "Level 2:\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Generating regression data - 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Performing regression..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Regression RMSE is 18.63835.\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Perturbing shapes..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: 100%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: computing mean error..." + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Fitting shapes: mean error is 0.027796.\n" + ] + } + ], + "prompt_number": 29 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Fitting the trained cascade of regressors on the testing images gives the following results:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "fitting_results = []\n", + "# fit images\n", + "for j, i in enumerate(test_images):\n", + " # obtain original landmarks\n", + " gt_s = i.landmarks['PTS'].lms\n", + " # generate perturbed landmarks\n", + " s = fitter.perturb_shape(gt_s)\n", + " # fit image\n", + " fr = sdm.fit(i, s, gt_shape=gt_s) \n", + " # append fitting result to list\n", + " fitting_results.append(fr)\n", + " # print fitting information\n", + " print 'Image: ', j\n", + " print fr" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Image: 0\n", + "Initial error: 0.0630\n", + "Final error: 0.0315\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 1\n", + "Initial error: 0.0683\n", + "Final error: 0.0291\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 2\n", + "Initial error: 0.0517\n", + "Final error: 0.0352\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 3\n", + "Initial error: 0.1147\n", + "Final error: 0.0421\n", + "Image: " + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 4\n", + "Initial error: 0.1027\n", + "Final error: 0.0261\n" + ] + } + ], + "prompt_number": 32 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%matplotlib inline\n", + "\n", + "fitted_images = [fr.final_fitting for fr in fitting_results]\n", + "browse_images(fitted_images, group='fitted')" + ], "language": "python", "metadata": {}, "outputs": [] From 6ec82c2520d7f3a39867a9f9351382239edab3b8 Mon Sep 17 00:00:00 2001 From: Epameinondas Antonakos Date: Wed, 28 May 2014 16:54:52 +0100 Subject: [PATCH 2/3] adds sdaam --- .../Deformable Models/AAMs Advanced.ipynb | 6833 ++++++++++++++++- notebooks/Deformable Models/AAMs Basics.ipynb | 6632 +++++++++++++++- 2 files changed, 13247 insertions(+), 218 deletions(-) diff --git a/notebooks/Deformable Models/AAMs Advanced.ipynb b/notebooks/Deformable Models/AAMs Advanced.ipynb index 65bad55..7bc7ae9 100644 --- a/notebooks/Deformable Models/AAMs Advanced.ipynb +++ b/notebooks/Deformable Models/AAMs Advanced.ipynb @@ -1,7 +1,7 @@ { "metadata": { "name": "", - "signature": "sha256:86e0ed20a709910cd872022d4f1bd4b89bd7737cbca5df426d5f70305a1c8340" + "signature": "sha256:d35cf4cd1133886cff19295e71cfb358c4bd19d273905a26298182341545f632" }, "nbformat": 3, "nbformat_minor": 0, @@ -95,7 +95,7 @@ "def load_database(path_to_images, crop_percentage, max_images=None):\n", " images = []\n", " # load landmarked images\n", - " for i in mio.import_images(path_to_images, max_images=max_images):\n", + " for i in mio.import_images(path_to_images, max_images=max_images, verbose=True):\n", " # crop image\n", " i.crop_to_landmarks_proportion_inplace(crop_percentage)\n", " \n", @@ -133,8 +133,7 @@ "cell_type": "code", "collapsed": false, "input": [ - "#path_to_lfpw = '/Users/joan/PhD/DataBases/'\n", - "path_to_lfpw = '/home/nontas/Desktop/'" + "path_to_lfpw = '/Users/joan/PhD/DataBases/'" ], "language": "python", "metadata": {}, @@ -156,7 +155,6496 @@ ], "language": "python", "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====================] 100%" + ] + } + ], "prompt_number": 4 }, { @@ -172,9 +6660,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nu1orAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] } ], @@ -195,7 +6683,48 @@ ], "language": "python", "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 5 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 5 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 5 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 5 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 5 assets: [====================] 100%" + ] + } + ], "prompt_number": 6 }, { @@ -211,9 +6740,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAWMAAAD7CAYAAAC/gPV7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWMAAAD7CAYAAAC/gPV7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMcd6wP5/D711f/J4AjEAAAAASUVORK5CYII=\n", "text": [ - "" + "" ] } ], @@ -52379,9 +58908,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAW0AAAD7CAYAAAChScXIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD7CAYAAAB68m/qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text": [ - "" + "" ] } ], @@ -52467,8 +58996,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.0692\n", - "Final error: 0.0247\n", + "Initial error: 0.0686\n", + "Final error: 0.0240\n", "Image: " ] }, @@ -52477,8 +59006,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.1150\n", - "Final error: 0.0194\n", + "Initial error: 0.0667\n", + "Final error: 0.0191\n", "Image: " ] }, @@ -52487,8 +59016,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0631\n", - "Final error: 0.0399\n", + "Initial error: 0.0444\n", + "Final error: 0.0232\n", "Image: " ] }, @@ -52497,8 +59026,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.1182\n", - "Final error: 0.1240\n", + "Initial error: 0.0799\n", + "Final error: 0.0255\n", "Image: " ] }, @@ -52507,8 +59036,8 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.0465\n", - "Final error: 0.0163\n" + "Initial error: 0.0910\n", + "Final error: 0.0160\n" ] } ], @@ -52527,20 +59056,37 @@ "input": [ "%matplotlib inline\n", "\n", - "fitted_images = [fr.final_fitting for fr in fitting_results]\n", - "browse_images(fitted_images, group='fitted')" + "# visualize initialization\n", + "fitting_results[1].view_initialization(new_figure=True)\n", + "\n", + "# visualize final fitting result\n", + "fitting_results[1].view_final_fitting(new_figure=True)" ], "language": "python", "metadata": {}, "outputs": [ { - "ename": "AttributeError", - "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", - "output_type": "pyerr", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + "metadata": {}, + "output_type": "pyout", + "prompt_number": 15, + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAVAAAAD7CAYAAAA8RMxAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAVAAAAD7CAYAAAA8RMxAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+TnZKAAAAABJRU5ErkJggg==\n", + "text": [ + "" ] } ], @@ -104705,7 +111251,7 @@ "from menpo.fit.lucaskanade.appearance import ProjectOutInverseCompositional\n", "\n", "fitter = LucasKanadeAAMFitter(aam, algorithm=ProjectOutInverseCompositional,\n", - " n_shape=[3, 6, 12], n_appearance=0.5)\n", + " n_shape=[3, 6, 12], n_appearance=0.3)\n", "print fitter" ], "language": "python", @@ -104726,15 +111272,15 @@ " - Level 1 (no downscale): \n", " - Reference frame of length 7418 (3709 x 2C, 75W x 74H x 2C)\n", " - 16 motion components\n", - " - 64 active appearance components (50.09% of original variance)\n", + " - 15 active appearance components (30.06% of original variance)\n", " - Level 2 (downscale by 2): \n", " - Reference frame of length 1846 (923 x 2C, 41W x 40H x 2C)\n", " - 10 motion components\n", - " - 27 active appearance components (50.18% of original variance)\n", + " - 7 active appearance components (30.64% of original variance)\n", " - Level 3 (downscale by 4): \n", " - Reference frame of length 454 (227 x 2C, 24W x 23H x 2C)\n", " - 7 motion components\n", - " - 11 active appearance components (51.56% of original variance)\n", + " - 3 active appearance components (31.38% of original variance)\n", "\n" ] } @@ -104772,8 +111318,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.1483\n", - "Final error: 0.1153\n", + "Initial error: 0.0877\n", + "Final error: 0.0548\n", "Image: " ] }, @@ -104782,8 +111328,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.0998\n", - "Final error: 0.0531\n", + "Initial error: 0.0775\n", + "Final error: 0.0469\n", "Image: " ] }, @@ -104792,8 +111338,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0690\n", - "Final error: 0.0678\n", + "Initial error: 0.0610\n", + "Final error: 0.0616\n", "Image: " ] }, @@ -104802,8 +111348,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.0855\n", - "Final error: 0.0697\n", + "Initial error: 0.0883\n", + "Final error: 0.0321\n", "Image: " ] }, @@ -104812,8 +111358,8 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.0614\n", - "Final error: 0.0671\n" + "Initial error: 0.1040\n", + "Final error: 0.0969\n" ] } ], @@ -104824,21 +111370,34 @@ "collapsed": false, "input": [ "%matplotlib inline\n", - "\n", - "fitted_images = [fr.final_fitting for fr in fitting_results]\n", - "browse_images(fitted_images, group='fitted')" + "fitting_results[3].view_initialization(new_figure=True)\n", + "fitting_results[3].view_final_fitting(new_figure=True)" ], "language": "python", "metadata": {}, "outputs": [ { - "ename": "AttributeError", - "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", - "output_type": "pyerr", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + "metadata": {}, + "output_type": "pyout", + "prompt_number": 20, + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWwAAAD7CAYAAABOi672AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGIZJEthhMwzDJAnssBmGYZKE/wAQ3WRCPEav4AAAAABJRU5ErkJggg==\n", + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWwAAAD7CAYAAABOi672AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n", + "text": [ + "" ] } ], @@ -104858,7 +111417,7 @@ "source": [ "All the previous AAM examples were using a holistic appearance representation, i.e. the whole face was employed as an appearance vector. Herein, we show how to build and fit a patch-based AAM. This means that the appearance representation consists of small patches extracted around each of the landmark points.\n", "\n", - "The patch-based AAM builder, `PatchBasedAAMBuilder`, has the same parameters as the `AAMBuilder`, with the addition of the `patch_shape` parameter. " + "The patch-based AAM builder, `PatchBasedAAMBuilder`, has the same parameters as the `AAMBuilder`, with the addition of the `patch_shape` parameter. We'll train such an AAM using IGOs with double angles as feature representation:" ] }, { @@ -156908,7 +163467,7 @@ ] } ], - "prompt_number": 23 + "prompt_number": 21 }, { "cell_type": "code", @@ -156946,7 +163505,7 @@ ] } ], - "prompt_number": 24 + "prompt_number": 22 }, { "cell_type": "markdown", @@ -156996,7 +163555,7 @@ ] } ], - "prompt_number": 25 + "prompt_number": 23 }, { "cell_type": "code", @@ -157029,8 +163588,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.1062\n", - "Final error: 0.0387\n", + "Initial error: 0.0752\n", + "Final error: 0.0242\n", "Image: " ] }, @@ -157039,8 +163598,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.0898\n", - "Final error: 0.0261\n", + "Initial error: 0.0827\n", + "Final error: 0.0257\n", "Image: " ] }, @@ -157049,8 +163608,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0449\n", - "Final error: 0.0334\n", + "Initial error: 0.0551\n", + "Final error: 0.0284\n", "Image: " ] }, @@ -157059,8 +163618,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.0958\n", - "Final error: 0.0259\n", + "Initial error: 0.0674\n", + "Final error: 0.0292\n", "Image: " ] }, @@ -157069,37 +163628,50 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.0661\n", - "Final error: 0.0162\n" + "Initial error: 0.0587\n", + "Final error: 0.0141\n" ] } ], - "prompt_number": 26 + "prompt_number": 30 }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", - "\n", - "fitted_images = [fr.final_fitting for fr in fitting_results]\n", - "browse_images(fitted_images, group='fitted')" + "fitting_results[4].view_initialization(new_figure=True)\n", + "fitting_results[4].view_final_fitting(new_figure=True)" ], "language": "python", "metadata": {}, "outputs": [ { - "ename": "AttributeError", - "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", - "output_type": "pyerr", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" + "metadata": {}, + "output_type": "pyout", + "prompt_number": 31, + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD7CAYAAABgzo9kAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nglChiIMXBEGoUMTBC4IgVCj/A0/cDSsJXfRbAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD7CAYAAABgzo9kAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQxEHLwiCkKGIgxcEQchQxMELgiBkKP8DexoRXQX29B0AAAAASUVORK5CYII=\n", + "text": [ + "" ] } ], - "prompt_number": 27 + "prompt_number": 31 }, { "cell_type": "heading", @@ -157115,7 +163687,7 @@ "source": [ "Gradient-Descent techniques are not the only ones that can be used to fit an AAM to a new image. Menpo gives to the user the ability to use the regression-based Supervised-Descent (SD) method for this task.\n", "\n", - "Let us train a new AAM model that employs the IGO features with double angles:" + "Let us train a new AAM model that employs 2 pyramid levels of the IGO features with double angles:" ] }, { @@ -196160,13 +202732,13 @@ ] } ], - "prompt_number": 28 + "prompt_number": 26 }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Then the regressors of the SD method are trained using the `SDAAMTrainer` class as:" + "Then the regressors of the SD method are trained using the `SDAAMTrainer` class. Below we build such a fitter by employing the PCA model weights as the regression feature." ] }, { @@ -196184,7 +202756,8 @@ " noise_std=0.04, \n", " n_perturbations=10,\n", " n_shape=25,\n", - " n_appearance=None).train(training_images, group='PTS', verbose=True)" + " n_appearance=None).train(training_images, group='PTS', verbose=True)\n", + "print sdm" ], "language": "python", "metadata": {}, @@ -228698,7 +235271,7 @@ "stream": "stdout", "text": [ "\r", - "- Regression RMSE is 24.01563.\n" + "- Regression RMSE is 24.01685.\n" ] }, { @@ -235210,7 +241783,7 @@ "stream": "stdout", "text": [ "\r", - "- Fitting shapes: mean error is 0.040127.\n" + "- Fitting shapes: mean error is 0.040369.\n" ] }, { @@ -241730,7 +248303,7 @@ "stream": "stdout", "text": [ "\r", - "- Regression RMSE is 18.63835.\n" + "- Regression RMSE is 18.93326.\n" ] }, { @@ -254730,11 +261303,36 @@ "stream": "stdout", "text": [ "\r", - "- Fitting shapes: mean error is 0.027796.\n" + "- Fitting shapes: mean error is 0.027969.\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Active Appearance Model\n", + " - 811 training images.\n", + " - Warp using CachedPWA transform with 'scipy' interpolation.\n", + " - Gaussian pyramid with 2 levels and downscale factor of 1.1.\n", + " - Each level has a scaled shape model (reference frame).\n", + " - Pyramid was applied on feature space.\n", + " - Feature is double_igo with 4 channels per image.\n", + " - Level 1 (no downscale): \n", + " - Reference frame of length 14836 (3709 x 4C, 75W x 74H x 4C)\n", + " - 133 shape components (97.27% of variance)\n", + " - 500 appearance components (86.62% of variance)\n", + " - Level 2 (downscale by 1.1): \n", + " - Reference frame of length 12228 (3057 x 4C, 69W x 68H x 4C)\n", + " - 133 shape components (97.27% of variance)\n", + " - 500 appearance components (89.56% of variance)\n", + "Supervised Descent Method for AAMs:\n", + " - Parametric 'mlr_fitting' Regressor\n", + " - 811 training images.\n", + "\n" ] } ], - "prompt_number": 29 + "prompt_number": 27 }, { "cell_type": "markdown", @@ -254770,8 +261368,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.0630\n", - "Final error: 0.0315\n", + "Initial error: 0.0728\n", + "Final error: 0.0246\n", "Image: " ] }, @@ -254780,8 +261378,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.0683\n", - "Final error: 0.0291\n", + "Initial error: 0.0686\n", + "Final error: 0.0304\n", "Image: " ] }, @@ -254790,8 +261388,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0517\n", - "Final error: 0.0352\n", + "Initial error: 0.0578\n", + "Final error: 0.0420\n", "Image: " ] }, @@ -254800,8 +261398,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.1147\n", - "Final error: 0.0421\n", + "Initial error: 0.0609\n", + "Final error: 0.0343\n", "Image: " ] }, @@ -254810,25 +261408,50 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.1027\n", - "Final error: 0.0261\n" + "Initial error: 0.0897\n", + "Final error: 0.0264\n" ] } ], - "prompt_number": 32 + "prompt_number": 28 }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", - "\n", - "fitted_images = [fr.final_fitting for fr in fitting_results]\n", - "browse_images(fitted_images, group='fitted')" + "fitting_results[0].view_initialization(new_figure=True)\n", + "fitting_results[0].view_final_fitting(new_figure=True)" ], "language": "python", "metadata": {}, - "outputs": [] + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 29, + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAAD7CAYAAACYLnSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n", + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAAD7CAYAAACYLnSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nNNNMM+0cMBPMTTPNNNPOAfv/AU5Cu6davSlGAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 29 } ], "metadata": {} diff --git a/notebooks/Deformable Models/AAMs Basics.ipynb b/notebooks/Deformable Models/AAMs Basics.ipynb index f0e8548..7d30133 100644 --- a/notebooks/Deformable Models/AAMs Basics.ipynb +++ b/notebooks/Deformable Models/AAMs Basics.ipynb @@ -1,7 +1,7 @@ { "metadata": { "name": "", - "signature": "sha256:a03fde015126fe0c925f16dcbc29f1a1906f255cd8be4122f962a837798a4cd5" + "signature": "sha256:faf6bdd67dd4e617f1d57b8d576df93ccd4cee550e81e531faca06aac31712b2" }, "nbformat": 3, "nbformat_minor": 0, @@ -75,9 +75,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAD7CAYAAACc26SuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAD7CAYAAACc26SuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvWusbWlZ7/l7b+M2L+uy9669qdoFhRQICCoqBBKINApI\nH0U8eryk5SIaT6w2Rwl9ovgFOWmlTjwNMUdPjI2JktAEO9BitK1G2oaO/UFETqc1RRQkBVW7oHbV\n3usy5xy399Yf3jHmmmtXFVVF7YIqnE+ystaca44x3jnnO/7v8/6f//M8IsYY2drWtra1rT0lTX6j\nB7C1rW1ta1v72m0L4lvb2ta29hS2LYhvbWtb29pT2LYgvrWtbW1rT2HbgvjWtra1rT2FbQviW9va\n1rb2FDb9jbjoK1/5Sj75yU9+Iy69ta1t7Wu07/3e7+UTn/jEo379/v4+BwcHT9yA/gXZ3t4eV69e\nfcj/fUM88U9+8pPEGB/Vzzvf+c5H/drr+bO97va63wzXvJ7XfayO18HBwTfk/X4z/ny1xXBLp2xt\na1vb2lPYtiC+ta1tbWtPYXvSg/grX/nK7XW31/2muO6/pPe6ta+fiRjjda+dcscdd/DLv/zLeO/5\nuZ/7OX7lV37l9EWF4Am47Na2trUn0B7rfbu9z6+ffbXP8rp74t57fvEXf5E77riDO++8kw9+8IN8\n9rOfvd6X2drWtra1p7T94R/+Ia94xSvWj6WUfOELX3jM57nuIP6pT32KW2+9lVtuuQVjDD/5kz/J\nRz/60et9ma1tbWvfxPbpT3+ad73rXbznPe95WGnd12q33HILVVUxm824cOECb3nLW3jWs57FbDZj\nNpuhtaYsy/Xj22+/HWstb3/727n55puZzWY885nP5G1ve9t1HdfXatcdxC9dusTNN9+8fnzx4kUu\nXbp0vS+zta1t7SlqIQQ+/OEP81u/9Vt8/OMff9D///zP/5xXvvqVvOcT/4n/8L+8i2//rm/nypUr\n1+36Qgj+7M/+jMViwWc+8xn+7u/+jp/4iZ9gsViwWCx4xStewe/+7u+uH//qr/4qv/mbv8lnPvMZ\n/vZv/5bFYsEnPvEJvvu7v/u6jenx2HVP9hFCXLdz3X33PfzID/8IUktCiIQQKMuCpmmRUiKlIARP\nCAFI25EQwoN+CyEIIaCUOvVYCLHmmjZfq5TCe7/moB7uvJumtR6ek8N5IUYQAkKI62tLKQCBc+7U\nNUeTUgzjixvXS2MUQuBdRCnwzhEFKKUQPhKEhhA5Py/43pe8iExFsjxjPp+RSUXfdSyaJWd2d8mU\nBOfRUmAUlMYgieRZgXctbdvQtQ3TaopE4om0XcuqrsnyjLIo6GzESIENFik10QYi0LYNgUhUmqbr\n0FrjfUCp5C/0IVK3HXXb07mIRyC1JiKJEZyPOB/onEMIgfOeoiiwzvHA1SVZllHXLSAAiR4+KxfA\nxciqbvEx0nuP1hotND54AIIPBCI2BoKPxOjTZ016Pp0ThJTEECB6wA/PC2KAiCcKhZSagCbEiCAi\npAQiQqS5KoVAyDjMiTRXBObUnJExIuLJPIpEiBJEBOJwTDr6ZIpEYhz/e/K8EAJCeg+CYSyodM71\nWYD07SAFhBiAyIc+9EdcvHjjI9+Q18FijPzUG3+K/+P/uQPxdPD/U+Rtv/DLvOud/2H9ml/6979E\n/gZN8ewMgOWfHPP7v//7vOMd71i/5iMf+Qi/+Lb/nuOjBa957Wv4o/f9EbPZ7DGP58Ybb+QHfuAH\n+Pu///sHjXPTPv3pT/OGN7yBCxcuAPCMZzyDZzzjGY94/ttvv533ve99XL58mZtvvpnf+I3f4A1v\neMNjHudXs+sO4jfddBN33333+vHdd9/NxYsXH/S6X//1X1///cpXvvIhI+jW9vzjP/4jbd+hlELK\nBAQhBPxwc/d9S4xxAAuPlBLv/focSqlTovkRzNeg6H0CwgHMx9eMx7oBTCABtZTy1HPj66y1A+im\nx8B6vON5R6DfXADGccS4CfRy/VwIAa01zrl0DqmIgA+eEEBICEJSKnjWhRt4zrO/m/vv+jz7N+wR\nbcHV5ggZIm3TMK1yGteQVRO87ciLgt62CCnJteZK2w3n96gYuPfLlyiyDDlc38eAbTSWBLbdckE2\nrYhIXGPJCsOVK1eQymAJuBDJsgLn3Po7a5ynKCfYCG1vaXqLEJrOWoQ01K3FOc+iaVHKYLKMxWKF\ncw5dVNjeYa1jsaoTXAlFsJ4oJV5EFouezvbUbUdRVOR5yXJ5TN/3aeHXCl3kNE1HjBHneqRWuOiA\n04uzICIIp25oITy9D2idI2ROiBKJRAxwGePJ3DsBTkjge3rhFxsgfjKf5Po4IQQheoIICdw5cToC\nDu/DcN40PhXH85zMuwTgaVFIx26A+XBc33c8lH3iE594TBmaj8Y+85nP8Bcf/9+Z3lYgjMC/PHD7\nf/yP/PK/ext7e3sALI4X6L0TkiDMAweHJ8kun/70p3nTz76R4t8YpmcL/q+P/Z+8+efezEc+9JFH\nPY7xvd999938xV/8BT/6oz966v/XOqMvfelLec973kOWZbz85S/nBS94waNyWG+99Vb++q//mgsX\nLvDHf/zH/PRP/zT//M//zPnz5x/1WB/JrjuIf8/3fA+f+9znuOuuu7jxxhv50Ic+xAc/+MEHvW4T\nxB/OYox0XYcYvFPv/dpTHgFuBOXxAxVCrD3YdJO6U5Hdaz3fa71zrfX6PCcLRb9+XbqR1AD+GmP0\nAOAaIQTGnHjXI0CPwH/tAjACxrgjGN/f5hivPU8MnohESYMgIGJkrjQ//Nrv5dxMszsv0NkORiui\n9xQ6o8ozlsJzYWdOkRt811HlGiU8Mnqk97R9i5CKLKtwrse5lvl8Tl3XKO/x3qMzQ13XaK2JIZJl\nJjmNgvXCk5cFDxweEJBonaGUTwvA4BmXuWaxXGCKktxotMkIIabPWEL0FiEkeV4QQiRGgbUuzQfn\nsb1FG8PObM7xYknbdJhME6Ont5bpZEpmM7q2o2960nouybICpRS9tbRtv17otTZILbG9Rwg2vmcG\n7FPJIxcJMD0eKQXW9mSZQkQJMRJFAukRxKOIwxyGGAMhRIyQ6TtcLwoRBMNcHkF2nJthmCMOj0cI\nlX5Qwwcuhs/8ZP5o0vExrSaIYaeaxpF2BDGqYWc37jtg869Nu9a5ete73vXVb9hHYVevXiU/kyNM\nuqaaSrJJxuHh4RrEf/j1P8z/+rE/htd5/JEn/Ff4oXf+0PocH//4x9EvVOS3JE89f43hY//lY496\nDDFG3vCGN6C1Zmdnhx/8wR/k137t177qMe94xzvY29vjAx/4AG9729s4c+YM7373u3nTm970VY/7\nsR/7sfXfP/7jP8673/1u/uZv/obXv/71j3q8j2TXHcS11vzO7/wOr33ta/He87M/+7M873nP+5rO\nJUiAHUhgrHUCytHrHUFv9PRG4AbWnq21du0ZA2RZtr6Bx+NHD3kES0gAa4xZPzdeP4SIkhqkREmN\n7ZMHp7UeXnvizW/esEIImqZZe+fjYjSOuygK2rZde//j+TbfV/LEJQGBiJBLODOb8ZqXfBcXz+1i\nTODMDWewIpI7qIxhbzrFdw3nphNc2xLaNm2ye0sU4OolUYDUaavft0sEiUrwzlEVJVGQKA3vqKoK\nIQSHVx8g9A4zKQlIfBc4Wlq8FLggOF4cs7uzC3Sn6KkoFbnJ8CEglU4A2vbsTCvQGceLGmMMaFit\nauqmHUDTEaIjeE/rHNoYpISsMDR1gxCC3Z0dDg4XiCgwSqNNzrJNXubmDi0tpAohIt57rPcIeXph\nTZOI9XcV10Cnhu8u4lyT3hP9AJwbh4pEwUihEuYqSQzgR7AmcSJynOkDELNeFA2Q5rCIHoFCCDlQ\ndIKIPI29MS0Y432DEIlwEpoYA3Lt2K75l/Xf4mFA/ImwF73oRdjLDv/3kfzZhvbvevbne6fiaP/5\nvf+Z8EuB/+39H6GazPid3/2tUyqO3d1dxKE8uTeveGbzR0+lCCH46Ec/yqte9apHfYyUkttuu43b\nbruNruv4gz/4A9761rfykpe8hOc+97kPe9z73/9+3vve93LXXXcBsFwuryu/D09QAazXve51vO51\nr3vc54kbd8UIeHmeA6ypk/GLHIE6hECWZfR98rayLFt7wZs2et3e+/X/x8ebwF2WJdbaDTAVg3cF\nfd+T5xld151w7DKuqZ8Y49oDHYF4kxLapFg2FyZjzKndxDjW8XXKZETn2ZkV/NgP/gBPO6vQMmNS\nTQhdRyUFZZlxYe8Mou/xUiJioChLlBSIEAje0i6OiLZHZgYRPEIpvF2xWq3Isgwl87TQGUnbtugs\njatpGiZlhZUNLkZCDMP7V7Rdi1SGPC9xLu1Wuq4jz/PBmy+TN2x7QnDEXmFkAnmiZDabsWo6IoGy\nzBFKEYPEWotzA90xLL5nz51htVqlXUcUtG1HVWbEAHNfcHVRD3PHnFBsGzscISRSRqQU9M4hZFyD\naQgh8dzjbmkNt8M8EhaBwzmLX2OgRKkMrTIIDAuFIIbhBWpzgRgojk0AjazjH4n1CGmM5CA2aZ00\nzx5kIUA8OV+MJw7DyP+frDRy+Pvrm+939uxZ/vIv/pKf+Omf4NKfXOL5L3w+H/7LD693wAB5nvO+\n33sf7/u99z3kOd74xjfy3t95L5c/dB9xL+D+PvB7v/8/f73eAnmec9ttt/HOd76Tz372sw8L4l/8\n4hf5+Z//ef7qr/6Kl73sZQgheNGLXnTdtfPfkCqGj8Vi9GQmH24qgesToCqdPFY48bKUUmuqZQT1\n9U3pA0pK4sANaiFREbRUa49/pCy89yn4oxR915ObjKACvbNpTEhMprHW44JFKpACiBE/cL/juUZA\n2AyGjo/Hv9feekxeUXAeHx3GZInHReCtQ0qNyguEg4vn9/lX/83LKEVNri+gJNywv4OInuAdE6Eo\ntcQjyExBvVxSKQ0h4LqOvKxQVaAwihDB+UCIkbKY4pwnxIjUiigU7aqm95ZcgOstpcnofUvUhlxl\nNF1Pb3tqLM6FwYsEhMCOC6gQCJkWgygEVV7QWod1DlUajICm6xMP7XuICiEVfdsTkQghWbUNzqUF\nI/RLfHBMJzOiXxJCwDmHMSXeBXZ2d3BRcrhagRMJi40ihEimKlxsCUGAVITQo0QKWMboB4828dGI\nkxsuxhF0E/gJafDRI0TEmApBlmiMKAhKnLggagiQh5MYCMNZPJsc+shgjy51GNYcRwxizXfHFBRZ\nz+9xbF6o9Y5ifG59XqnTWYMgOepxoH7Cmvr5etmLX/xivvCPj10PPdpkMuEzf/MZ3v/+93N4eMj3\n/6fv58UvfvF1HOGDA5u//du/zXd+53fykpe8BGMMH/jAB1gul7zoRS962HOsVqvkbJw9SwiB97//\n/fzDP/zDdR0nPMlBXHDCJwOnOPATgNzgiwfPtu97tEo3bN/1aClRUlGYDBEiPgaEkQm4pWTVtQQ5\ncOJC0vkURIzOIQQ4d+JFX8tbx+G31hop0v/HcQaXFhYf/Xph6fv+FO8u5ehlOpSQ65vSe49UbphM\n49ZZ4Gzg3CTnVS/9Dm66YQetBUpG5tOK2Hfszebc9c+fZ+/iTchhOx6dZ2daIaPk+PAqZV4ggsdk\nhq5LDpzJCpTW2L6jLCaEmN57vVxQlQrlFNpIMlMQhgVlZ2dC3XRpx1MYOhtwNoFpURRordd01lr5\no9MWv3WWosiRTtF1PUJpnHWs6hbnI8ponHdMJiXLVYcQYDKDEI4QFN6ncQuRvHClDEUhWdVdoh2c\nJc8zTNfTdwlolZZIaYhBMKl2qOuW3trhHHG9mxjQ7hRAjj8naiZNiI48L4gxpPnmw+DpB0SIA8Vx\nAgYJdjdUMCKeAHZM4H0SeByPZz1X4hj0jGI9tlNB8oH0GVVRm4FQIUavfKDpYkBKtRH8fGrZZDLh\nF37hF56w818btKyqire//e18/vOfRwjBt37rt/LhD3+YW2655WHP8fznP5+3v/3tvOxlL0NKyZve\n9CZe/vKXn7rG5nW+VmXfE5J2/4gXFQ+fQrppX/jCF3jB879t/XgTxON6Up7wxjAA/8AHIgRGa+gd\nEoHUiklR0nUdUilab2naFpmbdcBx9Oh9TLxpOqfCaE0I7pRX7Z1HXsOpK7F54wyAPIDzyHePXPu4\nIKxfH1kvWlmWYW2PUIrgQSuFipFpofmFN/0kF6YCLSJkOfuzCXs7Oxze/wDndnYos3T+vd05xwcH\nEB2rxYI8y/B9N9BEE44XS7LcoKSh67qB3x3oJSLettTNCiECWTUhCoX3geginkhZTlgsl9RtQxCw\n6nr6ztH3nrKqBrrphP4qy5K+dxwtjnEB5rt7uBCo2xbrAkhD0/b0PlB3HUhDVIbeBnrr6FyKHQgU\n999/P9Y6ptMZdghWlmXJ1eNjjMqQKITJaPueIp9y191fGhZngdEFnh6iTHEBZ5FK4EIKIIbgibiB\nSz6h6cQA0CcKp0AIHh9O6LoUfBZJebKheAKSyoTNmzUSgj+1WEh5etHYpAxHqSOAQq2PQaR570dZ\n4kgZcaJUGU1GtX79OK7/+v/+33zLt9zyiPfjNu3+G2df7bN8UnviRNZ89Qh2xhj6vsfkxYnHOwKo\nUkQfIEa0MYDA95bK5EitEFpx3DYD/+po+35QdJ1Wk4zUDdGvdbubHvS4YGRGIyJJKzwsAFJrBskA\nYSOouQna13p1MNzA4oRySZK44YaVEul6SgVvef1reea5GQWW+XSC84HSaCop2Lt4I8YYnO0oswnW\njgtTZD7fxXtLDIFJXqCzDGN7UJK2axFKIULEaIVAEmOg945qvkPTd6AztNR432Fth5ApaJwVOUf1\nkq7raHqL7QNapzjBJj01BpSlhLIoWNYt1iZaRxtJ3XREFELk5AGyMmNV9yzrmtZFXIjkRUnb1mht\nmEwmNE03xC4CSmoEmsl0jreOvnfY1QqT5yyXx0ynFW61JIY0ntnunHrV0DsPaYln1FYLAcF7lFbE\neE2wkxP6Ls1LhRbgXfq+YkjPO9abp7W3PXrZ196Lm3MgKXLGx6NaZXzuRMESccPRYnTaN2JII10z\n7ArE5nMDb74R2NzaU9ue3CBOxJiToNS4PR893wRQJwk6o+ciISU+iKSrFkLQ9h1t6/GDeiR6EFqm\nhIcNXfmJV+SRIgFaCHHt+YxeeFowPGVR0rYtYfhfFKx5Se+GhBOdPN3NYOUmoK9/yxOAT8lMEh8j\nSkQKLXnDD7yK5918hp1ccnb/RlzXUGhNWeSEGGjaFcrMCFqCVIgYyYsKLZKiZLk6prNLptMp1kek\n1jTNEqUMxID1lhAE1noCknK6Qwg903KeEmKcQ0pPUUic9wgh6bomUVg2xQuyzND3Dh8CVVWlgOjw\nffV9TwiBxWLJZGcHHwJt22IySfCWgMdkGe2yxoUI0aONYmdacXS8IklGbYpZhASwbdtjrSUG6HtH\nMJK+s2Q6o+9bfAzEIJASptMJ9aoHqQZF05iklai1GATegZIGhCfGBMWnv6cTGmdksKVMUshEQSX+\nPQ5JOdcu1A+a4Q967iTwOF7r9LxM+BtGKeMpjl1e81zcOObk+PR7fO0WyB+PfelLX+Lbvu3bHvS8\nEII777zzIXNkrrc9yUF88ESHCdh1g1wtBqQYJicCJRLn7ZxbUxZ+iMaLGHEu0DlLEMnnEgCD5y5C\nymEzxiQvnvHGM2niD0GglH2X9NKZNgSXVCS2bsmkpCcglcKHlP+XvFCNiBLX25QOsuGBb/L44zXD\n4HHl2qCVAqnonSO6lu/49m/lxS94DjffeIbZbIZEsHfDeRbHxwOIOyajukVGyommvnKMsg6Mpu4s\ni6NDZrMZXd/inQPXkhmVqIwoybKMzvYgIqFvaJc9UQg8LWpQ7tjeYhD0rsO1K4q8QiHR0lBoh9Il\nSqa4Q103TCYliEAIaZGbTqcphmAUTd8xKQskik50BCk4Pl7gvUxJXNIgtcHaHiUDPgrKsqJpWtq2\nRZDAN8tzmrbH+oC2kWlR0XSWoihApl1FV/cDLxwwRUbX1uk9hbRr63qHE4AcAn5RIqIAGfEhpt1Q\nZAgeronqE4BXOcGl5CAhQsru3ATYa8D62nyA0U6c/of22sfrhTX4Jk/8wed58LkBwvq5sHYcTmkj\nt/aY7OlPfzqLxeIbOoYnNYjHAdS0UrRdhxp04mqQpCVZYNrW97Ynz/JTN44QIoEhYLTBEchNhh28\nxpGqkSLpriMgxZByLU5ujE2vefNxCAE13AMxRowQ5FkOUlD3HTEmNkaKBNbKpKDrOsNOnbwP7z2E\niBqCo945pMowEi7sz3jLv/5X7JrAmd29NXBJo5nu7uC7lhhhuVoxn8/Jco1f1jRHx/i+I59OiFJw\n7sw5lATbW1rvKcoKRyQjebVd0xK8hRBQOtELMXqM0NTLmslkgswSA7U3q2jqlqOjIxb1Ehs8Xe+J\nwaOziq63SGkQQuNsz2Sas1qtkjplCCIqqahXK6rJhJ3dKUJplMpYLGs8GQeLBo+hD2CMQRtDvVoR\nw7joRpq2JcYkD1VaEL3F+h6TaxbLFd5HmiHjN8sMe9mMumvJjMZkOaumT/EABNpo3DA30gTSECNS\npkQfONmJXWtCpAQsH/qB51YPCeAP55VvLu7XPr/59+ns0YdWomw+frhFZGvfPPakBvFN/vhUKvoG\nmEYpkeIk8WEMUI6KCOs9mU4346hHHkEkBQ8tWul1FmLwHrmRYDRKDzd/tNHDDkCgkAOfrVBCkmtD\n3XcQUj2NEMKQzRdxnUVEcMGT5wV91yVsUAqIqGGbLETa5kfnmGrJW3/shzhXKZ5+4Wncc+lezpw9\ny2Q6Tby/FKiYIWVGlmWUZclydYyMkfm5ferVksnuLq21GCFZHBxSFDkmS3LMputwPqKVTjVDXMei\nXzKfz1kulyghCd4nhY8Q2BixRFzTUdc1Mcb0ObYNWZZxeFwTuqQPH75Fqqqk73sA2rZNuvFYEInk\neZ7+JwJRKKqyJARPkJJF3SZqwkd67xA+UBY5SkgWxw0my/ERYhC4EBFaEJRJ8sWuTzx8FEijB2dA\nUzcNhdF0IdLUTVpoo0dIvQbnpFARxLGiipDEmAKdI7W3Dk3GOHDOSSPunB0T8E9TZdfEQtg4/qH+\nfiTbvC8e7t55rOfc2lPTntwgPvwepYNukO8JJU/x4qOXpJTCGHMqqDb+1krhH4LKkFImEIkxqU2k\nJHpPVKd13JtFtpzzKe6vNcZk9MFjfcra8107qBzSNjdTGif8WiaZdhJyUNFIsvwkCCgAPWh9lVKo\n0PEdtz6DFz7rJm48u491gluf/ezkwYeQdgxhBMIWIQR931MUBbKQdM2KfDKnt5667uijZzKdJp66\nNAQE+2fPc+XggCLP8UZjm5a9omI2n6HzCjXw3tGl9zDbmSe9vOMkjd02CC2o257ZbMJi2WJ9T55l\nRBHoB8lhWU2pl6v0XQ0qHNv1CCUJAqKMCOVTOarYM59XfOXKEqUyDg+P2dmbY7uO4CPz2QxrPdY2\nxCCJUhBsCqwiNE3bUxQVx8sVREnfdchCU5WT9NmKnv29CVeOjwlNgxCaxvUYrfHWIRBonScJogIR\nAh63TvY5veOTBD9kaEqDD/5BnvDXKiV7KBrmsZ7nobz7rwfI7+3tfc2yua2dtrEkwUPZkxrEQ4z4\n4Ncyr1GBMoKkGzTIMcR1kajN9Pl1ISsEtk/b5CDFSVW7IUA5HgtJkmgHdYu1Nnnc+qQQVvLyh0CY\nC0Qh6GyPi54owUhNWZSs6lWS9PlAHyyZ1qkMQJ8yM9u2TZmlXY8cxzrwk0JleOe4cW/Km3/yR7jx\n7BlmkykynwMWZTRypHC0xnsHUpEVOfVqyTSvkEHidZZUDDFC5hEBZASJJLhIXuU0TU1ZFJhM85Ur\nlynKImVAAlmR07cdQgmaNi10rl5R1zWzyQxrEzV0dHzM7pl9vFyhLHS9I5OpRscDD1we0uYtZ8+e\nZzqZkBdlGnOMrOoVwQWEEtRNyzyr6PoeYzQemJQ5xyuLVorFcsH+3j6rVUuMDh8TraJ1RlaUXL7y\nFabTGU3XkZmcq4dHSYMuDCFErHVoFfG9RRrJanUMRIo8ByHpg8e7UfInsC6kQKutETEi5VCEbcOj\nTpUATxyGiMSHE+31V6NAHo09Xh3xQy0C1+4Gnii73nXAt/bQ9qQGcSBREiSdtBh14iJlMephyy6k\nWHu6wKktZhwWgsykLMLOu1S7w3v8RlU5MXjmdZfUFH3bnQQ2k9AFqQY+VAjarsPojIN6NQRQJd4F\nqrLAe4cMgYijD55CaSZ5zmqxpCxKGu8T/+ocCkGmFUpl+L5H6ciydZwrIj/zI9/H8y7egBIKXVS4\nfokUqRKfzAsIgWB7iIGinCMLScTTrFpMliOzkiB7XFuT5wYz26Vtaya7c2IIeNvT1Qv6voEQ0MFj\nlWLxlftxtqVXkOucvm8IMXn83np09Fw9uMxisUiqDClpmg4pNUWpOWsMzkEInum0ZLE4pus0BwcH\nLOuOsiyYVgV5rhFS4KOgblYoITk+OqLpLEoZ2q6nKjJWqw6jFY33LBYrjMlwBPo+Fb1y3tMFS5Zn\n1PUCIVLQtCgKokhB1+VyibUpBlJNKvo+BWtzCZqItZ4yL2jbDiGT+kZqifUWKXSie4AQh5iBkPgw\nJvcM0j2G0sAuFeQa598TAZhfqxe+mTV8omrZ2lPZntQgvk6ECXEN0qOUEE5ukPH3ZunYkTKRUhKc\nQymZqBZnTzx0eVL6dfTKx+uaPNVcEVJivSPLszWfvq6MSEBrSXAeHSOTskIqCEGQFTluUDVUSlK4\nwHQyoxGShW2QpKQiGRPH3tQNpc6xIbKTKV71olt5+bd/GxMtIc9Bg+ojbd8x298niJTpaTLD4eKI\nSmfIFrx3aKNParYgEVqnZKWywGiBjpHgHCKk+ucSgRSRtlmCm2CyDGtbCqOIscO5lp2dPTJT0PeW\naDJ02yBC5HhVQ4hcuuceGgez+Zzd/T1MpvAuEpznzNk9VquWxXFDUzc0y2P62ZSzZ/fZ29+nFxF5\nJAnHx7ggwUriAAAgAElEQVTeE/qOLgY8AkKqp24M2Jjelw8dq7YjzybECFLnLFergVZKyhepBL23\nFKUhOklKjU/ceF3XVFVB0/V4n0rmxhjpu4aqKOmdT0FKF8l0Rd/XIERanKUEkYLhRJG8bh0GZYoC\nJHlR0bXLB83TJ4M9WcaxtetnT2oQT3ruMCR0nFT2G7MqgVP0yWbZ2c0CWSEEPH5NPwCpch0MhfST\nnnydgTmkI4tISoUf6vRLIdYSLaVUUi4gqMoSGUDGVGgohBSEK6Qgzwzz3KCiIKA4qGtQkhgG/0dJ\nvBuCZVIhXM9eFnjrj/63zIzEKIUqMqLUVPM9ZFsnj1CAUKkY1f6FG2hWPTGmgCmySLpuKZnkO6nQ\nlXeoKFgcHsFAO2VFyXQ+R8s5991zF5PJFBcNXgr2JufoVgsaZ9k7ewPTasrR4VGSsxkFnSDLMnZN\nhhcSlWesGsfB0SFHR0eUkwm7ezvrDFatFfP5ZFDiaNq25t57W+q65sIzL5JVGVUosMc1VVVy5ahG\nmYKD42N8lPjg0VLRWQ9CoFWGtR6pzFAq2LCqO3yIuL4ny0xSsBCQCrRO8ZKRPkvUlSRGT1VWHB8v\nmFUVY7m/uk6KFRcjKYtzTFMfmlWM8RXG8gkpCUeIVLBr07bAubUn0p7UIH6tbapURiBfF6yKJ7VN\nNjM8hUhgE33ytDubmgNkWmOHc1xb1zuEgCRJ6YxSuCHrIlhHNmTxGalw1qKlAGuJQhAiSJkhfCRX\nkp0iY5ZJlFB0wOW6ZuUsCJOKSw1AHmKqziiBQlh+7t+8nv1Sc7xa8rSbnoGPCis0ThvyssA6S9QG\n62zihCcz8tDQLo/pvWe2U2HbRDtEKYkyFfLKREdVljSrFTv7Z7ARnOuIzlHt7nN4/+WUvF0MhZyQ\n9DYwm+0idcZkFonBs1wusDGgigwlFEFIyDTS1GitOF4sWRwuWR6tUFqyszulLEuEiOzMpqnyoDHk\nec7xasnBnXeyv5+CYJNZhV81ZK1iNTSGEEIRYo8SGhcivY9olXG4XCCzDKUyuroBkZKtQows64ay\nKijLinpVIwT0fUtZTlIgWwo6mwp2xaYlzzJ61yfFkYBqklE3iVoRKBg6S8WY4iBxAHBCIMRUqjZR\nQ35dyXLcPT6ZPPGtffPZUwLER4DeLN8qQ5IaepdqTEutET6Qyuan+ilpi9wyKSpcTIWZpFIorU8p\nWIAkoYsCG5JeW2tNkeV0XTcEDz1lJolRoLUhRkFKdAwobdBSIL0nE5GdWY4MHbulhj7Sa8mVZcNB\nExGqIBPghCCTgd42TLKcTGqkt9y0b3jNd30H81nJ2YsXQClWy45JVdF6R55P0Ubg2pr5ZII3OVeu\nLphMpwglmEiN73sWfcdeVaGj4LjtiT6QVZrertiZTvBNj84UUQqsyZCzXSo0lQr4qFlcvoTwLTdd\nvJVqd4/DB+7DtQ2r4yOqomDpfVKEkNLzrffszPcQaoHKDFKkKo95kXNw5QqX+wfY2d2hrComsykA\nve2oqoymrbly+QGmO3sILWm7OpWH7Xtc1EN7MoXMM3YnFYtlw2qZOvJY19P1DqU0fZ8Khk0nUw6O\njnA+cLQ8IjhBVhREIUh5oYFcZeuMUmt9qpOu0oIqZEQTERi6Hnof8D5581INJYadQ4iYpJQxIhVY\n1w/qFYPQBYQGQpKMyph2Tw9lmzkIW9vaY7UnNYgLUjBRcbp9WfCeKCRCCmQQMCQBSaPWAcsRnI02\nw7ES6xzRxxRMHBUvIYWkBEPfy+EmHakZKZMSpW1bVFXA6PULMEqis6QvV9GTG8GsNJSZAQchCnop\nubJqOG4tQZpUo4SIjGPqfSoXa61lpuHfvfmNFGWOLqZIU+KURk0kZlqhtGF5cESZlQilOD5eUuwa\n9mZ7NH3ic+k7ovfMdUZ9cERRlkxmkyRB9B5VTvHapCzWVUN0YHKFVJqiyLC+Y3l0SAgOFzxaC5r2\nmKLKOG482aSk8alMro8R6zz3X7mKNhm1sEgtmO/MmU6mHB0eU5YVSqUdTtu2XL58BaU1+2fOMJ3N\nODy+QlWVlCiuHi8IQjLf2cW6RQoy6lTr27pApQYttwhkucQLTS5yhEot3Iip0mHb9+RlhXU9vbPs\nTnYJpM87y3P6QVXjg1tTLCkQmaqN5EVJ17VoJWiiJcbUAcj7pHCSUpEZnfr8eD/GNlEqee0xpmqB\nQqRWdwmgH94T3wL41h6PPalBHJEKXoXOplrgPqTsSpF0wW6s2z3QIGOHFilE0lHHoRmtEOssTV2k\n5gSIk0YTan25kxosY/EhIQS2T/rhGCHTBhkDMnjmeY4WoAUoJIVWCVzaFiEUxx7ubzsOG0tQBqkz\niILgHQiP95EsL1OTYqV45g0zXvqtz2GyW0E+JUhD4xy7u/tYH3GhZzKdoXONNBm2P0xKFSmZFAVt\nvYC+Y3lwyGxvnyLL6ZuW1CfS4byD+R59lORZRDQ19eqQL99zwGQ2oVkeg/RMioJlDbO9s2glMDJy\n9913k+lUezxGQWZyXIC6XWF0Rtta2q7Bh1QC9sYbb+TGm57G1asHzOdz+r5PlIIuODw84iv3XWbX\nzTlzbp+2XnC0SIWtVp1jsXAoZZjOplgvKaoMO5YjlmBtRzGZ0vZLtDB45ymznBA6ehfoe0tvPXmV\nAs1tXVNUFVlepDFIzaqpmc1meBeIQ6OL4D3aGLTUkJes6oY80/jOr9vxxSjXtIrWBiU1EcuYqj/W\nTJHSIKUegD8O6pWHTszZ0i1bezz25AbxCN464kYTBRgaE3tHMXTtiTHi7aBAUSn4GWWqIiiHBBgl\nJMpouuCHJsOBQqc6LAzqhLE2vtYa19tEzUiB0jrRJkqgiWRaYhBURg9yM89sNkvp7L2l95EuBq40\nnkPrQObrGh4iksq8+h4ZJJlUKN+hfM/b/+1tlNOCcmePpY1MpjOmWU7btpTFBC2hXdWITNE7z2Q6\nR+gMZ12Kx0VJVk7YzwsW0XNmZx8OjsD2zPSUS1/+Imf2zhAay/Ly/SyP7mFnWvD0m8+xcpFsZ0IW\neo7uv48YI/vnb+Keu79IrFtMiNTHR/gIeTXFWkdnU3kArQxKepzv0dKwWqz43Oc+x87ODrPZHJWp\ndQEsIyU702miYJzn4OoREU9elEgvWbY1x8uGnd0pzh+lhJ3FIkkciwlGK3Jj8D4M7fF6mi556tJk\nzCcVq7pBCEd0nigCyuTrTk870xm+txgl8dauO8lLKSmLcl0WQaJSFq6OSOuJUeN9IDMGGyxSDUlf\nIg4Znaf7ohIFRuUE1xHjSdr+Q9m1WvCtZ761x2JPbhAndUORxqxrbI8JPRJB9IFJXqZ6F0MLLhVT\nokaIATukPhtj0oLgPZkQoAxRBDQy1dhXKumkpaDrOiaTBJgyOqZFReo5KalUUq6IEFBy6A6UJymd\n9ZE2SJZWsegdB12LjQqpsoGlT3VIREzNb0WMFFmOipFCeF767c/juc84T3ZuH9sr8kzBpKAPgnw2\nQyqD857Z7g6WgJYpLuBDIMpUwjSvJgAcHh0x39tlUffMbzhP71rqtmZnukN/fJXV0QE6z7j5+d/J\ncrFk2dSIGDAhsFo1hN5SlROOVj1lMUFmFYvjQ/bOVKyahlXdEAMUVcXdX75EVk7QSjCZVEiS+qOz\nLYvlgtVqhdYG51KHpugte7s7rOqORbPEqdTyrsoLWtfTWssDV46SskUp+q5jf2+P4+UCKRhqxSuW\ni47gUs/UKA1YR0TSdysypdFVTkDivKPtkma86ztWbUq6qnRBAPqup6lXlGWJVinBK+3CIplJzahp\n7OBEbCQNIAYAF5xUOhyrEAtiTHJDgdooG5vsq3ne1wPAt579vyz7+jbYe4wmSOqQsX5JdJ5MKEwU\nZEKSKU3bdygph6QZAyEmL1pIchTSpm49YgiOGqHQUaCRxN6RCUXmIYuSTGp284pJkOzmmv0s/exo\nSREcuZCU2pBpQ2YyAp7eO1YOvrxs+MLREV84qnmgjQSZDU2eA054PDEl2LgeETzzfE4lEyDlRP79\nW/41O4XGeUVnBHo2RYgcKXO0qXBBoFD4ALmQ9EcHqOhS27a8JEgDeUnMC/Z3z2J9oJxP6boG0/fU\n99yLnpUErTk7m5PlE9xklzjbZXL+HMW0IrSO3C5prSPfP89sZ5fZ/nlUMWP//NMISAqdUUpDliuc\n79k/twtYBIGqqIBIUZjUVUdnKG0QUtP1loOjY6I2iee2C86c28F5j3WWprP0NnBm/zzBCrrWMZtM\n0m7LRpz3ZEoTvEtSUCJEwWLVIpXA5BKhHZPJBKGhmOQIGRDBo5SA4NFKIgns7EyHBQewnv1qB9EF\nJA6jwfvUOEPqDNsn5VAC7LHOeyr7IKWGoXZODAqBQcosVa8USTeuVMbX+zbbAvi/LHtye+JDIaim\n7zDGpNZqQ43usU6I0KnbjJYydekZbrBR4pWaJluUTjIxF06aTKyrCQ49IH0I5Fme0quNwrkeUeQc\nH9Ts7e/iukgjBJZIu2qIQuKDYNl0NCF1clc6pXjDoDOPMQG3EKiYqh6mnUGDRWBw/ND3v5Rp1hGL\nilwrXAgYkyNMyv70cSwbKvG2Y7VsqIqKRdOiywojPHmZYRHIvKTtW6octBRcWSzxCuZnUvXDo6tX\n6a7ejyX10FRErh4cJFldlXHMLs/6zhfQtBZXt+sAr/URlVf0oqUTHSAJEnZ3zyLkMV3bYoNnNpvS\ndKmOy2Q6wdqTYlhXrhywqpdoo1BZxpUHDtg5c5au7ckmFcf3X+XqA19hOp2iVUaeK+r6gM5ayqLE\n+R6hDLPZFJ1FvJMcLVdY67AxIJTCWk/fedp+BVEghUYPGNq2LUYplsslnU11yfMqx0ePypLnLIXA\nZDkIRRg628eYaqMvl/XaoRg5fjFIEtNUiidSRJlq4yhp8FIhYjhp2SBOqhU+EdTJmB+xWb9lS9F8\n89ojughvfetbOX/+PC984QvXz129epVXv/rVPOc5z+E1r3kNh4eH6/+9+93v5tnPfjbPfe5z+djH\nPva4B+hJVfLGLWLqZTn2OZTrRJIY46BFTjdH3/drna5WCi0TiI+d5MdzwUltZwAXA23fcbRa0TrP\n3fc9wGFv+eKVq9x1+Qp3Xz3kSwdHfKVuued4yaXlkloqojGgder5CakwtLNJtRI9M6PIpWBa5JiB\nc41IdjT87I//CBcunMXMzxAIeNcRhaLuLT6mptBCSZBDgs3eHpgMVUyY7OwSixl1l1L5dXBMTKRZ\nLbj7ri+yM5ugM8OqbciKip3pnKzM2Z1UtMdXIHjO33CRnf0LuKLEnLuInO2hypKIR7ge7IrDy/dy\ndHg/dbMkKxVmMmOyc4agNEU1ISKwrmO5WlLXNUII6lVDcAHb9fRdx/nz55jP51y5coWITgW2pKbt\nHJfvu3/wblOpg/vvv58YAlWZkxmFBM6eO4fWhqOjY5q6TqVl9/boe4dSGcFLbO+HglRx8JRZt8Ob\nTqfoLKlqsizD5BmBsfpholaCkLRtR9/bdaNb59watMfksU1v10ZFlBmODE+GF3lK1UcipU7NRTZe\nPwLsEwWsY97E5vW29s1rjwjiP/MzP8Mdd9xx6rnbb7+dV7/61fzTP/0T3/d938ftt98OwJ133smH\nPvQh7rzzTu644w5uu+22h6y9/FgshEDXdamJ8eCBp/KgYg3EzrkkLRzUKkop8jxPHi+sMz3VUM1Q\nDUWMxseM51OStutwMRAQ2JD4cx8k1gkwBhdJqdYilWbVRKLvEKHHRIvGYfBUWpJLyKVIICTAaJXa\nfimVSscaxcue92zOTKaI3RtBGVQ+IZ/MMUVOMSkxRQ4i9QdNqf+prZzMS7LJFLSmRzPd2cUQObjv\nS6yuXiKvJtx400VClIQo2N0/R2strYfi3AW6omJ+4RlYVdI4y6ppCA5u3N/j6pfvwS8PEX3Nffd8\nkcuX7kJGT320oD5e0Bwf85V7v8yX7v4SV68meeHe2RuYzCom04q8yDF5xqSa0NQNx0dHnD1zlt3d\nHQSBnd09bIDpbM6ley7h+8BsUnH+3D5GQ54pnEuNP7zr8dYiiSxXS/reImWi2OpmyeHRVcoyx9kk\ne7Q2lVWoqoo8N2iTyi7oYYc2gvJitaT3gVXr8Gg6m8BYmQKZFTxwdIwbioyVZYkxhixL2vJx8R/P\nxyAX1VIikWihh4xijRSppvrjKYL1SHYtB/5Y6qpsqZenvj0iiL/iFa94UBnEP/3TP+XNb34zAG9+\n85v5kz/5EwA++tGP8lM/9VMYY7jlllu49dZb+dSnPvW4BijkiVZ7TPYZO8xvJuuMgD16S5ulX2OM\nQ3H/JA8bFS3W2lOKAiHE0O0lEKNM8jEPmcqQXlCYDC0klcmZZyW7WcXZcsZUZUykYWoMGZZCRqR3\n5EaTCTm0mIv4AAGJF3LIQGx427/97ygKQz/ZSx2DVEE+303Bs5gAX+hUntaHgPMW6xxCa0RmcDFS\nsqQ7uo/V4pDJfB8z2ydqgzQZi0WNFIa6sSxWKyY7++izNzC75VnEapfzFy/i/Qq3ukxhLf/fJ/6S\n7r57cFcvc+/nP4fG46TGBsmZGy4ym59DZjPKTJEPi9KX7r6Hr9x3ObWpCx4hJV3XpyxRlXY+dV3T\ndS1lUbK7u0sE7r33K5y/cGPKGC0K2mbBmd0pt9x8ER8CXd8hZcq0PLh6FWt7+t6hpaFvO5zrqaoM\nqUDIuKY9UqPjQN0scS4ldU0mk/U4XPBM5jMyUxCjpK49i5WlsYHLVw6578oBnfNcOTjg8PCQg4MD\nVqvV2sO9lgqZxo65sFShY1fDFJvmWEgbMqUkXy9n+KuB8rW0yhO5G9ja18++Jk78vvvu4/z58wCc\nP3+e++67D4B7772Xl770pevXXbx4kUuXLj2uAaaeCamuSZbp9bITY0QLiV2lHo9jsX7Y6L4yZNaN\ndVbG48bXrDlDmbr5aKlSI4DhRhjrtaQa4Cl1X4s0gPG8fkgQkUIQA2iZr9P/nQvrtm9yY8ERQEDx\ntDzjbNEj9s5QEbBCkZcGjyT6SJARP+w8okoB2WJ6Bq8EXsC0LFgdHNHbFm1KFBCEpBeeCojRsXPD\nLsEHXNsyn+8jCgOFJixa2vsv8eV7vgChpTqzT7uqueFbno2OnuboCsW0pG+apKeO0NuGrm9xbYtR\nkr5uiUN52+A9GsPBlWWq7iclWiqk1tx07mkpThAU9eKYnTMZ3lkm1QylJL1wPPDl+yjnU3bPnOPq\n/QcURjGtKspcURQFTRu4Ui9QOtWp6WxDaUqcawc5n0IEi4+Kqijp2o7C5JzZO8P9D3yFerVEKo0W\nmiIrWdaBxeIIpKJpr2KdxcUOZ3sCqaGzFBoRHUoGgptSe8lE71DmhjNZQWaPeN4t57h5uoOPcOW4\nYRUkDyxWXFmUHLctHdA6RYyGKD0mhUuIAvzgxT9efvzhOO+HAu2t5/3NZ487sPlIW7LHO2mUkPjo\nUEIMqc4bEz5GzNBFfezSE0I4VSAry3OstThr168ZO68D+I3XO+fWfHuWZetWYps3wqZe3Q71zMda\nLmNJgDG7dORPNznQEeDnCv7HX/0fmM7OEPqAyfTgoUPdNsx29zBKg1Sp01DqvksILilrnGN5dIww\nGqMrwtCoom1bqtmUenVMVpQgBF3vmExniBjR/z97bx5nWV3e+b+/y9nuWmt39UZ3Qzc0NJuggrgh\nihsKGg0ORiVRo1EzOmb8qZMYjeaXESfJmPgzmUk0GifGuMQ1JnFDcccFAQWatYFea6+7nHv28/3+\n/jj3Vld3QNQxCZh+Xq/7qqpzzz236tb3POc5z/NZ0oy8v8LBO28jcARKGSamtpBiKZ2UKDMoR6OV\nz/jYJKHscbgf8zt//WlW+hECeMpZJ/HsR53OB6/5AVffdDcNv9JNv+y83Zw8M1GtCSkoTY4aMjVr\ntQZLS8skWU66tIxEEQ5SlJI06h7awiCJCcqSIs9I85wkiRlv18nTCEdIfO1TFCV1z6G+ZRrP85GO\nz6133ktQa1WYcwuO51ILPNIkJ44GtJtjpFnGIEnoJhGdJKYfhcMLbVrp00uJlgbJsHwuLFZG5KUi\nKwVGHiTwJojDMdr1Hr/0+O3MOA1EnNNNJYPM0Kj52BLW+x6Ndk43UoRxSTgQdNKUgckopcQIO2Tt\nCswQ3fLzSK5rFT2PV9n/ceJnSuLr169ndnaWmZkZDh8+zLp16wDYtGkT+/fvX93vwIEDbNq06T6P\n8Xu/93ur31944YVceOGF/3InC7YoEWWFh5ZDd/qq0rarkqtIQZTE1cBSDZ3YVeUcgxSU1mCwZEWO\nkKKCJSq1yoR2XRcp5Sqrc+T2MxqorlpyiSO65aMWzygpH2F62qOOMUrqa12GrLXooseukzZDo41b\nrxOVBukHCClpNH2U1hU70kBl5FmhJBCwsrRIw6uhXQfrONg8xVhT4ebrAWWRETRalXSqBU9W/fS5\nW79P5/A80zPradUCSgzjW7ZjqSGzHKtCWspDUlBmEVaAN9ZG54Y3/eqz2TEzwez8HC/+nx/iEbu2\nopTiknNP4Rnnnc7C4hJRklcGxkoSeA1cR9NqNOj3R8NOyLGkccZgkON5LfphyK5dm0nChGhukcXF\nRSTQ663gbZ9CKUHYC+n0UqTvk8QDWu0arVaTJMvpd2MCTyOVpNVu4GqH0gqQkjzvVfZ7jkN/MMBq\nzUqvR1qUGJujNUgNZDllXmIcHyU02tVIW3mMFm6JJ8Ckkrw3z/nbO7zoWc+iVRQkoWI+jzAUICRO\nzUellrDTZd/sIklW4gUBM9Mttm4a48Y9exgYi5AaihzU0br3a+Nnqc7XSt/+POKaa67hmmuu+bkc\n63j868XPlMQvvfRSPvCBD/CGN7yBD3zgAzzrWc9a3f785z+f3/qt3+LgwYPccccdPPKRj7zPY6xN\n4vcbonLlsUNd8JFxcklFuBhRsQXVwi1sZb5rpSAtchylK72UIQtDyiNC/iP/S4ZemqMkC0cE89d6\nbK41yJVDazE9FNIa9euP8gEd/ny0jdcR+v9TLzqfpg9Z0EQ7Cq3rKO1hTAlD8wlDpR1T5Cme45LG\nGVpCu9kCAVZIpLUgFIUtcH2PvCxxfI/SSlwgDXtoDHfftYeZQNPcuoXbZpd43Tvfz8LSClJrXnDZ\n07jySY/BxgnGDviTj/wDf/LxL/L1P309M+ummWo3qasBQig2b97M1vWTzPcGyKGka1Fa2mMTOHFM\nkiSEUUQUhTitJr1ed0g/r+6WZGYoihSNJgn7bN42he84LPQWiJOM1vg04XKXwHFpNxoUJsUJPHQM\n9UYTKPBchaMlWV7SD0Py3CBthic1YS9Eui5Cu6AreN/e2UOsrCxTmgo+KEuDFZo8T3FchevUEI6k\ntKBlRQyTVa2MEDmOSKkLuPTJ5/Lsh++isxRS5IK+gXzMZbDis5xl7Jvrsm9umaQoKMtKQyUvInyd\nM9YY46mPfTjfvX4Ps50BKXpoI3H/g/+1VfW/RxxbXL31rW/9d/k9jsePjwdM4ldccQVf/epXWVxc\nZMuWLbztbW/jjW98I5dffjl/9Vd/xbZt2/joRz8KwGmnncbll1/OaaedhtaaP//zP/+/vk1cKw9r\nACurPqIZilqVZVlZqLnOavIdLfq8PGIQYUUFHxRSDM2LYYTclWtaHRxTTY+q7LXIl5GBxNpKfISS\nObZyH+17bJvneZddgmsLSqdOEoW47UZ1OktVtU1Ki3RGFxBBGkUoY5EGCix4GoTAZlX/1tVONVRU\nkjiLqTcmKcIeWRTS6S6xcXqMKLMUCOobAt76uldy3q7TWez1eMKvvJjzNrZxBkssdvt84/qbWd9q\nsHTgENHSEnmaE3g+xSDhzsPz3LZvlisfdzrdfp9v336QL994J9vXT3LZI3ZR8yrYnwVc1yFNYmwJ\nnufT7/fJ8wJHO7gownLA+ulx+v0+RV6SpQVSaqIoZnpiEqWgPxhQq9fYd2CZbhwxMVFnet06BmHI\n4tIKQnlMTjQoS8HSwjJCKDrLXbpJTJSXJFmOdSzK0QTKRUsHaSWJLUFLsAZjNFq6BKKy0ROlQUlJ\nUqbYUqNKxcue91gev3WMJFeohqbT6TLIBP0B3L044PDigMh6eO31iDxHZD3KosDTmqarcY1gslny\ntMc/gq997xZunZulkBJ5Pzn8WDTLzyORH8eL/2KGsP8O/9WfdDHdvXcv5555NsCqJ+Wxg8m18rSj\nRLtqFDFEdOih+W3gepTY1f2gqro9qf9FEjfWot2Khu05LhqxKmc7ap0cW6GvTdJH9SelwjEZRle0\n8ykn5Wt//15UrYk/NlUJUgU+idCVYUNZ4mgXoQWFKYGKnWqtZTAIadQbDKIE13XQWlGmKUhFOAiZ\nGBujTCPiaEC0ME97ok1aFJXuR+CgLZT1DUhZYlcOcc8NN/DKP3ovr3jmE3js+Wfysj98H6+87PG8\n6k8+xN+98deYaNTJkgrFM7e0xH/+y0/wvMecxdnbNrBvcZkkSYjijG/eeZhekvKySx6P0hAnKX/2\nma+z0h+glOLRp23j3K0bidKCG/ct8I1b7sB1NOeccgKXnXc2ew8cxMo6/d4Ak6Vs2LqesUbA4cOH\niTPJPQcXyK3h/EfsJB70iGPJ4lLKcpiRGIXRLvML8xxcXMQIiR0KUPlKo6VgZmaGfn/Aodm9RHEX\nISTjre2Vf6s1RPEiSdZFCkHNqVFzG9WgmQEvv/SRPPmsE4n7EStLGX3TITSSfbOab/3obgbSx/Ub\nlLYa8lpTkOUpWhg0Kc2GxvUk003YuXEaI3z+4uNfYT61KFVd8Auhq2JC/HSn48+SmI9t1dz8o+s4\n6cTt/yrvdTz+9eNBzdi01pLmFclCaoXBkheVjoWWYigbO6ynpcCUFRpl1HoR9kg1rV2HrDwi0j/6\naq0lyzPUUJp2rWlxWZZIUSFXkjWJf9RqWdszH5lPjC4gI1y7tZahfQBFluMqy87tW1GuQ2lhEMUo\nr28KFUEAACAASURBVFbZe+kKESOMRUhLWYLjephSUFSAD/x6Dem6OFbi1WoMohCkoOZqJmQNmfRY\nmZ/DUmCLmCxzKBG4jotTnyI0DuXSfrzuIb79pS8zc/Ju7u2G7Dj3dP7h+7ezYf16Tj31dBAS3R5H\nN2rkToIQkrf8749y8cNP5VG7t1cIkDJHuNOsdHqcESV86Nu3cNsdd9FqNxifnOTFT38sG8ZqZGXJ\nG9/zabZNtpnvxvzo3v385tPO55RTTmKl2yUMIzy3QT/KKfIMz9W0xgLa7TGWljvMLiySxik7TtpE\no1YnDCNqzTYrBw9y91yX+U6PUkkKLK4KkEIhtUurXqfu+0TRgLAfYnODJxsEjTFWogO4osKQGxtT\nlBEntrahHcEg76NcgbQ5z3j4SVxy9gaKMicrQQcKm7e5e9+Aq7+5h9Spo31NmRYEvg+mBKloNQI0\nUPcbaFWALLBFRp502bFjmuc++QL+5rNfIxQOghxFjhHq2FPgX/XcOh6/GPGgTuIghtT2cjUZIyWF\nMZVmyBApYgyYvFjdf6Q1bkyF2DC28pS01qIYJe8KW14WxfACMTQEGIoYWUG1rzHkptLPGA01S1O5\noI+qcjmsvkd9cmPMqlgXVGYBWlWIDUnJ+eeciVUa6VQJ1hgQUmNt9TrK6iIiAFNYLKKCxzmKIjfk\nZYkZDmxd18ULPFYOH4SkT5llCARevYnnNym1BiptD6MEjeV5vvWhd3PGxU/mjOdfyWUvfA1vevkV\nTLkB7/3E5/jQH76ZWt0HIKjVSYuMybExXn7V/2bjWJ0XXHQBn/jqd1kO+2yZmWbXFh8lBPs6A2Ym\n2mjXRbkBd+29m21bNhFnJfVGwMxEizAzfO+u/Tx8+wynnXYyyWCAzSp3Hc8LSDMwRc6GTVM4yYCF\nlS4mKYj7A3adtBPPh/2HQq6+9jbmVjIiA1ZLXC3xpGbM9bFK0Gy2SbMCUxqiqIfJBXleoIRl/cQk\ncRTRjaEVVJ/14d4cG8dnKE0JNmem7RPIgtO2ree3XvIiyjiie88diCxDO4I40nzt2lvIrF/NTABX\ngjQVqUgIhacsWgEYXEehVaV8WRYFNu/zhIfv5MCBQ3z+xrtIpUKSI2GoqnjfQ82fBsVyX1XzfR1X\niFGJcTweqvGgTuKWalEbLKYs0EP6tBAVnXk0PASDHPakK4CvrBK3sYzE5wyV671QGguUpqQcVvml\nLVclbAEwBltYfO2s9tNLa1ar7NFgUyk1fB+zCjMctVTSND1iE0eFRZdGoKTl/HPPpsxK/JpHUUq0\n55EZgw48TJ6TZCmeH6CVprAlUlT4dQOUhUW5As/TFMkAaQyLy8u4NqO0BSWCiZnNRGEX5bjgaJqB\nR6A0B77zZUSxxBlXvBQaG7nyZa/m8qc8gSeccRr3zi+wf2GJp7zs/8Fay+xyh0te8/u8++WXsRLl\n/PP3fsS26XEufP0fkWPwtruk12S0fQ/f0awba3L5o8+ktJZWq0WeZ+zdd5B109NEcwvsX+ywfrLF\ncj9mPkz57fd8HC0Flz3iTMabAcYaut0OmzfPMDXZZNAfkJQe83HJsq3zox/czFwcVnA/4WDQBI6i\nXdNMt1ts37yFXqfDweWQfqdHFGVI1wEpUEagpaXZCvAdScP3OdwTeFogHUm2nNAfLBHlKUrCVH2M\nx5xxMr/2K7+EpzX7FzrDz90hti6f/dJX6WYCIQ02jlHS0PLaFGlctcGkRplKLsH3HITNcLWGPK88\nTI2g7lme/MidXH/zbdxTBigFwlRM4VGMipQHGnCu3e/+2Jv3xRg9jhn/xYgHdRIXYtT7rirRakio\nj1qsI3z2sfT+ygGmqq7NaH9VOdcrpSqPy2Hv23M9siytTIAr0VjckYiQqYSisrKSj7WM2BrAcIA5\nGmqu1XUBjkKpVNpIlQHF+umpyhRZaRr1JtmQ/CGsRWiFcjRGQJqlOK6Lpaz8I5FIrcmzAgewRU4y\n6NMKPLKsoNGcZqkbYZVHFCVMrW/huw5J2OXgvQeY3L6LpUOH2Nya5sVvehun7tjCSy+/BCEtzYk2\nX3vXm/F0wezsLM/9/ffx1695HiJPcVuKf37ri/nidXfwlzd8j4mXNhBSkB3ICf865LXPOA/PDYjj\nhLSoSDSNep3SGg4vLvL337iJx566DUdXcrrS9fj9X7uM6/fcxXs+/03e/PxLGMQFtcCj0WggtMst\nBw/xzR/sYTER1axASmxWw1OwcazFTLtNd2WZ8clxJsabJHGX0qQkYYzJLa4OyAqLwVIPPDxX4PsO\ngSuJogSBwPcEcZxUQmuO4rx1WwizDjcvrPDBl70I5QWEhw6gevuwXosiFdy2r8+dh1aInTGESaip\nGnVPUHMtjhsQxTmOUuRlCgaK3CCVxZYW13ERQpBmllrd56LHPoKb7lzkr75+M6W1aAHlmjV8LGTw\nvhLysYl9NKM5VuRt7WuPPc7xxspDOx7USRyGzEztDqvdCra1dt2OBpxr8durg0shq5bKGrYkx7A3\npZSYvEAx7KOLoS60ZSg+pcnLYpVlZwVoJSAvEUId6aHDEV2X4e80ek4KQVlYtKuQpIw1WshandhI\nfFvR8gtpsQX0Bz3q9RrGWBzHHXo+iuouRAqUMUihiPs9tBQEtTomL1HNceLMMN6uYUpDa3IdOqix\nuDSHNoZNJ5xAiaE2VuMrN+7hw5/5Art3bOeRz3k5hxeXqNU9LrvwPN70wucyscHHcVy88WnyOEQW\nOWmWcXili5iu2kIAznpNlpb4zXEO7D9EZkocrZFRQlgOaI23+fBXb2TnhvVsbE+xuBLTqLlc+PDT\naNYDNo/XEQI6keHwfIcDKwP+4bt3sTxIKZRLWXq4CpoknLB+gs1T00yMN3Bdj7vvnaMUBZPTDYoi\nZ6XXIYwMnufgBYreIMV3KumERs3BcQTClNSCBnmaoZREljnrp6e5d+kA435AQcyv/NITeecnvkLf\nKtpSUUYJwg0oTUmvl/GFH9xEisSUCZBjUDS8gEAXOFJBaYjSAUVZDNUxFUJossSgnJwsr4qAoNGg\nUJJHnXkKf3fNdfSUU813hkn2vowi7o+Veez5ssoMPqaguD9i3vF6/KEdD+okbocCRCMc97HqcWsr\n8lX/zeE+Iwz42qpj7f5r0SlKHUG6rDItpah647YcOqhXGPRRYhZDtb3Rc3bY8lGqOpGttZUjuqhs\n5DQCkxdIr0raQmusklitQanq1twIGvU2QgDCUBpQyqlq/6KCD5bRCmmSIx0Xz69RFAajMmwB83OL\nvPQNb2ZuaRkp4fmXPpVXPP+X+B/v/RD/8KWvQVnSbgT8xTt+j+UffpWrr76aF/3uVTSeF6AmFJ/8\n52/TeVeHVz7jCfzNm1/OIO1zz/67CZwag0HICetapP+U456bo2c04ecHbN7Qph9GZHlJNmxr3bt/\nFmssP/jOrbTrdR61ewfdbp9BqDhpeh0/vPMQWzdu5M6OIIxz3vOJr5LrOjEeFgclHRwZctLUBGdt\nn2HHpjaeb1he7rMSRkSpYXZulmargS1zyjyjzA2BH2BEQZaX1HyHNM1xkChpcIQi8Dxc5VRcAmtx\nPI89+++koODAyhIXnf0Itp9xOtnHrmbTxo30FubIshhdq5N2I+453GHP3n1Y4WFFgSpL6g3D5LjD\nzGSLIk1IfEGnmxBnVastSQvKQuBpiSM0eZpjCnCUJo77CJPhCrs6oP95StT+e+PMj8e/TTyok7gQ\nR/fv1uokj7aPto2q72P7fcYcrakCcjXJaz3Ebw+TsFASg60w5cOLwerwlKHmSZ5XGitCkEuLHR5f\nUul3rL2IaH2E3g+VBowtMhylKUqDDDRC66qfX+ZVS0VIEOA4iiJNydMMz69RFgVFWiLLEs930W6l\nD6K0RkiFKQ2e6/L217+asx5+BnMH9vPkX3kVF13wCP7ry3+NV1z5PBoY3v+Jf+Tt/997edfb3sB1\ndxxAn6Pxd3nVZ/ZMwZffcxMvfdJpzC9ERHFO2I/ZH87hei5awXPO380nP3gLaVKwcV2Tp599EtFg\nQC0IkDZnvN0GI7lndok9Bw4z3azzvsNz9JIE13dY35pgsG+OT13zXYwV+MEW+q6PIyzTruGkqRq7\ntk5zxq4N9JY65GnBps0buPmO20mNJrOaxeUO7brP1i0zdPshaZJTC2rEhaEsYny/RpwUBL6uiDvW\nVK0M4Os3XEs36pMVOV+/9QfoDYraY3z6X4x471eu5Zq7D/Dn7/jtSpve5JQICiRRmpAYRVII0BnK\nGDylaAaCqYYmUCkTG9p0uxF1XzK7kDPIwFhZ+Xiqaj1q5SIsdJeWqbUCAtel7jjMFgZndd0/cOL9\ncUPOtcn7/qr648n9Fyce1El8FEcq6/t/Ho4WtQLWDD5ZM5Q8on44SvyjRT1KwCN50bW3saMK3XEc\nTFEZLZfGIJWsdEukoDCmEoMavu9IJXGUnLMswzqWOI7QtWBoslsRezzHJbPpGh2XHEyGMAVFBla7\nKO2i/HHiQQSDuLIPK0tEKRFa0p4aY2y8Ttrvs3FmC7t2nsRCGLHb82gEAUmc0OknTLSa1AMfX2vo\nH/kcy77B0ZIDh2dZWekyvW6GNI0Ik5B1zY0UtuCkjRt48YUBaRzjBQ7CFgiR06jVmW60WFrp4/kO\nO7du4oVj48x2Qr6y5yYaz6qj1ykOfW4JOgGN5qkom1FzStY3Sx7z8NPZuXGMIuziug5lklGYArdV\n4+DhORQeUS8kHCQUecTG9VOsLK+AdLAWyiLH1YrJVotSCOIkRWtnqKxYebIaazl584k06g0Oz8+y\np3cnk69oI6SgdrbP0js6vO/tr2fj5q0MVpYJAKF94ixBaoPQw/VQZAhZIqyP50iagWbT+gnqnkOr\n5rPUGRAOepQSsrRqf+V5TiwMtqFJk4Q0ThibbJNGKWNBCxF2Ky/Z4Tr7Sc6Jn/S8Wav3M4rjCfwX\nJx7USdxasOYIwmN14VkLwgy/PVLpVsKFa6uQI1P7Sv7w6IvBsT3DtV+FrJJvdVxDWZhKAjUvK+Pk\nYXN+xM1I8xwlFXp4gRBKYqUd0vwlpXUQuqAkIEx6rDMtRJFSOg4lDq5wq/czGaIwFFnl3K5cn8D1\nUK6HdBziNKvaBnGIiSKi3OKvGyeQEHcH5BZ0vcmdB+a48eZbedTZZ2Hzkt/+43fxsc9fTc33+Ngf\nvYWVO/fw9FM38q6/EfQ/GcK4ILs24z9dsJuwcBibPIGFAwcZb7fR7RqdwyF77riDQkuajQmcwrB1\n+xZcW9LNQ1SS0Yk9kqJAOiV335tyy75lDveXcU9zqD2sgi2OX9Fk7qplHrnecMb29Zx80jTLnUU2\nbwwokpDcWASacBBiZUBROoT9PmE/pN9dYtu2rczNC1bCPoWRuJVXdYWnx6KEJEsSPFdhrKDVapGE\nfYQAz9VIqSqVXykQzpH+PgqkFkTdHsl4F4QhyXJyMjxRpytDrOyhlKAwFYxQCUNNS1xhGGvVaLdb\n9Ls9RJnRX+cS7o+QpUNeZkgKijynGGsRJwmdzjJTM1NkWUar3YRBB8sx85X/i0R77EBzbfw8WzbH\n498/Htwem+Jo1cCjFqSVq1DDKlkfaaPcFz72vh4/Dkc7epRluaq7UqnzyaGZbvVas6btorRavRvI\n8pxiSO+3tqw+aSUpTIVAKLCUWYKJYyhTyiKBPEOZkjgagLGMjY3jeR6lMeR5Tp7nlHlBURTEUYyV\n4NcDbJIi0wybpNS9GnE/5oWveC3vfMsbabeaWCH47697NTd/6dNc/rSL+IP/9T723HID/e4s7/6N\nS3lm62Qe3d3IK574cB53xomsrHRYHHSJAs1bPv41Pvi5m3C0y+Me9ziedtGFzC6HfPA7t6EcTZmm\ntOtjNOvjtF249Y6Cj355ma/ty5krG1hRwwzW3B1FBsdRPPeZp7P5hBrCyxmbnKC0hu5ggHIcSmsR\n0sVaiKOYIs9Jk5gTt24lTzLyrKiEqpRDkqa4rks46JPlOVJWLTQlBY4jKYsC7bkILcmKvJKezTJ8\nx8P2LL3PD8juzel/csCmiTHGGh5FVuAql0EYVyim4VrRQqKExtF6uNosUlq0UvhedbFtN1tMT00y\nMzlB3VMUab+CnhpLXpQMopw4KSjKalIeDaLKNQiGamdHr/Nj1+x9bf9x6/w+z50fs+14PPTiQV2J\nV+Qdqmw+ijUIv0rZz1YoESkw5ki/XAqBrdRWjoZVmbWD0RGi5Eg1f2yVsnYAKlXFBFJarRmk2tWq\nP8sKtF7T0hmSlIzNwChKcgJVZ36lx9SWzeRxgkgNThvyMiHrD/AcjSwtVlbHk47GiJHXIzhKUpYW\noR2sBKEspCnLYa8y8fXqvOBVr+P5z34GT338Y4jihCzLhlDMksvOP53LP/4ZXvDoHXSjiH4UsXVM\nsrndoj3WYN/SgE5cMiEN3735AGPaIU5yVK3O1MaNRFHE4e6Adt2jSFMCr80diwXfuvp6Zs0YhfQR\nokZDWALX0p7YzC0Hl+l9MkTOKNJvJjz7grNJuiHJQGGMR71pyU31N6dFjnIsSZoTDULyNKUsSqYn\nJhmEfYoShNB4jkN3MKC0Bmkr67V+2KfIcmxZYeu1AENRiaE5AWpozVaYCvF05qbTufOH9xBdH7F5\nYpLXPveJdFc6GOGAW8NxXBIBURyTppUImas0aVkgBCglMLagLPPKfcgKlK2QSJ40nDAzRjjIWQmL\nyujaKjrdhGag6UcpeZZhjCSMEhQKOHqu89O0Ve5v37UFy7HtxuNJ/BcjHtRJvKLTH21tZYZyrEcG\nmAyZmQI7dCQXgDUWEMMq/UirZG1lfyRR66N+BlZ752t7inb4fmVZIQmkGDm2jN4HbHXVWfMeAmMr\nRx6jSnJT0O33UULiBn6FZS5yhIR2q11JtmqJdlyU42KspShyhHXwXE0Sx2gpMVrjSDBFSm4NjYkx\n0jTm1//bWzhlx3Ze+Oyn87F//BwLnQ5b1k3ytAvOpTt3iL/424+xYazG1679HrXx9YRhQpRYtmzf\nQmZzHvGIJ2Kk5Pobvscdyz/kkmc8iVvvOshjL34Cv/nqN5LXp3jpc5/OO973cTZu3swH/vqTfOtQ\nF0c3qdfXUaazpOki1ncoHcljTtvFxWddwDdvu5elHw045bQTOXP7DHFSMIhjpLYE/jTxIMb1XHy/\nxiCOSJMYU2RMTrXprvSp+QFhFJHlhiwvyfOSdmuMxeVlhC0p0pRWo06S5tRqPsZAHKcoaYkHA4S1\nNFotPM8jTXM63QHKWHat30WZdNi+YYwszen3etQb48wvHGZqooVUkjzPKhy366CQOFJTFBlBLWDz\npg3MbNlEbxCybnIKU1iKwqCEZbLlcuKmMfbcvUwnKpEIklyy0suIkpxBnNNLMjppClSD72K4bo6C\nxa6JY5Ux7+/7tet5LTzxvgabx5sqD+14UCfxqgj/l+yy6vvRAjeVuS7VJmEZao9Um6qFunYRr61G\nRou84Ce5/TwWq1uWBj0kH626AJkjIlxKVagRJRQKDbLCjgtpKdKUtIT6+CR5VuKgKKSD49eqHrwA\nR0rM0HhCOw5FUdBs1InCEGEMnqPpdvro+hhKab75/Rv56D98gd0nn8Rff/QTJHlKsN0jvitlqtWi\nVXOpacnZm5tMbtlJlMU0JgKcfJI9ty8wv7DMdd+7g3XT09yw7xCvv/wSRNDkh7fcRby8wpYTdvGD\nO/fxiS98Eyslz3r+C/jUl65Dz96CVoJHnzLN7EqfyfoOnvPoU4niDqVxWOqEPPrkraR5wVm7TmJp\nZZ5SlDRaNYQ2FFlBv9cj8GrMHZ7FC3wmWjWsdYmyFM93We518byAuMhAlXha4blO5bRUlDT8ACMs\n1nfIkwJXObjNBklekGcFxkC/0yVSDlmRk+WCZs0nzwyuCihyWFjsMNmu47nzOEIR9WAQhmRZhrGW\nHIsrXYoix3VcxibaNOo+cZ4x5tdI0xSUZssJ27j3wN3USktewEInI8lCsswwSAtsGdLpDVhcWSE2\nJYOywJa2aqeoo4Xd1q7HH4cXv6+1etS5dB/n0epzD3i04/Fgjgd1Eh/F2oV3hGJ8pH941MJcm9+H\nP2Lt6kId4c1HZJyyLHFsMDzmEYXEwmRDIa1y1KoEcaQ1YyoZFwpTCXIpp7qCmNHJohTl8KtCYAsB\nVmOEw4HDyzzaZFQAlBxhVWW+HC9SolCqjufWyPKy8tKsICx4UlKEy6S9Hr7j0u/HePUG1lPEg5LH\nnXUmi9d+iquvvYVff+cfsO4lEwgp8A969D8w4N2vupRv3rgH6U+wsgJRlHN4+RBpofj6nttxBTz/\nvFO49tA8e2eXeNdnv4a1hrFmg/VbtnKg3+HZF+xiIQu4+Z5DfOhvP8jAWs5e32SxFDztnEk+9e17\nqAWCUmmSUqOUwEqNKQxxPGB+oUOrPYHrZlVi7Q04dPAgZQmeX6PerFGUKVGUo7RDlhi6/ZB6vUGU\nFWRJRt1xiZOUNO7SbDrDC6glLwzaKOI8odYMCPsRvhvgKMhRQ40cgSRAUyC1i7QFmJLMKOJEsLjS\nR1po1TzCbo7rtlBaIjNLbyXEKoPIBYHSND2fMEyJ+yXb1o+D5+K5LlZETLfGWOqsMB5otm9oM7fU\nJc8teV4wyGOy1JLHBcupJUos0ikw4v7p8WvZvw8EL/xxcX/J/Xg8dOMhkcTvK36axXfswBKO3JZK\nKREjVMDoZGGEbBFH0fylHOmKW0aCc1IcISEdy5Zblai1FmkhLwoSMm6/cy+Ci1haXKE2PoNyHKIo\nIpBBdQGxIIRBSoM70j8vS+I4J4sHSKHJ0kpe1gqDdgV+LSAbZNhccuDwIdQ6eYRZOaOJ44Lv37AX\nY3yyKGVx6TDdbkh7bJo9B/bjCWg26+w+/wxWbj7EvfMrdLs9Vrp9bs8yXvk772Df4QUOz1cWa0me\n81/+4L088tSNbD95I7M33Mt1191CGMZ897b9fOOme1jXqvPEM7bTqDeJ4y7bT9yOqzVhPEAIQa8X\nkqU5YxNj1GoNVpa6FHmB6znkZcFiZxmQ5JkhdQqKFHzPoygNrWadNM/IygLpukNseELNDUiyCFMU\n1AIXkxf4ngOpwEookcRxVrW4TInNU2SRkdcLFlZCPL9KtEyN4XqWKOngupokS4mjhMJa0IpCSg6v\nrFAUEZqUHdvWMea1CII63eUlXKUYb7WRpiTwck49aRPX7zlISU6c5nTjlAPzXWaXexTSYARIjiCq\n7msNr03q9ze7OR7/8eIhm8R/ljiWALGqv8LQbKLaC4RAmCO3rhUKpoI5KjWySRtBHO2/OKlGJ9bI\nTMKWhtpQKhUUs4vL9PshJ2w5gbwoEVbgug4Y8B0HawpEHBLnGZmwGAN5VjIxOcWh5T4ved3vsrTS\nQSrJlc+5jFe95EW88ao/5p++/FVcral5mmhvjDxH4mzQDK6OmBqrk6HpdEKs9umnlmBsHXv23sv+\n5QUuPGcXc2HCOWefx1mnJTxl91buuf1OPvatm7h32fKU3du45+BhWr7H0x/5MN77ze8jjOH7ew5x\n095FhIUkzdm1foZHnLiVvEj59h37+cINd/H4XSfQbNVp1Hw6K0uUZYkxMD09RZ6XLHZX6IcxUZjh\nDFEhBSXGaqwFYzVFLhHWkCQJUirCKAIBtUZl0xb2I5TjsLyyhOc6lGmCEALfr2EEdDsrSDfASot2\nJGlaDbOjOGWs7iG1S24UK/0ca2KEENR8QbNZp9ft0Y8ystKQm4JOr4dyFOGgZJDUOWGmRSnA9T0K\nA+MTU5hBRN4vcbRiquWS5hnNhsPCSkiUC1ZCg5gLOdgJQYtVk5KfJBUfm7DvD201Wo/39Zrj8YsT\n/6GSONy3END9xVqG6CiZi1XN5wotwuj50VZ5pM2zCj8cmUgoSWkE++bmKcuCLEsQQuG6DnEckZuc\nsJtS8wLKNMMbm0A3mtihQ1G/20UrzVWv/8+cffI2eknG4694OU963KO5+HHn8+bXvAyTDHjTH/4J\nky2fr/3trSyFKVMTDV70zIfT29fj8EKHQVZdUKSMONBb4YLTtnPKSduYve4mfvCVbzF3eD/X3HYv\n190zi7GQG8N//+SXwVaaX0tpQVkWlMYy1mrQ64cgJdfPL/D4tk9Z5NRqAbs3TfHZ6++gWXNpBJr5\nuQND4+QM36sRdnvkeUrUHZAlplJ0VIY8LzAUBF6dJMnQUlNmBa7rgcmRUqAEKO0QhRFpUaK0Q5rk\neK6PxCKHksCOVNRriiAIiNICtxaQ5hnO8O6nVquRFRmlsRgkSWaJNCSzy3iOZcMMWJHTjwuyIqdR\n8+mHXUpbkFrJQi/i1gOLnN6NWb/R4LnVQFLXfHxjcbVAyi5hFDNRF8zWXFYiyUJYEOYR++YXycsU\npXS1pnjgdXl/6/lnWePHk/tDPx7UOPF/61iLCKiEB0ssJUKOyEWjZF6JGlXQRn3U474GpGpo6Gxt\n5QMaRglaS7SAPI6IOkvUtSIQmmazjQ1q+Bs2IVvjGO1ilYNQGqUUk2NNzjtzN0WWMtlqsHP7CczP\nL/Doc0/D2ALX0ZyyeZLFpT6P2bKFv3zjr/Lqi84murnL0lyP1ECYJfRWFknziPVjLR67eyfdQ4fo\nLC4T9Q+y46QNvPb5z+RXH3cehbVkQYneomk8rcZyHPGdg8u0mm0ue8wFvOXXnsmTz9uN67mEquDa\nA4dZPzPFthM2sm+5w/ZN05x88jaagQN5RhLFSKDICgZhjyQe4FgXckEW58RxQpwmONrBlBWio8xy\nbF4yCMPVOYZg6MrkVrA/IRRhGGGtwBpb2bAhyNOMOOqjpUQrRVGUBEGA1roaRA9FqqyQSCUYDAZD\nL84aYZhx190H6A9iSlPp00+Pj6EBR4/kGwS375vnhj176Q1irIBw0CPJU7xanSCoUasFTLSabJlq\n0ax7WKVZ7iWEKSyHA5QWSCuRVh91J/ezxrFolPtL1D/uuePx0In/cJX4/cWx1YtBgBjatUFFGi2J\n4wAAIABJREFUs6+A5Uew6FZU8rFrboKN8aqEb8oKpy4shSlQ2iKFhyEhp0WSptj5OZRWeBMzJLmD\n43sgvcoo2YJNQlwvwABZXuIHDYosBmnJipR9d83zo1vv4IyzdlMuzWNKS0e4vPvv/pkTxhs888Iz\nOHDbLcwvFcxGKUlm6XQTBmnMzm0bme122D/f4Q8//iUskJWGf7ptiRdv3cEnPvctrr11nrjIIYb2\nC+qY1KJakvnZReI85Bs/3MsXvvd94izD1i3hE10OfnyOmz/yOcYbPls3bOAVl50PRUaz1sIVGmPB\n9V0GgwEGQZFbEh1XolVDRqxwJJ6riaOEsrS42qPVbhPGXYTUSO2QlRlFaciyovJXLcBxfRCKoixo\nOBpjCmq+D4kiok+z5tGJUkpRrs4vSgMCwY17b6aX9HCV4kVPugi/5vPtWxe5/s578XSlufOwbdvx\nCKh5DRJbYmWOUBqE5ctfv4Hxep3Hn3ca27dsIlcKJSTxYsL2HTsQB/dTCMFN9yxjbMF8f4AJKgs4\nrMWIooKnisrCyTKSf5BYk3OEzHas+8+RhK+EBDtU0hQSKwSlsAgUlWaQRA0Z0LZa7EMS27+do9Dx\n+PnH8ST+AHFfuNvVbVJUxKM126WtJG2tlCgkxpZUdP9yeB5KoigmTVJ++68+zJe+eyPrpib4xsc/\nwsHFRf7TK1/HnjvvwhjL5o0zrJ+eYmFpmUOzc/iez1mn7uSXn/pE/vg9H+DO/Yd422tehg0XuP2W\n6/C1ywt/909QOuC/vfw53PiDH3HvgRWWBoJuXJLEKWWRM91usGG8wZYWPO1hWznj9JO4Y/8C/+uz\n3+FQp8sL3/4+lHSo++sreqmFlU+EmH6JGVhaMw2ypRilBKdv284NK3eSpyXeDpfp/zrB/P+7xO+/\n6FK2b9tAnmcsLy2hlCaouyRJiqMVZZEQDSJsaRBFTsN3yBWUrqLZbNAbDGg3XJR2sFYiyKj5LoUR\nxFmC0ALf80jTCCEFeZGjnUorJfA0FkGt1hgagGQE9RpJXsn7pqWpkp2tlCq1UkzUJjhn1w6++cMb\nsJS4jsR3FU982C4u3L2TOM24Y+9+5vuCQDlIo6oEacGRGk8K7t67l5M2tQgcxfjEBMJxqdVqJHlO\na2KSJM7YuWk9N9y+H6NdFnsrSFFiTIHSGqzEoIZFgWCkKDFKspX8xCjhqmElXSXo4Q7VM0OrQcsQ\nciskgorTIKTLSMai2sf+hJ344/FgjYd8Ej92oPOT9AF/mvixvcZjKvOqYq/0DqVQVeIekn3UkMJf\nlil3z0dc+rp38O43vY5fv+KXeMnv/g8ufsGLidOEvffu451/8Hv88mWXcMp5F3Lmqadw3jln02jU\n+buPf5pdO3bw7RtvZmpinCzPuGDbOLWVg0xMbeaK//K7dDLBb11yAV/66rUszYX0QkU6SLFZRmYE\ntcBjw2QNp+xzzpmnse3EE/B9xave/Ul6JHRqCQWWoshwzPIqJLNcLrFZRZW1RUp7rM3mdevZsq7J\nD/t7ISsxkQFdJaBNk1Nok5L0+3imZBANyJFkwPh4m4l2g5ofsLzcIY0z0iRnECdEScz4eI1Ww2Vh\ncZma71Xs1bRScdTaoenWKK0hLQxWiIrAk1v63RDH0yAkSZbh+z5COSjtUsSDSp89zhGissLTWpMm\nMY6rafpNmq0mQkqK0lD3HFxHVaJWgWK82WbD5ARf/s5dLHoe0dAmT8oSX7t4jmZm3TRIQZKlZElC\n0w8oshypNROTk8zvP8C4r6gJTeo1WOjOIaSLUkPpCCtxhEvVtoPVfD0ko62tmoUwWCupFJerO4XK\nZNlibIWztYxaK2ukJoRcrd2rtX08gT/U4wF74vv37+cJT3gCu3fv5vTTT+dd73oXAMvLy1x88cWc\nfPLJPPnJT6bT6ay+5u1vfzs7d+5k165dfOELX/jX++05Wufk553A4b71KEaO9laICtsrq69rGP2r\nt7TISk9FSolSGtfxma7XkVJx7pm7mVq3jvmlZd7y2t/gui9+EikVH/74p2g36px56slc98Mf8Y9f\n+govuOzpnHLSdh517pl88vNXc9aunbTrdX73fR/ll9/2bl782+9gfz/nLVdeipv3kcYnL0G5FSnG\nsRJswVhDM9F0OGP3TqbXjbFxwwa+/aN9ZO2CqZeNYULD+K+0QMCznvwEzj//sXzkw/+Hyy99DlgI\nagHUKhZjlve46GE7qUUaE1rSOzO6H+jzqFO3M9Z2mJ1bYmF+gbnZObK85NTdZ/Okpz2T0848h02b\nthF4AZs2bWJ6fIyZdVOMN2usn5zAUZpW4DEzNY6kRAH1hk/gaxytUEqgVHUXNPqfSK2oNeo4jgNI\n/FqDOM0JBzHK9dCei+t5TExM4GiPNM0q9UjXrzTbjSBPKp/WorQkeYajNV+8/lbe9pEv8jdf/g5J\n3GfL+iZtT9J0XMZ8n3HXpy4tU806Y2NjaM+n1hhDN1rooEGt3kQrB2GhVWvRbgU4jkcQTGBsgFKt\n4aOJ0k2ErCFkHanqKFVH6RpC1UHUsdQw1sfYgLz0KK0DwgPpgBy2THAQaAQKiUZKByk1UDlkCWtW\nH5VX1HG+5kM9HrASdxyHd77znZx99tmEYci5557LxRdfzPvf/34uvvhiXv/61/OOd7yDq666iquu\nuopbbrmFj3zkI9xyyy0cPHiQJz3pSdx+++33SSH+ecRPk7R/0iT/QPsdS3Vei2I5ekc59NcEYUf4\n8Uojw2KrvjgCrRQrK0tgSzaumyLPc269/TZ+8KNbKgEnPeDg4Tm+9PVv88NbbqUfDvj7L3yFpZUu\nKBCewEYVeemVf/pB1o832TrR4klnncievQcpHUWCIHCh4UtOP/Vk/udnvsqmdeO84XkO7//UF4mW\nM6I/XcbZqKGs/o4zzn8Mh//pH/nQh/4Pc/ccxnUckixhcKYinyu4+fq7ueqDK7TdgB3bJin2KDKb\n8frnPBfpFsxsOZHGTslgUMEaJzefQC9KCaTCrzXQUrG8vITneWT9kHq9Tmkh7EdoJJ7jkmSG0lK1\nY2oQDVEiflCj01up9GuGgmNSVi0Gz/NwHIdBFFeaLIWh0WoShhFFIVBS47oe1lqU4yKxFXwwLaub\nK+Ww0ulx8SN388KLzkMa+Og3fsBHvnEDz3jkWTQCTZqW+EEdRYFWCqVgYX6OiXGfQ4cX2LV+I9L1\n8ZUgHQzIkxRhFGEU4jUbJNrHWg871EwZMcrkUFVcCEtpzeoAFxi2UoY8B6HXoKKGbLRjyEKsWcPV\nerVg157yq5iqBzoljseDOB4ws87MzHD22WcD0Gg0OPXUUzl48CCf+cxnuPLKKwG48sor+dSnPgXA\npz/9aa644gocx2Hbtm3s2LGD7373uz+XX/bH4WB/nvHTVvOrg04psVIceWgwypJlEWHSJ0lDhCmJ\n05zDCys85SWv4fLffANRnPCSN7yNnY96Kr3BAGMN5z31OTzlcRfgupU59G++6a28+VUv5rsf/jPG\nWg3iNEO2JVMvH2PD70wx9stNJsZq/MZlF/HJq17LKy95FIcOzlIODDYpkbqSZT1h8wzXH5hj+6Z1\nZFnBgVv34mUDlBXoKY1sKMLPRqybnuKyJ55D0ymwMmex26GkZOoVY9TPDxi7rEltt8cl5+7mz17x\ny7z6mY/nVx+5g99/9ZVc853r6K70KQYdunMLBEKhi5Ry7hD1PMOxpmKiOgrf0fi+D2WJKwUaGB9r\nIGVlZF0LXKSq9LixGj/wUar6rOv1Gr6rKYuCWhBQFBlKVkC9cJCgnBp5YYgGfdIoIy8MhbGUGIR0\n0NohHgwoTTm8k5JIUbkpRUkJeYnrezQadS4593Tunl9mygk48aStFMKgcNGBjxNUbZh+d8CtN97C\noXvvYn7/XYhBTtLt012YRyY5YaeLsh5RFtGJY0rcCgYlVFVJS4mRBiMNpaiwUUYIpHCQorrDGGnz\njKwCkWL4WoXBwQiNlQ5GVOxUY8Ww3pYYKzFCUiKGD0l5HKD2kI+f6j94zz33cP3113Peeefx/7P3\n5uGW3WWd7+c3rGlPZ6p5SFUqZA4ZGAKERCIzSMcgGryI2j7QCna3A9oyOFywbfVetdXWiyPPFVta\nxUZEFBAlREggCQmEkJCxUknVqTpDnWkPa/4N94+1z6lTRQEB+vaT4qn3eXbtfdbe67fXqfNb7+/9\nfd/v+30XFhbYvn07ANu3b2dhYQGAY8eOsWfPno1z9uzZw9GjR7/pC/xqmPQ3Y/9/0am+3nVpFRJH\nHcAjlKb2MD3R5SO//bP82a/8DAi44SXXc+/NH+T//qW38tDBQ/ziz/wkv/ATb2L/nt3UxnDjC6/l\n377yWpaW19g6PUWnlZysXKRgkJZ8/02vYeeB/eSjQbN9VhopBUkSsn1Lm7jT4r5Dc7zymqvwxnH/\nA49w1bm7eObeXfg5S/1lg0thOBzx87/62/znX3w7W1yL2blFhBLIeNP/YQJlWaK7LfLFBfbu2cvk\nZMTRo31mj42gGOLKnOHyCnVeko0GSFeAGWHLEQrLzJYpnDMEccTE1AxeQF4WRHFMGEUbWjdVXgAO\nU1dYYxiNRgjfNNNQQoDzBCqiKG3TEs0JsiwnSdp0upPUxgIBde3J0hzwlFWJ1nqj+5Kpm4g2Lwtm\nlwa85+O38b5b7mJoHbc98jjn793FlpkptvQ6bJ2YoCgqytxTZpYsNayuZqz0c5ZWMtaOLpD1j5Ol\niyjpcUZgbMn8aoYjJs2GeL/uSgXCSYRTCC+/4uFRjQPe9LrZ5Sm8E40ypz/drbyuQbH5cda+3exJ\nJzZHoxGvec1r+N3f/V263e5J7309vum34jy/FbjkG61W+2pVb1/vnM3Vn6d9f9zoGRrc3EnNIM2I\nkha69hhjecuPv5kgCPi7j/wzaZrx4z9wE6//Dz9Nfzhk69QkWX+FRx9+iHf88fuZaLdYXl3Djzzl\nIxV2zZH/Y8mu7du59IKLefzzn6K/soapDc4JghAmpjpcfMFe3v+pL/AjN76I1cVlBv0+6USP/+PG\nG5m//36C73gWf/bAYfaft49/uvVOHnr8cd7+O+/mldddx72HHufAOTv42AfvJHxxgFm21PcaXvKu\nF5AEnnywzMXPejXzS3Nc/oxLmR30OXd7jyhpUxrLvgvOxzuoB/2G+laVlFXN8bU+c8cXQAQEYYLU\nAa4sqOtGBsE5O4YrmoIp7yxJHGNs49C08qT5EK1bZFmKlQIVBggvsONu84PBkDAM8UoQRjG6do1m\njtLYuiaKWzxw+GEenE+pbc1fffJmrLTIGck9t87yNzffzrMuOsBv/8yPMTxylKlui317dnP7ygPI\nzBAHDutqvCsxpWVhfomVHdMcX12m043ZsWsvC8f6LPRT7ju8hIgTRisDGDeoYL0LN+Nk+XjeSAS4\nca7lVAGr02iPM646bhLsYmPMjRm9kXw/C598O9mTcuJ1XfOa17yGH/zBH+TGG28Emuh7fn6eHTt2\nMDc3x7Zt2wDYvXs3R44c2Th3dnaW3bt3f8WY73znOzdeX3/99Vx//fVf9zpOgi1O42xPV468+bzN\nx5+sENDpFoWvNsZXG8fLhnaIEHip8NIBjh/7lT/iU/c8CMB3//AbueSC8/j07XcDMH3Z1RsRogwl\nv/tX/8jv/NU/IlqAEfjaEyhFcUuFoOTKSy7ku172IobLC6wcfYLRKAUhSJKI7kTEgQv38uChOaZ6\nXS7Yt4e/+/y9aKX43h/4frarhNky4/a0cSJ3fOk+5voLZC9NmX1sln/+xZt50/e8hDe+8iXY96R8\n8eajJEHIz/zcDVx13h7+5QMf5IWvfS1OxCROcPGBCT722Yep9/XQ2tPtTmKcRAcBMmoh8AQWVCgx\nUUQ+GBC1ewz7I1SgkQ7SskKoAGuqBsPWAVmeEkQJlRNY68jznKTTRYeKQVqgwoTBcEgQNT1KkQFF\nZYjjGOPsWB+niUaVkti6RmuFUJJzt55Prx2wY1ubf/j8p+i9rk14ToNPjz6QcenuPUzNTDFYXMA6\nR3+4RmobhcnKWrAWaQoSKegECh1FHHpijl6vh3MtFuaWuP+xFR6YX2Zm/7mwuooQUVNLMKalNu73\nBI97vXrTyxPdqNZRcHlKVN3g46fMR7E+5jdnt9xyC7fccss3ff5Z+99jX9eJe+95wxvewCWXXMJP\n/dRPbRy/4YYbeO9738tb3/pW3vve92449xtuuIHXve51vOUtb+Ho0aM88sgjXH311V8x7mYn/rVs\ns7P8RuGUr+X0v5HS5FOv5WvJep7+Qk68LIshztaYCv718/eT1zXtboIxhtvu+gJ6m6L17Jj0kzkT\nL+7Qfk6C957jv7VK6/qY4UcyRCQQCi47cD43/82f8+v/5y/zmx/4CP00447P3skPP2MXqBCtDF4K\nJnottkz1mLvnMe49OMtrf+43wENRG/7kw7fycy96NrPJFF94YJb/+pYf50Vv+gm2vm0KoQQcAPG4\n5/lXXMri6nH+/Df/M0dmj7D8yANkE/DALf/Kd3//6yl7UwyOHmMwd5xu6FmeO4otnwahZcuWrTgv\niYOYekpja4sOIlYX5zACztm/j7ywpEWBsgF1bYiTFsM0wzpHK4mwzhOEAToIsMYThgpQ5HmOkAod\nSnztUKo533mP0hqpFM7WKOEJw4CstoSRRuCx0hPqpmdqHMfjmFVgjEV2N+nOt8FLzTBNsQLW0pS5\npRWM8FhvMc6hTcazL34a1z7zClw9YlQUHF/OqOo5lEh4+MFHufWehyi9YpSPEHI8Lx0nImQ2UVVZ\nP/5V1ApPcc7jO2TTgfH7p57un3wUfmpw9a53vetJn3vW/vfZ13Xit912G3/xF3/B5ZdfzlVXXQU0\nFMK3ve1t3HTTTbznPe9h//79vP/97wfgkksu4aabbuKSSy5Ba8273/3ubwlO+VrOd/PPm+2khsdf\nZczTOeLNTvrJJlFPFdTafP762JIN/gBx0kM4z795wRV86LO3Upma1qtjBn87YvIHu8RPCwFIP5Oj\ndyiO/8Eq3nhM35LekpNcGdG6Kmblf/S558sPcdXLbsQaRycK+Mw//CW/9Qv/hT/6yB1cvm0rroZ2\nr6HVucrzpu95Od/50CN8+Z7Ps++yq/i7z36RIAr5sT/476zkcOsH/gfL938GZx3eNvk27z3OeAof\ncPkLXsaxhYM8evfNTE1M0co6XHbT66mMxS6vkC/NkeV9dKvLtnaMbLVpbZnCtdsEBJTGoUNJrQQq\nVngExoCRIZUvUKFmNEyxFrJiRBAliNoxyjI8ECYJzgmqqsY6izWOMAwpncdZg1ISSUBZWyKtyfKc\nKAzGBViWKA4ojCUMVaM5rxUSgaPZbUKjc3Ngxy6e+MA8nVe1MCuW+vMVL/vlaxkO+ywvLnJ0YYWF\n1RStNFVdMNWBH3ndq9gWNqyVhSJldqlmJY0YZRXDO+7nwYePMpfmTG7Zjg5iVJBQGzOOqNfnqjvN\n3DrtFMZhWMe4pdANesIJny3WY/tNU9Z73+jan+Y+OGtnrn1dJ37ttdd+1U7z//Iv/3La4+94xzt4\nxzve8a1d2Sn2tfDqr+V419//auec7nOnFg+deg1faydwOpXEpkJuvPgYQ+Vz/vH2OxAXSYJ5TXJh\nxHAipf+hIYNQNIwz68lvLZBdgV324MCuOrK7CrK7C9ZbwDw+eww8PH3bDL/4pn+PWFvm84eXOLc1\nQZBETHYnaAealpI8dv/9zD82y/apGeKtO7jvsQ9z6MAio9UMn3mu+77X0Y4CtnbbjN6XIa9ScMiz\ns72F67/rBbQVHLr/IS7ct4/WvkuRvV0YJchnHyEslijTPibNkCoh6bRxrRb7LrwUFbVwDoRWFIMV\n4m6Lqi6Jej3SwYi6stRVRZbX6DCkMCXr+tlRElNWFSCoKoNQIaEKqLxDhpq8bipia+PxTtLpdMiq\njKKqxzg6lNYQ6oCqsiAkSRjgbE1Zljjrmh6ZMkCJht543eXPwt5zJ8fee5wkCviJ17yM3dt61HnG\n8mLGI4eOUUgwvkRTcuMLnsVzr7qQrD+grgKOLvaprKafGyqb8NixjMNLGd1Wmx07drCUliRxTDFM\nG7x7XFV5ati8DoYI1Fd0rVeiSVo659gUx58o5OF0u0WP27xQiK+M6M/amWdP+YrNzTzs9Z+B00a+\np8rCfr1x18dZt/UI/uuds35Np/v8qc7be0+eD3HO4L0jz9eILwspiwp3yNF+TtOQIjoQkt2R031h\nG5c70k/lRLOwOqzBN701azvusgwgQLYEKHADjw0Dji+X9AlJawOiKfioqoq6rsmLlMWFJfbv2U0r\nkPz5zZ+k/eKEznUJneta5F8q2XbfJO/56R+l3e3xxx/+OF98/DB7dk/w1tf/AP7wQf71c3ewY895\n7Hj+C1nLBROx477P3kIkBLOrA0yekXR6+DChP1hj67YZ1pYXCcIA4yHS8Zj3HtGOYyqtsc4jfdM3\n1FhLHMZEQlOlA5xzVMbS6XTJygJlJcatL9YNzc44j3MahMYJT1Hl6CDAWYOUCmMdOgwxzhGqkBBP\nbQ11XdPrdBn2+wQ6QAqBMQW1cQg0V+2/hKefU9ONLHu3b2FxaZ5EJ8z2K+YGGU4H1OWAjrJ853c8\nD+kCgrBLWXuc6JJWq5S+wgnNqKwxeCanZkAIjLP0eh36WTYOkDY3evjKnacfO/nNsYPbELRXuHV3\nvwmK8d4jpNhw2Z5G+96K0wQ0Z4PxM9qe8k78dHj2Zmf6zTBKNo97aqT9ZMY7Xan/qbZ5kUiSHhZP\nXaVEz5VMvKyNOW44/sdrmCXL8BMp1edqnnfx01l5aA2c5Wjs+W+/8i7++x/+KZ96+HEKUzfjAWGs\nKItGxwQBoi14aG6RQZqze9skWsmmrDyK8Ej66Ygg6hK1mi5AMvIkrQgRbvqdQqico7d1ms7END//\nH98EUlDXBfkgpRUlfMf3vYFMC0Z1Tewl/aUFJgLB4uE5wk4bGSbsOvcc7n/sMOlwyI6tWxDWQF0j\nI026ukxd5ehRSlVUlINVvJdNyzqhKKsaN0rRUUgcx0gVoK0nzdKmQ1IQk41SKuMQUlPbGqQkywuk\njnG2bFgncUSRpXS7PYTwhElAnjYiW1JKrDHEYYS1zc9aNYud0hopLKb2KB0xGhZQG7RusbSyRESH\nQwsrVLUn8hV7pxJ+6HtfQWvLNLFP6K8d5sjcHAv9FYZpTVHmtFpTeCsIpCdMYmpniNothqOi6alp\n6jGppInEvd8cGDSL1emS6/X6/JKbghHhN0XijMvwT5znhMB5+5U7yrPB+BltZxRxdHPpO/AVVaBf\nCwP/WseerPaKpGmAK8dlEkI0LBNweG8Bh6ApyhBirCHuLdJLIuVw2I2OQHqrZvKGDvXdFXsen+HV\n113N9770ORxfWuGxo4ucu2sXH/mbj7J13yXEvZ1IGTXXIASmsogQ9HZFckUEpaebxHzqt/8TF3cD\nJtottmydRkcTPLjS52d+9TcI4i2sZI677/4ij83N8yOvegHVJ0vy+0qKh0qqj9a8+upnkBcFg3xI\naQpkGJLs2EU0s5v4wHmIsItbHOL7S+TZEuXKEtkoJ56ZQsctJmem8DLg8YMHueqKS5CqcZjeV5jS\nMnXeZXS3n4tOWuRVjvMCW5SsDUfkeU6300ErOabACZwDFcRNezcvMJQkvQQdSmQgcEicEHjtqEyG\nNYYgCHDWEUUJznnqyiK9wprx30dK6qppSqE8SOcwZYVA0mq3QQWsDodoHTIcFmQ1HHxigdFazbA/\nYml5wGRY8rSJEW/7sddyzTVX09m2h9KWzM0t8OjBWfpljhUZu7d2aYeOuBVhZNJonYQxxnu0EshA\ngwzw68GDcGNIRICQOCkxgFWeWjmM8hjtqQKPDS02tBjtMNpRSYuRBjt+OGnwwuKE23hYbFNEJMEK\nj9cSr+XZgs0z3J7ykfg3Yt9souZJs1NQeOc58d/mN24AsfFcs55RWmcaVMIjXcDOPRcwd9uDqAmJ\n6kjKmyuuvvA8nvOMq/mLv/8HPnHnfRjr2DM9waHZWdxoQCU1g5V5HBBqRW0sSkiE8ZgFi1m04KHX\nbpENU54o4bkX7KXvDHmxxhXnHeAtP/nT+Cji8/c+wL+57pk88fD9XLayys++4rl86N4ncEhee+PV\nvO7Fz6XV7VLUBlHVLM0epTUzherNUKUpdeWoo5BOqFh9/BA2K8n6I7bt2AoCjLH0V1e578GH+Lm3\n/wKyOwNBjq8yNJ4qW6XTjjl09DD1MKVKR6z0V6m9oN3pEIQhXgdkVc1qOiQIEpyr6Ha7jc53bcnS\nIUIGCKEauRAHYZAwzAuE1o3glBQEgcaYRg++qmr0uEmEKfLxn8xhHWitkUJiTCPuZWpH5S2VMiip\n8V4wykpmq4xe0uL5T9/Frm1P56KnnUOn28WrhLUjxzj2xCEePfw4hXF4Z+m0I7ZM91heyYjiEKU1\nXjfiWlVREkhNt5WQl0OM9agxTRzlT9BRfTO/3Ji14rzbgD7EJmzb+w0E/MnP8bMJzW8be8o78VOF\nrTazU07Fw08975vNvH/1BKll8+ZFbko94dehGNv03Wzq8JqqySQhCaYYZIIwvAhuPcbMlOaZVx7A\n+w73fukhnn/ReUz0JlicP8ZtDx1i+2SbR1fWkFJw4d5dPHTkGJUZVxaOE81KS6KZgGyh5PDCEq98\n1x9wzYXn8B1P28EDSxU/8tY387l/uZknPnOYw+kqrYlpDh4+Rhz3+IcP38yOmTb//trLec61zyOJ\nI9JBQW1XyeqKqqzZvXsvK1mKlZ5tKmK2PyCamqBcXmFttEh3Ygu7Lr+U/so8M5NdMNP804c+xMUX\nXcSOnTtxQiC0pq4TitGAthSMVpfpz8+zOjeHkBKnBZMT05i6Jmm1yaoaJWSjTFjUeNW0YLN21KgQ\nZiV4T9SKyNfWGGQ1WS0paosIA4JQ4QAvHGGkSYcl1tYYUxMEGrwj0gqtJIFqot4sL8GCfKCdAAAg\nAElEQVQrvPUooRBoBoMMvECqgP6oZuhymFZcsDPknHN3cM755zNYWWPl6FHW5o4ze3ye0nmmt28l\nTKumb6Yr0YFDCsf01DRCx4yyjEDrphTeW3Qgqb0DDcKPW/8BjsZhC9GIVnnvTxTzCJCnm6Knq9o8\n5RaQ3yg99qw95e0pD6dshk/WGQubneyGONApCc2v9vpbMTvekjphcePO9q4BWZoiHhGAaONFghBt\nnEhAt2h3Z8gziTHg9STTk5fyqmuuZe+2HawsZ9jasTS/hC8HfNdLv4Pt27ayVlqElJS15dFjC03c\npUFEgvjyBlqhA3VomfnRCQDe+MJn8WMvfDaTSUKSj3jPn76b6171EuYXj5MeWWImCNmzbQbnK3oz\nE0xu20GgNflohBER7ZmtyDBg685dTG/dQmUN7W6L+tgs93z6E4j+car5I5QrC7QNhLVh9qGDtGSH\negSf/sKD3Hr7nXz/a15Nf+EIS7OPMVycJfSGThhTjHIevucLHD70GGleQhgzOb2FyZlp2hM9lFL0\nOl0kjcZ3HCeUZc2gP0LJAGNsowioNMNRhsVT1hZjDN46XFUQSgnWILynLgu67YZnr7UiDgOSOG5E\npawF67G2Jgo1Snlc3Yzjx3MqihOKynFsbo3B0HL0yAL9vCRI2uR5TjFaI12aJUvXcNaRJG28cSSB\nQntLEkimJlooLem02jghKOsaayzWGnQgSVoxXnqMtxjBhhqmE6JRyQS8kDipcEjsOEDw6I0HIgAR\n4JXGCrnpcULHx5009smPs3Zm21M+EodvDOv+X/V9p4vklUjYkPQUCqnG+PcmbQo3VprzEoRzhHFA\n0a/RxNQuQ6k2SysFXzxiOKfrmJpMiMOIXTv38dvv+zB//sm7aSVR4+R0oytt10XqAoEvPL5oDnRf\n3KJ1VUL+pQIEzPcz+oMMLUL275shXq348Pv+JxddfgmHHpylG1l6ieOSa65kptejHYe4MmW0sMDu\nfRdinUHJmGyY4ipLmZdM79xJICL2X/l0TGWpi5r29hnMkidIAi678gp80OG2Oz/P+//yL/hvv/mr\nCOHpTM7gsxJR5Rx/9AH6iwscOzLLYHlAZ2qayR27SDptkiSh9hZlauqyxpYlQgjCMMRaxdRUzPLK\ngKqqsHjipE3tYFSMGu54FFIUBZHSqEDinaOTtEjznE6cIIF+mtLttKjrGi01kQ4YZintyQThPVVV\norUkDBVBoLC20RrPy5wkbjM3N2Cm3WO4ukKdxsTC44ohxhpqFVP4IUKAtqAiRe5KAhnQ63WoBwVh\noIkizezqKgjQocYIkMbSSWIGeUFpm0BbjBt1K9G0ofMCPCdwa0ETiTt/mhoKaAS1xtYAM7aBTjaC\nnE2J/LNg+LeFnRFOfN1OJ4Z1ssM9MUnlWI7CczKLRYlx9t83yUfnmqhHIMa6y01nFS8abWnRVKI3\n21wRIYlxUuFh7LBP3p5qL6i9w3qPCiLqyqE8OFGhifC+wDq473BKcsEeTHWE886d5NpnHODlz3s7\nVep42Vv+C9HlAfVhg689bjRm4xTjZ+NBQv/vR4xuzXGpR4WSAztnCNsRVkumw2m077PaX+ScLdP0\ndwSYNUvcmmFycoLJySmEtehA4/KKJ277JI6KA8+8Hl0VHD38GLv3n8f83DHaEzG2qEniBFRE4aA3\nswsjQkzY4ffe/Xs8dvARfv8Pfwcd9ahqR+UV3pSsHjrKI5/7FMeW5xAiZveB/UzvOcCOAxdT5Bl1\nukpbR2RrfYSvwAmEh1acsDzMMOgGcqgctXEEQFFWWO+Y2TJNMbdG1O6QlzlVXZFECQhPWVdESYK1\njql2G60bHXjhmmRhojWB1FR2xPTMBIKQsixwrkbKpoVcZmryssBVNZVpZA5aSZuF+QXYugPhJM4o\nwrBFbJuoVimFEgn9OqfMK0zlqI1lNS3IKkegBcY5ZBTgC4PQEMUBZdVg9Cd8rAfVOGS3Xo8pxAYm\n7tfn+0ZlZvP/tjmyFgiElxvHvBDg680fOPn5rJ2RdkY48a+Gd38F/VCYcVTcbEGhSVYpFTSYtVRs\n0EPG8pxKC5RvGu0KFN6vO+VNvPT1m0D6RknOr2OVm756/FzjQDYOw9ZVg0G65n3nG3aEl57R6iqf\n+fyQ8w/sJHctwqDNyvwi7//YHYBHdRW2ZUFKOtdFiNsV/bVB8/tMK1rbNdntBWahaRr8gy+6mst2\nb2F10HSe7w8zpqem2bm3w3JR0J/psSThrvseojt5OdtnZnDeUKPwUcTk9DSjtVWWjz7CcDjkoksv\nw0Uh7fYUTiRYV2OxyEQQRpoKRz6qeOP3fTdvfN0P8LM//HpWa0N3uk1xbJZD936Rg/fcxezSUaZ3\n7OSyK59Le8ce9u7dzcLxZZTJmEw0aaXJ8xxwVFXNcJARRG1UoIhaEXVu8UKgtCYZN3ww4wTkcJRR\nVAbjNDqK0JHEVjlV7ZiY6GKNpa4sWkvqum40uJ2nKEqiKMAYQ5yEWGspi6xpNAF87qEvsDRcRSvN\ns89/DgJJOhqwf2ub2w8e52ff+zF+782vZbIbk2Up27ftQThLEoUUeY2horaGQMZko4q8siwNBlQW\n4qRNHMfkpiIMQgwSJRzSVafUa54cqGzMfXHKzvTU99i0DqwHOONjQgi8VuAceI+X4myC89vAzggn\n/rWErU4y31C2lIzWGbY0ehQBOImQwdi50/QcbAbBiU2RzvhdIcYtsk4qeBtH+fIEj3fTLdT8O46W\nJE0SSXqLpEm2SSlwwiGFQDnHqIJ7HlmgRcbuXoJfPcyXDh3Ge0hvz5thDdRHmsYDeFBbFNGBkPSz\nObItUKXkI7/4ZkLvWRkM8OPdRdxuN8Jb1tCVnqdNT5KIlGpmP3d84ctkacbTD5xHp52w64JzCeKY\nbVITjrVGFueOEdqCfO0Jdu0/H+UE1kkQmjytec8fvYe7776Lv37/XzNKVzluBtiVNe647ZN84bbP\noHzFtq0zvPz7biLZsZcwF4iJDkVdM7VlmpWjRzBVRaczgXNN4+IoipFTIUVVU9maqqwQQjbwg7V4\nC1VVY2qL1iHeK4xpNFXyKkdJ0cjlOkesJZUQmLrJoRRFSaQ1Zdn0+HTOEiQJZZWPi7bCxtFLuPTA\nRRjrufPBu3HGIYSmKnOkSnj4yBxbJ7t0k5gqr3FGceTIMSYmJ9BSY+qcuq6pDZggYGVQUhjIrKMd\nt3C+iayrvMB5Se0MylhaUciorBCyaSSy7oClEBvzc32OnlSnIDZF43BCY3x9Ljs/dtR+HIkLUGKj\nP6xU6qwjP8PtKe/EnwzLRAjRlCWrCKXaQEijVufGjrzp/O29ZL3ksVGPW4903Pi7xj5bAOOuKh6P\nHGtaN0mkZnMrvBh/x8kcc+8d7U6PNC2azyBxcnzTjccUQiKEJ6LCWHjg4Ar33n8XUSDIshStBUZ6\nqJpxkySmKMrxdXlGn8yYuLGDXXWYj9d88M77+aEXPBuVl5isXAdXUePuNgpLS0vOm0lIXUI33oP1\nkg9+5J+44qILcTJi9/nnQ9IimNiJKTJmWtMkGjAla+kaSdxieXGFD3zw7/nkLZ/iHb/+y/zkT/1H\nhnOzPHHfvdz52VupslWiWnHRxZdy8XXXkDrBzv3n0R+uURUpiS1phBk9rV6PYjgkywZIGdButekP\n+tTGUZkKpSNwFltbvHM4b8iyEid008TBN3TPsqyQxoN02NqD8nTabQItGY2GOKewdU2v08EaQxTo\njeR4nqdMTHZZW1sj0BFCCIypmelNs7iyDEBlDUm7QzY8xm0HF3jzjdfwa395M7FWlIUDGdBfW2Xp\n+ICZLduRusMoz8kqxfxqn6ODirnVFGccUkK7224Ki1SA9FCUJROtFq4sEco3CfLxnPbOYzcgj/Fc\nVfJExL7Ba22moZDrL8SJgMQ3GjEbxWdyXL8gJYwXlLNO/My2p7wT/0YUBhEGP25UvC7t6RnTAtcb\ngm/QsNwmjve4+ezJA46PNc9SSqw3CByKRpPD4U6KkpqbqeTpl17MZ26/e8P5M8bmhafpo+wcFRVt\nWWJMTS0S4tZObrj+cj5080fxl2mC8wLW3j/E9h3B0zXmAUM9NNjl5hYefDTFrjl+/BWv5KO33slN\n11yFVgFRlDQ9QKUnz5oKxnYckAQBRWkI0pz9UzFeSXa86DrOP/9ibv7gh9j/+CzPeMH1xPGQKAzw\nYYfSOsK4y+HHFnnnL/wszpT8/u//Dv/uzW9k+dFH+Ls/ejdfvvcuRsNl9u7dzfOe9WLi3ds494rL\nCKKEnvMMjs8zGQeMIk+V5QRKkpU1ImhRkSEl5HmKlgEC0cjGCktZltRVBU4TSEXhodNpk9cGnbQo\nK0uaGZIobFqsKU9dOAZ5SStO0KqheyathEC2AKitpa5rOt0WVVWjxp3fgyAAD9ZawjAkCALMWAY4\nakek/ZyF/gq7drd49nOuQf3Np4m6XUqzTK8bk/lp8pUhR5f6jMqKsBVxbG6NucwwN6pYXhvRidsE\nYYgONKN0hKksVW1IkhBjSwIFgZdU450isqlkbZzveJcnxUak7tTYUbsxROfH1Zrru1S5aTaLZlEX\nUiKsHMcCTVm+3MglnbUz1Z7yTvzJmhCiwfpoqHkehxCepi/hCcftNwi2m4AQb04eC1jXszjxmXVn\n3CTGkOs7WYEQsincFA6vNIura9QeQiFpLqseO/8a7y3CwY7piKVVgQi3EvamSE3NP96zxuLKiK3P\nm6I8WONyz8y/nSB6WoifcdQfM1x36fl85oGDBGuSn3z1q9BVzfzKGs5ZyrpCSkm/v0oYxgRhyGS3\nR1mMCOOIMh/Q67Zpt2KklkgER+6/Hz3ZYzkb8X/97n+lt3UHo8GQ5cVFlufnELbimRdewJu+9xXU\n6Rqf+H//gJWlNQbD40QqZM+ec9h57Qu59iUvZ1SUJElAXVQUlSGJk6ZAR2l0PMHy6mEmJ7agqDj2\nxMMN3S8IwdUUVcFomNGdnkQHMcPBGuCIE4VDI7ImKRcGMWlRkQ0qpAwJQ0NrokWalkTtiK6UaK2o\njWN6aorRsEbEYI0DoWi3Q4JAk2YVeT1ABT2ch7pKKQsLwlGbslEX9IBTWGClHnLjeRcQTW9ByEYb\nvdtuszocEUYBde0Y5J7jg5KVw2sspoasdJRGooREBQ1tMh2OUFJiBARhw2QSztIKIoYIaq0ZN+5p\nJphrdpBagBEWpzXKCpSQOO+RWmzsINeds1RyA9bbSOxL2Ww11Xhc2YCBbrxrO2tnrn3bOPHG1kNd\nT6Mj4Tci8o33T1MQ4d04Et/EdGmc8xhiGWMsfrPYpx8nhTyAwje3BMp0WZo7zHQyzY4dkvljR0nz\nFISjqCu00mgdspYrwvYWrBWMBn2csywN+witKR+tmwXDePQOjSs92e0FalJy/ZWX8Rv/4Q289U/e\nxz/f/kWuOXAOWknSwYDRKCcIQqTUGGMQUpLnGdOTE+BqVNCg83WRMTkxQZGnbG11mNm/D+8F01FE\ny0bcv/Alzmsl2B0zJMIiTZ9Hbvk4Xmu27NjPM57xXPadfy4T27cgex1cFFLrgMmpSQQeqWWjg+Ic\nUdJBCY8OIlqtLtbUVGVBFMTYqqYYpERJi7ouQcFqfw0vmxVSIsiyjLK2eOswxlI6h3EWS4V0NJKy\n1oGtG9gph9EoZWpqktEoR0qBNRVCKOIowHtLGERIMuIopiwKOu02oq2Yn18CD3Vt0apZgLMso7YV\nxjn+7Ja7+Z93vYWV/pB/9xt/yq//yPfgbcwTS33uffQYywPLoIK80tTC4qQjr1LiuEPcmmBtOGBi\nokeZ1xRFSaAb/ZcojvFeoKwnUAFWC6xunKxy67xwhxQKpwQ2lOAa2VzvGjor1uHlOGhQ6wHISVSV\nZjfpLELrE5j5OoZ+1s5Y+7Zy4mIdyx53l28gb0WjALeOJKrTnCg3cPV1LNGN+bZCnlCGO1ElJ8fL\ngwPV3GzeN9ooCUtcuG+G+cdyZh++j+c+9wV8+o67QAhaSQIIysJi6lWEW2mgD28IhG+ob+EO+n97\nlHCmSWQOPjrCDh2qJ/ELnqsvvZhdW2b44G/+ErYq+cwnbuWTX/oy3XaP/qgAGlggCJrCFqUUw+GQ\nVhzQ6bToRI04lC1LpLQM1xaJdEzU7nLJuXs4HsCNL38DtWy6NCk8/cNz7D1nL8sry4zKGh0nVNZg\npWCy1eXYwwfZt20naQfq2qCcwuYVwjtCbyiGA0qhsOmIqDtBWZR4B5EKyfI+3juKsqLdadNPs6Z/\n5hjX7bbbpItLxHGM1ooyM0RhQBBGjIYVoQ5YWTxOXlbsOH8L84sDpARnHKY2JEkbpQQrKytMTk5S\n100ZfrvdAmGp60blUQhDHIdNE2ax3mkHvLLMp7O0em1aleVHv/ta/vBDn+ZXfvQGsrzi0cPL3H7/\nceYWB6g45vhggI4m0DqkKjM8phHpqprfr6pqvBdopZBSonTcsKS8pC01w6Aikho5GKHbHYo4wkuB\nFQECj7KN9okMA9x6vsh7ZBI1WD8eoXUDxWz8FiCUAiXRY1ZXZWqEUk2ELr4ysDlrZ459Wzlx50Cp\n9QRj0wG8aSy7jnt7TpvUXy+EUPLEjbFOVdw8/sarMTYpGmy8ceeeMIopRscYjiKmpicZZi0ePniQ\ndrvFcDigKgzeSwSaUJQIvb5LcAgBgVAEOqC99WLytWM4NYCHPFXe6IH8/OtfwzXPfQaLcwu4o3OA\n5U9uvpWbrnkm6WjUUNasJxgnBdVYna8V6QbnNRXDUUonicmLDHSz2+i12xTSs7x8nAO791HOr7D9\n3KcRuR5BFCPPmaFflahkC724wnpDx8WY2lClBa2ZSebrAe26h5YarTVBu0WVphhvqdMhQRAxXFli\neWmZIAxBCEZZ1sBSOKJQszYaUNSWJEkYDofMTG9lZa1Pt52QJBHGKVaHq4hAkqUFZVk3OHMYsb23\nhbWVIb12h6WlJSYnpymKgjiOGQ4yolDjbI0ONKurfbQSKCXo9bpkWUactMhEgbWOz9z/OY73l6hM\nzV0Pfpb40pD4kojj/1Tw+3/5KUZ1zv/z3rupnaafVVQodNDGuhwROpwsqEwNeFpRF4HH2op2d4q1\n1QF5VhLFAcPhiKiVoMf65vmgj1oeQpbTA0qhCLpdknP3M+xGuCBCOomVDi/0xjZRjhOX66wWoeSY\nfTKey0Lg5PpOs2lNJ0TzN/BCnI3Ez3D7tnLiSgUw5nsLETRxiG+Kd5oEpQNxouvPOua9uXR/3cQ6\nFfGkxOqJLWqDQ4YIROP4ZUNjc6rHI0/UdPRxfDDN0ZU+0uZINU4iecAbvFBY78ap1+a7glriyiEy\najOyQ+SUJ19sKCphEPCr7/tbfu2vPsiBXdupsgoh4MWXX8ArrriI+aVltApRWqK1RitBWZYNVioF\nRV4QhAHtdgTeNc45kIRekI9S5ESPc/edw9zROWb27iWONFWxRpF5onYbgSFphcwvLjOzdQtFmWPy\nmkQFtJOEQWmQylO5ZqGqymLcyCDAekE+zOj2ZhiMBggExjicgNoaZA1ZVeKF3tgNtVotsqyg2+5g\nvaWqcqSU5HlOKDVlWZEXBTMzE6RFDUJTFBmdXo9BELC6skIURRhbESqJCgPCMKCqm2pMfLNbWVpa\nIkkS+v0+k5OTGGN41vlXIITg/sMPc+yco/S+qwOAnlGs/tmIKy94Pv3VEh+GjOoBAZKgFTNYXWtY\nJy7GigGaBJyiMiWT0xGrq6sMB3nTANmCFk3H+uEow5Ul3tV0TIrRJZn2eCuJUkf+0EHCqy6gmuji\nhIZwXZdnTBs8JfnvpWgqN51DiTGVVjU7Uy/Brjtu0QQjZ534mW1PeSfuvW0U3vzJCcqmCq2RmWpA\nQQWijVUBTmqUU+MCn80TNBiXX64HMetc3PUvAyUlUkpM3Th87xssEi8R3iMUOO9p5GbBOYMUDukF\nGkEpp0BZ1tJlLjjvHPLHBxgVYmyNlB6wsImXjgc1vianHc5q6tV59F6J7Cps6kAJyrJm5g0T6K2K\nhY/1ecbMXn7vh74fLzxFPqLTa4NQ5HmByUty1cBDYRjjnERJSVHWCC+J4xCJIkwiZNjGOceOfedw\n9OEj9Hb0iNsBvs4xdUDUmUDrRhwqLyo67R7FMEVKTxIHTdFKGDIhJiiqgqDVxg5SXJFRBwGh0NRZ\nhbEVQsa0ZmZI54/jywxiRafXIy8rpLf0khihBForqtJRljW1MQgZUNeeqK2YmWpTWWhpzfSuXZSm\nZNfOCeYW+sSdkJV0FQJJnHQoyxylBBZJ0olw1lAOM5Koi3EFrXaXNCvQYUgYRxRlRhBHaBLyYYF1\n/iT0TahmcY+7EwyyZUCgjCSIWjhfY0WNkhprRygZo6SkrIbErTatpM3x46vYokRHEXlZEXW6FGWJ\nyQucz6jtCEHdzC3ThAtOloTekt5zH8nLv5O800LkNb6jEc6jlGqKyFTTc9SO4cT13I6VNA593NMT\nWzWUQykgCiDQoM/CKWeynQFOXDcOW6yX7jgQFuk5IT7lA8IwwahpGia2xgnVOEfnkXLMAhACL+xp\nNCcU66L6UjZReqDCsWrhiU9ZZZrSfZoISgqHFSUIi7MlzlUot9pIh1qD9I5QRUgXYFHQyGfRwCen\nweZ9QBgonHEwI4mfHtJ5Xszyn/VpXRkR7mu6rycvj/nsbx0kCTRZPgLRUPOWVtYoSoOXijQvUDrA\nGwuikbGtiopeZ4LFxUUmJiZI0yGhkLRbLVaWB2y78Dw6O7dT5zVB1ME5h3U1ywtNlB/HMUmgKWyD\np0oFrSigqEqiQBGoGFvbRspWSKaTmOPHZulMdxlkKe3WBLOHHsXXhqwokCbE1YbWZJdBf0Qk283f\ntarptjs4N2rauklJq9VCKMnM9CTLazlaG6ypSNMBW7dvZWKiRX+QjmGUCmsc1pVMTE6ytjrCe9eo\nGOIpqxSpBcPhkCAI0FrjvaOuLEjDKM1pxW12z+zmiTufQE3lqAnJ6KMFLT1NnjUOviqLZpGXUBQ5\nSskmJyMaeqMxjZNNkpilpSXqwqFkgBABWkvyLCPN+3g/wvp8TCl0J805EDhX0rOa4W1fQL/meuxU\njI80vqwbptS6Bvt6NaYAJQW2qpCBbqqbhcA6RzeZwBiD0oowaHD1s4H4mW1PbScuJDqYwHvdwBsC\nhG80onG+qboUAVoneKFRvrlJ5ToUIvW4uKHBnNerMNf1mselEQj0eEfqN56t1A0UIwBv8d4RBTGm\nHoIvcKbE+hrrKwSmoSkKi/LBOLkkeOixR7jooos49PARtAwwDhoH3ui0eO+xdl2jRRCNu804L8nv\nyCkeKpsIPfO4JY9NLat/PcQsWZQVrOQjAuko0oLKOurakBYlFsFaf0ScNHzpoTUECrZMTuG9J2l1\nSEcFZVVjrcE6QSIVE+fspfKCzuQ0y/2UylRMb5uh3W4TqKYNUF2WHF9cYPs5uwmUZpRlCAR5URDE\nEbEMGNg12oFibWWJ/toK7U4bFUZNkUttIQxphSHOOIoadNIiTBKMa7rOJGFI0ooRHvr9EUEYYooC\nU9aURYGpCnqdNitrIyY6k5jKkY0KwrCBigb9FZIkIYk1oRa0WzGj4YCp6Wl0pMizklbUQquAsvRI\noRhlGUmSkBZ5g5MPc7rtHleddzUPffpBCmfY3tpP3NlKXlYkSYssX0UFmjjWrC2njRa4b3hMAogC\nRa83QavbZXlliXbYwwvVBBKmJssGGDtCqAzvmlZuYoMsKFhvyRYKSRZY2mtr5F9+hOglz6KnE8qi\nQLgmfSmlQtDouygBzlh0p9PQIaUkCkJMVZMEColEegi0JpCSUJ4moDhrZ4w9tZ04CqFmGs0TxuRZ\nsd4YVtAIdcqm3F4ohK8J1qs313UhxHo3IMYMlHWHvf6zG+uteITwGyJwwjecYeFqqnqIwFBWFudy\nBBWeuiEd+qaCU25oqfgN5TmPZen4PN1uwnA0GvN4G2ze2eZGVTIkSRLyPKeqynH5eQvBVsq8adUm\nhWBbNcH8H64iu4LIaV7x7Ev5o49+mh+69gryogDVSLVW1jEsCrySrK6tsWWihzc1vXYXYR1FkeOE\no6hKBsOcwtesZUMm1jqoOCHstEjOvwgfBuw/7wD948dJs4yJiYhAa4w07Nt/gEHap7YOqZtdTL8/\noE2Hus6IQoWWUAnB9r37yVf7FKMlQikIVEQVKIy35IMhIBkMRjgLy8uryEAy0euA98RhSBmGZHlO\nnMSsrQzBOzqdhOGoQiJoxRHDLMU5Sztq0x8VOGfodGJGackoHdJfaxx0lmV0u23iOASvcRbSNCWO\nY5xzLC2tkHQT3HgxEQICGfK0nVfgUBhjqK0jSwtAYKwlCmOKqg+YcUJ9ne3hiaIIpSRHZ2fRSrNz\n+yRraU5WFKTZGs4VIOpmtygC5LiyGCTenShCM96jEHhbIe56gL1XXEr3wu24uAW2aaDshUA6C3i0\nbOaiFAJbG6KokS4O2h1yb5BSIpxvipx48gV1Z+2paV8TDCuKguc85zlceeWVXHLJJbz97W8HYGVl\nhZe85CVccMEFvPSlL2VtbW3jnF/7tV/j/PPP56KLLuLjH//4t3Z1QoBq0eglhwgRIESMlC2cjvAq\nQqqgycbj8TLEoZFBglARQuhx/8YmkbNxfwFiLCErhULIoImMcSgFeIMtj1ONjlGlc1Av4arjGLOA\nFCPwBYydtxBNEtU51SwQlEhqJJZYBywvrnLxJReglUTpEC00QjRrpxQKgaQqq7FOS+M8rAMdtGi3\ndvH8Z1xJqDXv/aWfo+dbvPk5L+ej7/xPvO2GF/OJLz5IJAI63Q513eiMFGXRRPjjakWpJLu2bOWc\nHbtxpiKJQuqyRmqNDgOG6Yi1vMBYz/yRoxw/eIhsdYWi+v/Ye/NoS6+yzv+zh3c6451vTalURkIG\nQgIISAthCNjiLIJo84vdrSjq0p8/B7rptsGpTbf4E6Wl0RZFhdagIChiQEJICPeJUHgAACAASURB\nVENCQgagMlVqrntv3brDmd9x791/7PfeWwlTr7Z1JWvVs1ZWVe6559xTVe/7nGd/n++QcfrMGdqd\nKeYWdjEej1laXqYyFf1+n0bcQCBoNVtoqZidncMZS5amRFHE0qmTpGlGEDaQThAIRZpOCKKIjZ4P\nu+j3++hAkaUZw/GQuflZDlx4AUIIyizDWkOZ56STCc5CHMfEYYQWEq0kYSAoq5Qo1kxNN1DaEoUh\ngdY0mzEHDpzH9FSb6ZkOWTbx14j1cJZUAqUlRVHS7/fJs5I4jlFC0dvsEUURUmmUDNA6pDQVxvoP\n3yAMKKoKKRTGGNJsjBTuLD6TQElBEMaUlaGqMtqtFlkxQWtI8yHGZViXIaWrr4cA0P5UWMf7+b2L\nxOiApPACnSSvOPzeDxHmGYkWzCQxU0nETBww024x1WzQShI6rSbtVoNOp0nSiIjiAKUFs1GDjgyY\nihuETtCK4nNN/CleX7eJx3HMrbfeyn333ccDDzzArbfeyh133MGNN97I9ddfzyOPPMJLX/pSbrzx\nRgAOHjzITTfdxMGDB7n55pv5iZ/4iW3mx/9JbRH9lAhRwvNqty44fyhUOCt9GsvWxF2P0laAU16R\n5v2YFaCxofbLHCH8AoiSIKxQakKRn2YwOEqeLVGWq1RmA+MGOFfUWKWgMg7jRM0N36Iz+qndCYMR\ngcfpERSmwiq46+67edpll6GBSGsCoQiFrk2yoLIZlhQhLEJ5dadzFaP+KT7z+ftpJjHPuPIyirLi\n517zCvbPdNk9P8f6aEyFz470GLCjGTdoJwlTjQbNUFOlE2KlCIxgujsFFUgnWVtbQwcCaQRVDodO\nrnD46AlGozGbZ1aZbcZEVExGPYosp9lssrg4TxQGaO2Np6QOGQ4nZFmBDDVaagySQIW0khahtfTP\nLLPZX6URhyRRExEKqsmY0ElUFBHGCa0kIW4mDCcDBr0+UgWUWe4/dAOJFGCNJdTKY/zG/503mzEC\ngRQBSiqEFUQBNKIIU5YoDJPhGOcqpqY7hEFIFEZgBaPRkP6gT7PZQghFUrsL5uOMWEVkaY61UBQV\nzkIYxoBGKY0xhkiH2EqgpKQsK6yxfvFdi8v8dRrQG/TQQqCtoKocG70N8iqltEXNcxXb1zpCo1QE\naA+P1JxubSWlkjjhsMoSD1Pu/qP3kTRioiCkKTVWgZaKQAWEOqyX8YIgDLfvGyklmSmwCoralbIo\n838yX/5z9c9T3xBOaTS870RRFBhjmJ6e5m/+5m+47bbbALjhhhu47rrruPHGG/nQhz7Ea1/7WoIg\n4MCBA1x88cXcddddPO95z/s/fHsCqcJt2hngJ2rnkHUcmtKylhqzne7tfZ0lVgHWEljtG64WlEIj\nbYFWJZE2bI7OkE42CQMNJkc6fyy21h9hfRajrRkrZvtmgJ1j6E6AszrrhrDbcE1eVaycPMKFe6bY\n7A3IKkFRKCpnqZxFOOU/BFAoWyFcCUpz3lSX51xzOX9966f5tT/4s1o2HbL34j1sLi8hBERJyGAw\nwlQGhSCQiiLNiZT0C8FuB6kEo2xId2aaM+sb/H9/9iGKGhp42uIMz7tgP7ccPMSDq+t04pAg/Dv+\n/b/9Ab775S+icpqRhb27djOZeEgoihpkeUGj0WRz4wyNRoypKlASUWacOnKGSEE68rh6maWUSjIa\nDBgNh0RxwmCSErc6LK9tMNttU2Q5nakmaTrhwIEDHEsLssqgtSYKAsbjHtMzM7Rsg6o/QgnrudYb\nI3QSMh6ntJpdimrE/MK0P5mgcFYR6Qgp/IJvc3OTMAyRQhMGgv54jNYhIOl0OmTpmC0dQFYUKC2p\nrGU4yWuiqiLPvK2tt0K23lZBOr+3cRKlAnTQoT/apCwzpppdQhWwORpSmDHWjRDC6wW20u1FPYiY\nyjOfzqayArXPyY5oLXhsleU7v8ji866mMwHXDKnyLUjHobWmMhVFabxS0/hfde3kaIzXERhz9vL+\nXD0V6xs2cWst1157LY899hhveMMbuOKKKzh9+jSLi4sALC4ucvr0aQCWlpYe17D37dvHqVOn/lFv\n0El/dDbbNrBbC85aWVljl+AxQSu2LSc8Xi0FhZZUwmGloeEyynJEOt6gIAebEmCxeVbfNj6eyxso\nOcrSX+RCiG1s8Ym5n56uWGP2bst4y69NPY3Qsra5zvl7FwkDQZ6mZEXBeOLICoEIWozTFCsdFkmg\nE5ypWBr3eP8n78AZx///7ptoRBFjGxMbyalBynSzwWizj4oiojjGUKGdoyxz4qiNw6DjgEo65vbv\npb+2jq0qbvz+bycvCjZHQ/7LzZ9isdXFOMnlc3N8y8Xnce0zr2CmGVCOR+iowVSjzXBzjUarSa83\noNlqIXCMRwMajQaVqRASyqIktJZxOmFjMiIII8qyIgxDVleWAYlQiiDQlNZQVSVKSqy1zM3NMhz1\nSJImp06cZNfefaTZmI3l00xNdyn7/e2mOTMzQ290iqosfAxbUWFKg5SCZhJR5AVRqPyeoSqRRtLv\nrdBqt2rKqCAONVXlWFiYY3NziHUwGg3qwUCTFQXtdoesMvRGKXGSMBqO/abDeI/zJIlJ83UcJWz5\nzNeH27zMqewIVYdbj6o+kzIlN5M6sYQdPaVTNc63c814MdqWvbFnNgHbexdZ5Tz8P/+WxcsuZphE\nMHEUZqdhgx+8dKBqi11JURTb1rzGWE+bPevnnKunZn1DgqiUkvvuu4+TJ09y++23c+uttz7u8Sdm\nWz6x/lF4mxCgtF/aSOmx73p5b7Tb/q9QllxWZJEljx1p7MgbgrIhyZsBo6akagriCLL1I5jhEhQb\nYIZIfCPRShPqCFWzWfIspyo9HTHQYW2ktXPBnw3tUHPVpZT1MVg+7nHtHCWKz3/5EeZ372FhpsVC\nR3L+fMRFuyP2zzqecaBFTMFovMZG/yS94UmIYPFNM6hpiWwIJlnOf37PX6F27+EDd93P9ddcyfTi\nIihNo9VChwFl5ZtmZQxV6fiP7/soP/3uv+Y7fuV3eMc/3EF3ZhpnfRP66Jcf48Rmn6qwhDrEWMf6\nZsrBg48w7g3QQmJwVKM+xajPYGOdJA4JAkUkBYN+z7s5SomOm+SFYenYCdZPnGI0GJEVhtmZRRrN\nlvfQrnKiRkxeFYDDVQUmm7A5HDBOU6SQNMIISkN/fY1AQJUXFFnBzOwsCEWWFUwmGVNTM0jhczhd\nZSmKHFPl2wu9Is/Ji5SFhXlMaYiiCK0czWZIsxkRhwHdqSa4iijyXjNhGPosztgzcYzxpmJhGHrO\nelmR5Sngs16tLXGuQEqf4amk9ulQTmDtgKpMwWlKaxmXPbJygJd3+dtO4hBCbV8zAEK6+lTmITq2\nbZLrEcNarDVYUdEuDJ/8jXdAliPw07cQPpCkLH2CT1mW25O3lJIw9H+2raXmPwbuPFdPjvrfZqd0\nu11e+cpXcs8997C4uMjKygq7du1ieXmZhYUFwHttnDhxYvs5J0+eZO/evV/19d7ylrds//66667j\nuuuu+6rf57ShtHiPEilA12IbqUEKDAWVMH76Rm0r0SyOyAgqbTGBJswtmycOEpsRSmgCHWJMgaUi\ny8b+Z21NO8KhpARpkU5iXYXWAUVVeLUf9ZTvPA/YOZDSay+t9YIhnPRLMOVvUC08n/gzd97Ld3/b\n9YT5Kr3hEKEj8rxiNBrznGvO494vfYnNSUmWbVCODaf/yzrOQjCvsBPDp+65l+d822vYPTPF797w\n/dgypdnqcvzYSQrjcXGLIk4aaCre/Krrmel2icKIn/j9v+COgw+zrzvFG//y71juDYi0Ys/sDEc3\nejy8ts5j6xvMHAtZ2LeLSb8gWJwBV6BEhirGlLZASxhsrKKNJQoFLq0oVs/QVYq1NKPsjxgJR9Rs\nMxkO0daS54b5/XuBkI3BgE4nYjQaMbW4mzybYIxhdnqWtChodaaoyDDGkTTbZGVFkZUMs9TH6VXe\nUKssC4oUijyHylDmFUGkiBsxvX7BwsIuJpMRw6zP/OwU2WiMDiI60w1Gx1eIwjZxEtLrpwQ62Zal\nLy7uZpifYGVjg6jRIB0WJHFMnpUMigwl/OJSCCjKAiEsOB+SLbWjtGOyYkwUNqkoqcjITYoTpYdk\nXK1L8AoFxLbdrGQL3Nj2yJdyJ0HKyJoma5FGUMqKZm/CHf/tz7j+F3+CsU0RlZ/vFYJQhVQ4AhFs\nw4DWWpTa2S9VVcXXytr85Cc/ySc/+cmv1xbO1ZOghPs6Z6m1tTW01kxNTZGmKa94xSt485vfzEc/\n+lFmZ2d54xvfyI033kiv1+PGG2/k4MGD/OAP/iB33XUXp06d4mUvexmHDh36imn8cckkX6cOH1/m\nqn/5Y5j62CnUDkxilQbhJyKU2JYWb12PSimEk5hQQVWRrK3jlg8hZIFEYvOKypY7onfh1aEe77Y4\nJ3BWEEYxQnieunFuOxJOCLbF/EopqsrirCMMlMeHBUT1tKMQCB1irCVEQVnwkz/9Oj7xiVtYOnGM\nyy6+iOVTpzCygbGOcVZBPuTB08vQhIWfmUEmktW3b9DMEk7edxfrBx9ErZ7kzPoZNvt9Tp5exUhJ\nvz9CGIjCkChSCCzdVpveYMyvffjj/OiLr2Hv7Cxv+8gdvPCS/bz943fyXVdfQVsoKAyTScF9a0vM\nzE/zez//k+x75jMwWc64t0YrEFRFBUohBYQ6oFSCsjTYvKIoMg5/4R6qLMc0Yi649GlgLcYUGFsx\nnowoKkGvt85Ut8VwlJMWlkBLHyYcahYWFhhNMtqdhGyY0t/ok1cVp9fWCZOEPDMUJeQGxnlBHDfY\nGAwJohjjfLhwq91hfaNPYSrCKPDJ73lBOhxz+dMvY2nlOFlqabW7DNOCM2cGDAcTztu/m09+4Q5O\n984Q6JArL3wWBsXhU4cYjtcx1qf8tJrnI/HvdzheIlACIROEjKhsTmW98ZWSIc5BWeZIZb0NcQ2b\nCCERzi/nxTaUImox2M49spUHS61Q9temrR13IDSSrJEQP+0Cnv9jr/Z+OeMcQkXhLKLy8BHCe49L\ntePYubVr+tPvfQ17Op1v3Cz+N+/bc/XPW193El9eXuaGG26oj3CW173udbz0pS/lmmuu4dWvfjXv\nete7OHDgAO973/sAuPzyy3n1q1/N5Zdfjtaad7zjHf8oOMUJmIQ+mWQb63POW3AGQW3649VqSiqs\ndDUaXXspC/99scgoNpaJbUXlLDhLWWVenSlFzdMVIFV97PQ/XwhBqGO8E6JGO7MtErI17iilhMoS\nqwAZCGJtCJoN4jDC2gpVc3KNE2R5RRhInIb3/umfEDcavOSl13Pi6HHiRpe0AmFKjq4cJy9ynn3Z\nJXxJHkcmkmqtojpt6LsRs5c8g2dfchH//Ybv49ff/2E+8/ARpBRsjFNaUYizjqcvLPDyyy/h1kNH\nuP3Rwxhr6SYx1UTy6eUTdKOIfVNtAqVY3txkdnqG0lmcFuyW8Oh6j/nFeZytCJsdmo2E3soptAOX\nTlDNBkkcUqReaai0wgnJ3J5FnHPM7NnH2vo6YRiQYRHOUqUZhYEkjlhZWSVOmpiiIo7aCClQYcDy\n6mlmZmY4vbJCK24hpaTTaiOlZL0/oDvVYWl1nSBKULYiaobYfkkUdxiMxuRZiTGeSjg3M8eZtTNY\nLbClb5yLC9NsrC1hQ0jTlDQtCCOFVBZjDOcv7OG5V30TN3/u44RhwjDN6HZ2Eyd7yYuS8WSF8eQU\nU+0Lqaoc50qcbdYf7mVNHcx9FJ8rqcoKhK0b5lazlrVKeOfXr9cbHdVZbm2uVg0LLBahBEmek3/p\nEY7fdheL33INKtZooZHOoJDbHwZbe6UwDLdxcmPMWV6H5+qpWF+3iV911VV84Qtf+Iqvz8zM8PGP\nf/yrPudNb3oTb3rTm/7vvDshEEkIspb1hApkbZIUyG0+rRNgnfCBD9pnBlrhbxWEIqLEFiMym5FE\nEWWeEQSqZqF4oT61C5wSEmsqhNDEUUxQQyMC0GFIkadopYkbUW316qldjopQKZJQEASKqioIgybW\nVtjKT+6NZhMlSqQKWWhOUTjFp275GOPM0u9NyI1F2IzFqRkuefqlHF1fw64bTN8gIonsCmZ1h1tv\nfAvX/vgv8P677uHAzBTPv/5bKBB84J4HUELx7H37+csv3Ev7eJfpzizXXajoD/vcd+YMN97sWUXf\n++xrWB3lFMZwaHOdpUGfZ0/vAjfBNBMuardJi5zx8gpho0WSJDS6M4gqZ9Rbp8wzhoNNUlsxv2c/\nRVog0DTnFzyEFGjmdy2ysbZGEseU6YSk0eD08RPeWtXCcDhGCsXm5iYqkEzRJgiVF+AkTYqyZDgZ\nM5vEJEmC6/VJGjHNZsJoUpDEIZubG7SaCXk6weYFOEuz2WBlZY2yOkMQBIhIYFzIKE85tXQMUxRA\nQJpmJEmLohzTajeoqor9u/aSFgXWOuK4SW4EYlJhXUUYBuSFxFqvKXC2wjmLUkHtY2mwtqghj/ra\nkjs+PX5Xomuvny1lJjXjxMMbZ0MbO9P4WT28VvdKC0oI8tqPJxCSB9//MRYuvQC7f4HAaYJSUihv\n9FWW5TYUaOp4ui0M/Vw9tevJrdgUAhdHO5O10r5Jw7bPt9Oq3isKhNL++7SCQGNdBVYhNzJCU6Ck\nZu95+zn08IOeEoZfAjm7NSntLC21U7STJnEQI4XEVJYgkjSm57ytaVnQaISUZU4SSeKoAc6CMWgt\nsFahpD8XaO0o05JEKeZnptFaMsocm5s9FmZmKCs4sBhghUS4nNI5kgC+81uezf2PHuG2332QqK2R\nI8lbXv89BFlGqBWrgx5PX9xNWglG/RHnT81x/8lTHNvsM8xyPvfQY1gV1B9oft7KqgrjLO/57J01\nhARrVY5KSo4fOURbSS7avcBbfuCVNDoNIhOgQsE4S6HRopKaaGGB9YceYqbbIpQam2fEOoJWi2Zn\nmqOPPcpc5DHrTrdLPhpSWUd7dpq50YRGu81gPGFzs8fJ4ycQOmHf+btAeoy2zAcsLO4m7k4RRN5h\nMNSazlSHNM+RUhIFiv5gRBTETCYZZWFoN9vISHs/EOkYDQeESUxDBNgqIE9zdu2ZJw4jTp1eIywV\nUgYEQYQ1UJYFWoVM0gnOOcbjCQBFVdHrHSHLNxBC0GpdgJRQFBatfcSbw4t6HAYBGLPDXtqhEG5f\n2Gw1bVerQ7cw8a+8BbYk+GezSASldCiHD4MQIF1F4iS3v/VdvPyX/1+KmYA40EQ139xKiVKKLM89\nJh4EO+6dXwMTP1dPjXpyN3EpUd0uJhBgLEJpRKD8ICMlzgnv3iaV58WqChGHtTJToVxIFTk4dRQh\nJKU2nDh8iEBJqqqssxUlUjqMdV5ViSNJGgSBot2OcM4RBwpbQNwMiUONchU6VjQjh3CSRhz45wqB\nDqdQGCJpEVQoIRiqBpULeOiRo9x53z285AXfzIlTy/h70C+aEIaCEmMNiVKUheFvbv88/+6138pv\nve472bQJP/977+Kt7/8wP/+H70UAly3sYjwyjExBWlTcdfQYq8Mhh86skqgEtCKQlrwsGZYZFstF\nrTZPm5viooVp/vzwYdbzCQs/PY1sSAZ/P+Ll4jJ+/Q3/hpmZRfr9Hml/FWKNCBOCMEBgqSwkM9Os\nrW3SSho4csrIIsqMWGnm2i3Ggw2EAFMU5GnGeJxiAa1DQh3izITSwHkXXsqxIyc4c+YMF0+dz2Rc\nUKWG5v6A1dPLSClphpJRv4+UGmWBMifWmp6tiENNWSqyovRGXCGUhSXNcoSQNGNvnFVVJWVZUFWO\n/nDAeDQiiKfYHAwZj8dMT0+ztrpBUVRUVT3tIgikBmtpt/fTSfbTz46QTk4TBPsoxQApQirh81cr\nSsCyQ70+2+K4tjH2F2/d+F29iFc46x+zypu7+WDtszBxeHyrdT7f1RvNemqtlDHT44qbb3w7L/uV\nn0MEMakx6C35flURBAFFUWyzWKy1nOvhT+16cjdxJbALLaSo8W8pcUrglMTFAViLkxqUpBICpENG\nnkKllEJYR9QM6J1ZpVu5OthYUBrv4maMIVSKMAhRcYjEIYWj02rSTGKCOEALSSMKsVXFbNfjwBKD\nFJZQR/7YHTq0glBptOsTa4WKEqrGPv7iY3dy6tgqYZRw2WUXc/k1sxxdXcIpH4SL9QG+1lqqwnL/\nyRNs5SIaDK//nT/BGkczDMnLilYcIXB0mw0eOH6SvVPzTHLDpw8fYzieMOMa6HaT05MzKBExKibg\nHJFWZNZxpBxxqpfxUDb6CqGH0IIISbqyxMFDh7nokosYToZI1fB7gMmI0ljKqiRwgrk9uyknKWun\nV9mze5G0qsiFpLe+QRhHWDzUEMdeKBUISavZ8ItpY9DaL5H37t3FqeUlDh48wt49u4gaAZNJSWd6\nhiiKMEVOXpaYEmxV0m63GacTWq0EGUjiOCEvQciQsnAUhaHd7iCEQGvBOE/Ruo1zsLnZx1rL7Ows\n/VFZ+6l06Pf7JLWwrZ+lXhjU62GlIgxDijRHSEccT9HPjmNs6WESJUBYTOV9S54Yi7YTMCJrDFw+\nARrx/9ZS+oYqrMNu6RC2v+sb1Q40k2uYG8Knfv89vPhn/i2x01RlhUKQmgprvZ96VXlhUFVVnIPE\nn9r1JG/iEtntYiJVN2wQQYCUPnTWWkucJFhn0UHAVBgghKOZNLDW0IgiHBX393o44SiFQBiD0gpp\nDUkQEgcRKhD+NSU0opCpbpdYC8JQo4Sj3QyxThFrRxwY4sAHTUgyhIFAxYAlCS1NtcjRvuWmv72X\nvHiQtq545jVXYiqDsCUbK2sIa71MXYdUlUFJ6S1Km4pnP+1K0qLiiycfJrhW0b6+gelZRu8aceMP\nfSfv/cTdPH3PAktrPR5d6RHpDvcfPc7h1VWevud8itwRihBjJygUT5/ay2xHcc9glfULC/KjJVM/\n1eX0e0dcnE+TTzYojpeYgaX6fMl3/NyzmGCY3rvAyBaYZkTWX6dygDNIFUBhyIVfEC+vLEFecPp4\nQZAkJI0G3XaHtY0NFnftIs1TisIrSntr63Rnuqytb5IXKbsW5tnoD3C2otOZ5vDRE1SV4TnPuQon\nvNdMXhS4yps4dWdmOPTYY36azHKSOGS93yeKuhSFISvG/nlKUZY51lUYG9DqtMhHkizNSdOUJEk4\ns9bHGJiZnSZLC7Isp9OJaLen2JykOCA1E9YHp8nylHa8FyFj8myE1hFVVeB5r4LSTHCu8nFoT8y2\nBKiVnrVzQ8022XLM9L4/1ppth83HhZYIrxp+3KsJ4d0tt16vhmcCY8g1mKogeGSZQ7d9ln3PfgZW\nClrODz1FWdQ+8yGTyWRbwHaunrr1pG/i4e4ODUBHIaYsaDUSIq1I6niqVqOJlI5ABzQkNMKAQCmq\nsqSZJFTG8kBVYjToJCLKDVWREUiIdYDGEYaaMNB0mwndVgMlBY1IEkhJEmrCSJHmVT2FW5RyYA26\nCogiSdwFp7o8djjjA5/7HIGoeNoF+5iemqI3GJMP1/1UGEZUBrRqkjlLomOGkzG9fp80zejbgkjG\nCDSTScquF876500ruFDyS+/5O4SEtMo5vtJDaLh/+SRlbnn++ReggwAVK8qsZDMfE2nJsjF867Xf\nzGdvX4VAEOzRCCVQT9eED0p+9Orn8fE7DxFrxY/c8HwubHVI1wc4o+iXJaK06LbCWsORRx9ienoW\nrKQUjmK5YHp6CtVqY43lzNoqexv7SLOUKNKYqsSWliCIWFhMWF89w2DQJ89TOq0GRZETBpqNjXVa\n7SkWdi2yeuY0Bx86ztVXXoqsBFEQ0O/1oKiI5iKCICDLcmZnZ9no92kmLTb7qVeGRjH9wdgrNzsx\n1np+dBhqSqmQUrO4sIvlpVO0Wm2GqxtYKVBKEgYRcRzzsTs/wermGnlZcGhyL/HTQ6oNw+rqJlKE\naJ3QaM0BDmFCv8Sk9AwSeBy+vdOk6yl8eyrfgVe2ce66qXtpfR3JfRam/kSV8E7VOHodba+sJQ0E\nYVlw6q9v4fxLL8bOtinyEi30NoRSlh5OzPP8n/AGPlf/HPWkbuKRkly7OEO73WU0GhFpSTuMaIVR\nHTbv0ELSjGs5PJpGFHnJhALhLFopsCVCgM4tIi9pBiGBFtiyQMcNtFTMz8wgKUmikEAKEJlnpyiJ\ns5YkCtFVThwHKFcx1W2iI0teRjx4yPHh2z5NOB3yim96DkePHceYiLXNkiRqI/UcTpSsDtc5emaD\nvIRIQWkdKE2FN+mSRmFVQBVIRKUojpbEl0U448gPlZjU/7m+fNzbHLRe0GByV4otHZ8+cojSOLSU\nWCwuEYQviTh824C3fOhjhFqRP1gx8/ournSYB0pmIrhyvsXl01cz3e4QaUUqc1xiOT1YYTAYUI5z\n2jMLCGGZX5zDVSVlXrGydhqNYri2jup2aM5MEbfaHDl1ggMH9tPfWGc0GBBFDdLJGNWI6c5MMepv\nEkURpYVhmtW+N4ozays0Wh3m2cXBg8eYnYlYXFigMTWDtiCRrK6uIAQEQYhSIUnUIC8yyqIknWQo\nZz3uG3rF4tTUFJsbfaytGAzGKK0ZDkdIKeqlpKKwjo2NTbK0ZN95e7jqgssY7bbcf/xLuOdPaL3A\nQyyTu1MmH4OGPh8YYUyJFAnWlVib89XFz1tY9hPUvVDDJV/JRHkiD9ud9fjXrFrNmQYQWEdrUjFJ\nNPGo5PZ3vocX/sKPUBmH0P59mC34rqo86+ccnvKUrid1Ew+k4sK5aWId4BoR1npDpDAM0cI3VyV8\n+lQceQxWOoOWEqFAVZpSOAILWAURzHbncFVBmY9odRNmZqbpdloILEkYkYSaJA5xVnlfZjxuHmiF\nVhqtDFqHqHiaO7+4wt1ffIjuVIeXvuwFHD56mIPHTmGdIu2PWe8PKSoLzuFkzQ+RIUaUhC7AxJKG\nCimTACYFBSNyWRFkkh9922/z7l98I8V9gmqtwmaOXW+eRYaStT/s0fqWozPkTQAAIABJREFUhPhp\nEZ2XNhl/LuW5axdyw7Ou5ujxFX7p7z7Ows9OIxNJ47kxk9+f8Juv+xH+63v/gqV39qgKw2Xz07zq\n+c/k/PP2I6SjLEt6mwOq0+tcedXVHDl6HBVWTE/PEkhJr9/jxPGjVFXF/MICk2xCq9Umq3Ky5SVs\nUZIkCa2owZe+8EWSRLN7z17Qis7cHMpZRhtniOIWm70eaZ4RhgFhpBDzu2g2MjY2e1RFwfnn7+OO\nT93NDT/8WsbFhHi6iXKa3ukVZmenWVlZY2lpiTiO2dhYw4mIqdkOhTUEUcLG5oi0yJB6wjgtGJ4s\n0LJFWozIiwnrawPyImd+YR/33v8Q+w5cSH8wpHIFxgRsbPRxWGRjpzGLhveylyLFGYm0IVKVGFvw\n+Aa+ZY625Xkf4IRnVwm7c7sJ1DZ0AmfZOdSeQM75pacUAuuMh++cxAq3/biolcnUP0tbhxOWLHTI\nyvNkoqV17vvrj/KM77weIQWFc5iqJFQBQRhQFsU/5S18rv4Z6kndxKUUTEWxV0cKgdZxLXH3xuBC\nKrSWiBozlFKiEHU4rPezAEepIETQTprsWpinKlJiPU0SK6QUxJHy9p2uIlYWW4xpqBgNNBohYaSI\nY00iNJWe4fMPr/DZB+7HhQG7Lr6Eo8eOcejTdyKF21aXIgTGWG/y34gRUUDQafGCl7+My668go+8\n7X/w0Pop8lFKkhW0M0uaaKIKRolg9llX8ZN//qc8ev8XESrkw7/0ZraxVgmu3Pl7cqUj0pIDFyyw\nMekhlUCEZ9HbEkF/dYm/+KWfZ/XMKqsnDhOWQ5DOJ8InIVVVccEFF5AOBzzy5YPMLSww7G0ySVOa\n7Ra7zzufRw8dotPqsr7eQwSRV0xGMZFzHDt6iL3nXUBRFqxv9ui6Fp3RmKr0CkqlA9bP9Nh90X46\n1qIGcGZjA9GIMFYxmQzRgfbLSh0QN7osraxz1RWXkI3HSAe75mbpj1MakcZ2GqSFodWZwqLojwtk\nEHBqdZO8qAi0RCnpA6rxWag6AB1IZmY7ZHnJ2sYaKEdlSjZ763SnWrVnSUUn2sXy3z+EbEmEhMHf\nTkjsPNYZfHbrFhf8K10Ad2iBCrY44meHdW7/w+2YYG03ZWG3HxS1se1Xr1q9ia0nern9Or4MpvbT\nn3zuIBtXXEbrsgvpFoIRiqJ2qGhHyTlyylO8ntRNHCAIJNLWQgi3Q4tyNUVLS4Wp+a7GGB+0oAVa\nSYT1ieI2VjDxwQSNwDfaqVaCloYoiUiCiFArwOdiNlsJCINAEcYJOkxwWvPuv7+Fx471sLpN5hzh\n2LGxdhqnFRkWqyWy1SJuNRFxwFt/97eJWjHLZeqbuQ4o8VG4j5w8wa9//CbyIkdISddpzHDMn77l\nN7noZS8gt45ocYFLX/IiysJx6Uuu4/h77yS6xqtT+x8cYQaG0R0pDB33TB/hN8Yf4LueewlXXriX\nIx/cIHheQHW0wq5UXLVrGpkNmAog3rVAGO6hqAxzc4scP3GUKIpYXV3lwv3nsfrlL2OqkkAJesMB\nRkiWVlbpdqc4eWqJdDxhmKfs3rPIcDzgwPn7efTwQwzznIsvvhQdhUgdcGJlmfmFeXQzRuuIub37\naLZauKJiY/UMzSTh9KBHs9ml1UyYpAVOBEzSjCBu8ZGPfJx9+/bRaTcZj4ZESYM2wuPiS6cpJgVR\nHNEfZkwmY1TcJoxbrG+u0og0QaCZ6bZodtocPbZCsxExPz/NieGp2ugqotFokOUZKEGWlrQ7LeTG\ngMhN0wkOMPzLJR9pJxcIggb+6rHeB74qfRN/ApLyeIfLuhk7t61DOLseJ6/3z6i/7kVAAkFtfH8W\n3l5/n3BshZPsOGbuvK6yjlJCkhbc/8fv5yVv/ll6AZTaIYqSUGrGNqvThM7VU7We9E3cWNBKY0zl\nRTfWoXVAZS3C1Y1bSbRUCOchGFFf8JU1qEDxhv/4Rv74Z3+Jzc0+1f4FGp1pjHQ+xiuZQSjNIE2Z\n5CW9Xp/Hjt7L5qDAoqlkiBEa4yRGlYi4DVoSxZru3t3sufginvfiF3HJVVdAHFBWtUFXpNhQjrQo\niIKodqgVBEiUMcSNhAkOF4QYfNhE1tZ0LtnPYyeOcalR5AIoHS5SfOsb/z133/Q+Tj14kF1Xt/mR\n/+dKPnj7p1DPcvzUq76d5miVf/XWd3PlhXP8h2//Zv7wtvt54ANL7G01ef33XM2e+SlWV07S6nZJ\nGg2++9f+B0mgCbTG2oo/+8V/ze99+GbufuwDRIFmJgk4sjYgDpR3eZSS//R9L+K2w6vc8eVDfhmo\nHyMOFGvDz7GyOWKmFRPfch8Az3/afv7qcwf5zde9jC8u9/nTW+7ms7//q0TDMZu9Hgv79pCmKUES\nc3q9xyTNKFEUpSHLSxZ27WKzt84tt9zOt337tzK7Zx+DldME1pBlGVhLq5EgdEhVOsax4/jqBsPC\nP39utktZ5XSaLTY3N5mMxjRaMc5Y8iJDhi0macrU9AzHTy7T6nQYpkOqShPoBJNnaNmiG15UKy9t\nDZ1YPJvEG54J4SmB8ETceuskJGt7WglfpYl/JQa+wwl/Ym/1bBV2VMZP+Fnew15uB5U454MqSi2Y\nnjg+8atvY+E7Xswlz3kmhSyxVYXU0dly0HP1FKwndRMXCCKpMbVa09aTiBDe7ySo6YYCr7hU2lP/\ncLW3iRRU1vL0a68mbiSUgyGf+9LDBFKgwduXGocWGpTCSk1hLZYYIwSzuxdIGiG7DpzHd3zPdyE7\nU8xfsB/bTBgbSaw0tvAJMKWSPu0ntDhjoYKoECQ0GIkSJBhrKLHISFI6n/ojjcJZRyUVSsHs7t2s\nHz6MKw1We8XdSFp04Ljmhh/kyjJAyg0u2+zxzhc/E1WFFMM+J760gtKaxdlpLj7vfH7le7ucXDrJ\nwq55BoMBX37oXi694rmMhgNsmSJw/MqrXkSn3cFhePjhh7lwpskPvOiVLMxM8dvv+ygPLm/ym697\nBYmwTNKURpLwvPNnuWImYO++RX75pk+CEPz2j38Xb/idv+QnXno5l5y3ny8/eowP3n+EqWbEODXc\n+eVDLHRblJMJeSHZvWcPJRYRKLLhCC0UpvIcfmMMYRyRFTn79p7Ho4ePsNEbMjU/R9BsECURk8GY\nbqfLmX4fgaXVTDi1PqZ0klE69p4g1i8ukySirAxFscILn/Uv6A/WabXaGBFjbZ+8zMmLkqg0pNmQ\nokiYpN4f3YnK523WcfACiXUFQni2jrVbuaxfbakpwHnnwB0Mu35k6zfOfwCc3fy3cjWxrhYcsQ2x\nbEV7S+n3QV4EtOVJLkFUj3sHpXI0KkOuHaXSzPQNax+6g6YOaV59MSKQtCp3Dk55iteTuomDN7FS\nwmGs2aZfCWcQWnkLWgTKWQKl/aAjBdZZAhVQFgYtNRNteMvN7+OtP/MLnLjrXlQQYIqccKpLd26G\nhQv2Mrdrkaufcy1XXXsNzW6HQWpwUvhQCVOhAk3pJEUt0IkECGu9nFrVbopSYKs6J1M4KumwGKR1\nWCmIrWQcOMLMUkYx2mmEdeQYAhxVZbjkWddw5PgJjHYIY8gxNEpBbi1WAG5IJub5DJuclwosOd/2\n07/MkaUVvu3aC7h09wyPnXiMqXZCOhzi9iwytWuezd4m670lpNNUeYGxlt/+yKdZ6o0IdcCPX/8s\nDq2u874/epBmo8FkklJUFbv2nEd/Y4UoVJzurTJOU3aft59Tayc5M0x5/iVTHD10BGsdB86/mNNr\np/iHR5f4rm+6iD/4+Bf5n3fcw2teeBX//eZ7GQxPs3DhlYRJk0m/jzWS5vQMwdCHG5empKwcQseE\nSpIpjZIJt91yK4vTmqC5gLAlBogCwVS3ReUUp1ZWKUrHoDciDL1Z1jirMEKxtrmJdJowjnCmpBlG\nnDx6GktIu92lv7JBVpTs6bQJIsWxpQGjLCcvC5yQWP/RjHXePwVChDCUrgRp2Ir/eGIJsQWjbIV0\n7/DH3baH9xZW7qf7GiTfesh7AAHOiB0DK+Fw1tvReq/xOix8m7K4g9FLB5lytfePpAgMcTph6T0f\nIb9JQyyZuvxCiu/5Puh0/y/fuefqn6ue1E1ciHo7b4xfVlpXH+19cJpU2hv7qACFBFkLJWp3NoFA\nWIGRgkEgeP3b/jNJHGONn6JUoPxKtPQufNZahkrTNxDFwY5dp9QYdiapLSqYq4VyzjqEktviDLMl\n+hA705MTAqugqr0yurNzFEVJpDVYf/xVSNqLsxz8/D28sPoh4iihsOXjztVONEEXrHfO45Ta5LIq\n5ea3/yeOPXqQf/Nf/5gvH1/lrX/1OZLIy8Vbn3iYt/3oi/m5mz7P5uh2nINQa4y1HK4sk7ygNCmD\n8YAffPEz+RdHj3HJJZfws390MwA//jt/gpaKf/msp/HCK87n1Kkv8anD9/Gpg0fIiorTm31+7xOb\npGXFf/iTv6Wyjl0zHa66eD/mYw/QDgPOn5tDBwGb6xO42DHJJkgpSRoNbJEx3W4zGg2RxhI3Qk6d\nXmd+926KyhI3Whx88FEOH7uSSy5qUOJPYKUx5KOUUTphPB4h8BO3JaXIK2ZmmownGY1Qk+UlZ9bO\ncPjwIc7bPUOnO8vh40tUbsIkzdm9exdpXrK+0UepgLzsU1mHVA6pbC3EqUD4PFNbG1/5xvy1clV2\nGvgTawcDd2dBLFv/H+x83/Z9YB8Hu3gcXZy1+HTfUNbp3y+ExpJrgaaAYYX79D24Sfr1n3yuntT1\npG7iQA2XeLvZLd8HZy1CSsqy9GY+wjNSDNYfcWtM3Eq/FFLWUlXgpMYYASJAaFHHaYEO6qWpdSjn\nPyhKZ8DWtC/hvZidEo/LJXTWYoz1Dbx2hjM1tIPccaSTTmCswRmLUFAMJxSVQUhJta0g9RBMGYdQ\nWtDKwzJnlTfpCgnKMRuuxZ2bE/bKlFCDVo5vumwv9z5yHCkFb37Vc9g9Ow3GEOuQ4SRnsdvAOhjn\nJVXhuOaCXXz2YR/i8Vsf+QK/+J2Sex45zZv/9j6MdSRRyA+/7FnMKMdv3Xw3My3JwkKX1z1zL5cs\ntnj7338BKxSve/5ebnl4g2Yc8OCJM5zpDXn45BrjvOSHrr8WU46pypJOp8HJ44eZnd9Nsz3FuN8n\niWOyYEK306arQ1IjyQpBmhU021O0U8Hy8imGacUkHaBVQGd6ivT0aawzlGXF9PQUveUB83NzbIxT\nRuOcNCvJC4M1hmxUIJVg9+55Wq0mx0+tkpUOFUiG4zFzjQ7jSYq1ipNLy95oTVqqmnlirbeTpcaa\nrasQwk/PW4k8Z5dfMO6Edz9RpPO1fm8MuK9yR2q3swDded7Wz/Vyf/hKfH3brwXvj+JwZIEjcJYk\n86eIUp9T3T/V60nfxAUQ1tJgIQRh4CfkyhSIOvwWIXe8wIXYPm5KrcBWGFshsIRC0kRhrCO3lf8A\ncJDKkq2hKtSawhk0uhYU+WOsE+z4L2/dlKL2Fq8buN3ywVAKWwfaemW05zRIQBnH6MwG84uzWOkI\nRYBxBiUCnKvIhOXZ1z7H4/9bH0Zu54SRkhJXCqMNR6qY93z+s5jVk+xtKu4/eobXvPDpfOJLy0gV\nsNrrMR3FHDt8jLSo+O4XXMn3Pfci7jm8yr979y08cOw07UaETAt2Tzc5uDTknqOrFJVhuhHx6//q\nJYw2e/zGR7/IJM15+0fuYaoR8cuvnefeI6sg4OGlTf4sq3jaYouVYcEwM5SV4bc++BmMdfzcH32c\n6WZMb5LxY//tL3nnT34fiwuCNMuIGg1cPmZqqkMlYJgVUHnr1KwsGY5TBqMxnakFbrv9Tp73/NeT\npjkNpxGrq7RaTXTYJFvdIAgkjtKfwirLJC3p9cd02zFR0mBmdpq5uRneedMHefDoEloqXvHcFxJG\nIZ8/eA+9Yc87D8qARnMRpELW2DfsNEjr/HJTbMvdv3p5nLzOXcXUV8ITaYaunpD917UKag9EHvcz\nv/ad8fjX+uq1Bbf467FZKTIJ/USAlcTVTijzuXpq1pO6iQvhRTxBTSOsalilrOoGvGWzWRkcwtvF\nhiFS15Jna1BKgNY45wi1xmpNXhbklUMKg1ISXXkGBgDGS5+t8Ast4/zE4oQAW4czW+vdE52jMj6g\n1wnhvaW1rL+mfPN33mnam/P7UInPfeKTPOsFzyOUGmM9BFNWdtsMaXl52fupOOkxYrx3dGUNVlly\nodHphD9/85tZf/AgQgtsZnnhledx7UULWGv5sXf+A4FW/OsXXcG+mQYO+P2PfJ53fPhOkkDVRlYV\nv/HDr+Sn3vlBjqz2ObE+BOB7nnMpvcGQv/jMw3z/NReRFSWldYQNxb75Dr3NEa1GTBJo9s+3+anv\nfhE3feJuOpHmV157Hb/6vtvRsaK0jv/4mpfzkqsv51W//gf84c+8loYrWT55nEuvfjZVWWFMTtBt\nQH/IZDwhSNpMTQUce/QxNntjWu0ZhHQ8/PADLJ9e4/zzzmNjZZ3u7Cz5mRUmWUoQaKanOxw9vcRw\nmBJGCdZUtFpd8nzMIC8QtbfJFQcOMBPP8/lDBxmnOZWFbnOKfXMHOLmySS9bJU3XiRtz2zxwjz+L\nOpLPAMLnGruvbH4CiUTWPbXGriU72PmWpJ6zSSFnT+rVWa+1tVDdqcf39S3jqy1h0dkPnq3D3DZZ\nIVWgraI9ETipMGH4lTSYc/WUqid3E0cQS40zddaghNxWCCkIhXdn00GAVN6XORAC6Rxa4qELWTt9\nIlBW4CpBaSuEhdjpbRVcpR3OsZ0/aI31gbX1e3DOYU2FCgTOeRaKdc7DLVJg6rxNoSSmKBBS8r/Y\ne/Moy7K6zvezhzPce2PMMXKoyipqoCgKsUCQB80oOPHEAUVpW7EdnmPrc2kr/VobbG0spbXFdqlo\nYzdN6wNHBkUFhxIElUGgKIoayKrMyiky5rjzOWcP74/fPjciGdSnrVatlXutWJkZGffGjbjn/PZv\nf3/fIQSHD9JJN0TwYGyOo0bVFRMVKTAMYp3GWh5vFblTrO1sk4WU3IJGt5KOGJkbZwx7jot/8lf0\nt89y9IcPooyivtDwvv9+idGwz+fddg0bI8dav+Ln3/HhWaJLN7f0JzXDSgrFYNrwXb/4ZkDKQJPg\nmzd/4AEAfIi86+7T8mMua+a+MucvfvUif336MlYr5sqC/rjh373u7dJFK3jPfeexHc3ii+bxbwq8\n6rffyXLRwRrD/PwSS5mmnOuwsb7Kyesfy9ZkSrfI6Xa65KrP2to6IxewmcVmJY2vwRoan3P6/rMc\nXlpibvkgupnDNxOqGrKRI9cNRmdE1dAfjOmWObu7Qw4u9djZ2WJpUeNcxAbNgaU5ULCzO6Y/HrO0\ndIi1y1s4BdZ2qZu+/E6iI7Jn1bo/vGF/vYyKGYSno8QCtirKgENFTUTPiuxMgK/UzFNFLGEDer+B\nVvzUIq5SUs9epqAVgdKsq9ezr1RoYkoNak8OOhqi1YRMPn81bu3Rv/7WtPt/zqWVYj4rKbTFoulk\nOYtll9JkWK3plqWkyGiNtpbciilW0zTI7ZdSyd2eV0TtHU3wOBVpvJPuNkg0l4QeS1dkTAZtclAU\nRVwIUQamM2OidOPuo5i1f2/xUPmHbELOOXKT08069A4sC0yiFcG52WO9hu7BJYpM5NpaazAy1I3e\nYzNL6WAw2iZbMWKFCmTHLFXlGWrDWz7wIOc2drj7zAX2Q7Y+eIy+suvSvX3/zsAaxbHleZ5987Xk\n1nBicQ6VK1Sm2P3dId1ndnAEnnrTjUxrz6QKDOuag9+8yPEfO8yBr10gqEh+KmPl/zlE/rk57z99\nht/+wZexPLfA1mDEztYmyx3DZLyDme+xvraKUZ7jK4dpqgoXAlaLnbAPho2NXZaXj/Le97yfelJT\nj8eM+gOGu0OaacWxw4fY3tzAVTXBG6aVY3Nnl+F4wm5/zGAw5NZbn0C/P0RrTZYZQohoW5DlXS6t\nbjOeBkKEabWNzbqEWBPS5hyCS/+u/0YPk/3/F5WewXEgA/pPXm0BvbKQ7vu6RC0MKnzKh6B1V/To\nRJKNLZoYLTFaNBlWlRhKDB2i0QQl10KINSrUV3nij/L1iC7iCkVhLN1Oh9xIIIBFU2pLZixWC5bY\nBr4GLV7j3mqchjp6GhVpdGTiHXVLGIvp2fVeSK0kgbc3FUyrGh8iTYJqInsc9RYDjzHOhpztDRzC\nlcPINg9RhmSKyXjCw2fOgtX4GNBorLVy0ggRpyLLK0cJ0wYf94ZrWotScxim4GHlttuo7q2oLzTE\nEBn/6YQbTy3zn97wl9z+mBXuv7BFiHBieYFeIQeuYeVm3Xa7wmjfDdyA85H+sOIDD63yrFM3sDmq\nKE/lHP2eAxz4hkXGH5jinGfzEw/z5F6Pm8scO2eYfEjc8MrHFWAUvp++Tw0QIItUfkivk6Gj4+K5\ns3QKi9GRIyeO42NEqcDRo4dYWlqkk+c0dSDqjOVDR0FZ1jf7aGNFadnrcfLENSzMzTMajVhaWsQ5\nz/ZOn97cgoSG6JydYc20dsRoOHP2AmV3jnZn294ZsL69w7Ce4rRiNF0nEtE2T7BJov0RiNF9Bj74\nlRv2lV4osvl/cuxau9rQ7SsUnkFdWVNTPuenFHzl90n+E/auLSiLUhnGdtFG5ketyjRGjw4BHTwm\neixg4lWe+KN9PaLhFJDkGx/3jOwVCluUBCK1EwMRYwQbN5EEh3jBoY0V+p8yZJlM9D1REoOUShRA\nBD5RYkkaQsAojbU5IQTBtr1Pw6e9cGQJXI57Ac4Ilq6NwYWQhpKtTagMr6KCsiwY7Y44dvLkzPxf\no3AxSKKLgpf+q3/J1voW5clDe3RGL9AK1kMsOXLtjTzj376c97z6J3DjXW6+cYWXPPdJ/MJv3cnG\n7nh22j+7sTv7Xf5dGy7daAax4s4HT8tM4BMQf61PcWOGGsGtR47xH17yhRgi/QDf+Lr/Rf2wvBfN\nZUccB6b3VjAGPhr42ld8Ab1DSyzMdWmG8toqLCNnyXODaxzLR46yfvEii0vzXDx7CZ3Um/3RNocO\nLVN7R39zwPmLl7jphpvwClyI9Pt9plNHt9ejco7uXIeqarBFznhS0d8ZYnTggQcfxkRPGSOV89R1\ng0fjCATlmVYbNG5Ip3eYdgjYKh9RPg3LPz18LCk8n9yJ70EuOiXzxE9SbO7vwNtC3nbuLd9bqSjJ\nT3xSg6B8glt0kuZL/qzsHRYXpCNXam9wqrRGeO4J2Emfj5+GYXN1PXrWI7qIByLD2GBVJAa5CWJU\nGETZpyLkeu9H0DESXcQpoQIaA4ZI0yT1ZhSGyBWFV2sZeCZIJYQABkzq8ttuKSSZvwoOpQy5MdRN\nLR20kQLtgnT6JpMNgLbL0jmZC9QmUlSBi5fOs3L0KJPoxJUuRnCBWFrMtMIcWeQTv/U2HvvSL0YT\nUSHiBXQlw4ByOB255XnP5bqnPwO2N/n2U4ave8n3EJRhOJ3u/RIzZFaWA3+LdbSaV8RBZCdM0MBS\nt8N/+rIv4PJ2n1f/yZ9zQ7XMPX7KTpjwjvvP8qW3P57rFud48vXX8777TjN5/ZjJhZoXf+5ns7M6\nYqHX4+t/6NncdPONTIfiEDhyDYsHlshcA/1dJirQyQoIEBpPf6OPcxnbOwMm0wle5YyrhrWdTbII\n+cIhhuNdDuQ5w9EAawL1eMxwYDh0cJn717bImJDnOT7Mo+OUXqaYVIpJrQmh4vLaLtpYdgabjJoh\njWtwfkxv/kgaLqcCjiOo5DSmEyY+o/vt0U1tFEppDAGvBCLT5OI+qNTsPW5NsGKMM/ZKRAp1xMNM\nwNMOPtPGERytLzlKviYGoVP5ANaWMj1J8L2KaZajNTHqK04JRhezxoD4mU8JV9ejZ/2dirj3ns/5\nnM/h5MmTvO1tb2Nra4uv/uqv5uzZs1x33XX8+q//OktLSwD8+I//OL/yK7+CMYaf/dmf5fM///P/\nAS9P2B97id9yh6l0rM2y7MpjZhDutUKOn3XdSJFFmiKfirh02HtH2f0djk1MlrbIt3+K8ZYUcJVU\noTbLCOn1yc2459Us8ExIFMWQogAU2iiM1rjgcUl5CggtMUS0tYyHEz76wQ9y80u+EK01AmNrfJDH\nhhDIs4zGBfI8wxw4yJve/V6e88ynsb65xY3XnODVr/1VAI6/8jAXX7kO+1wPi9syqrvTJ6SZo3xc\nDgqm99ToqPicEyf43i94AQt4fvqP3sO0cfz1J85RPj5n9JTIL7/pTt707r/kwPwcxw4s8Jpv+ioq\nH7jpmhWuPXoQRSROJnS7XfLKMX9omcpVLOt5+sMBO9tbHFw+QD7fo6pqhtMpOs/xeKaTAcYYut0u\n/Z0Rly4NeeITP5uPvO+93PXXH+ILn/tU1re2KeYXOHRkhaAGjOOIejploVsyGI1wjaPe2eRQz6Dz\nnI/cfQ+DyYRBvYsPNT44pvUZ8sdkNOecQFKDtXQNlJTlsti8tqr2BDuIe2GS00fEcC3KtalpJfZA\nGlheMT+hFfJEGTqi5PEqbRD7NpDZ1ylFUD4Jh5J0LMpsQykrQ2etRaavI4TEhNHpXqF9QXL9eTdI\nMx6173VcCbFdXY+u9Xcq4q95zWu49dZbGQyEgnbHHXfwghe8gB/4gR/gJ37iJ7jjjju44447uOee\ne3jTm97EPffcw4ULF3j+85/P/fff/xmxxL9tCQEkiRWiQicKnor7utyEUYcQ0EYTlcJaSSwJSsvw\nMMhl6kLEKMm29M5JgMK+gt4W4RjjFcVcay0/gxZrT6UUdSNBvO2NHgGjNdFcyQUWx8X25oSmdpw8\neZIwAzxSZ6ci1kfG0aM1LCwstdVAfj4iSlliivFyTgzBnPeYzPJH77ubh9/xJ7i65s/Lcvbcqz+5\ncUUBB6g+9kmf8NBccvjtgF7WZJXhSY+/mb/c2eSbn/80/scTH88L/u0r6D7NMPcCCUkw37iA/o3I\nr33fv6aaDul1u0xrR9YtMVlGVBpdFsTMsrG9weTsGZrRiIXFJZbq7SjEAAAgAElEQVSPrZAfPMzc\n3AL9yRBtNJ35BSaTEV4HylKzuj0Q29jFBTZ2dllb2yTonHo6YTLs45Tmumsfg4uwtjmkqiqM0oS6\nD8ZSO8+R5YLjhzvcdfosw6qm1pq8c4SFxSXWt+5l/sU55S2iQdh+44Di7AEW51fSm+LxwYmdcNzz\nR/GhJssKWqGP1lbgsOATnbSF0RRtGPFedy/qT60N1srAPHhF3TT4NDR3IaCVml2TWmvqxKiSnjlA\ncEAm0E70xOgTzBOIqsW41RWUxvZ+0rRNkUm1PVxV+zzK199aXc+fP8/b3/52vvmbv3nWIbz1rW/l\nZS97GQAve9nLePObhab2lre8hZe+9KVkWcZ1113HjTfeyPve975/0AuMCiofCdrgpPWZDftmX5Ne\nlyfio6eqKpG5t8rKqAhBummBPVKXnTrl/d281np2TG476Xaj8FEcCqtmCjokeEce024A7c2+/7lC\n21Gljnzt0mqKBTOYloGiFNaDMoZ8vsvFs+ewafNoMX9IHV3Car13UkB8xRO//bt4yhe+gIWFOfbv\nmWF332ax3P7C9v7fHjFizrUtatLsqKWpHf/zz9/DXRdX+eqf+mW+7ed+iS969uciQZvpKRrpCJum\nglSsgvOUeYG1lk5eUo2mDPsjYoyceMwprr/9CegYOP/wOYaDMQ/cfQ/V1g7jfp/ReEQdArawHD52\nmKywHD16mF63w9LCEpNxxfLyIbZ3h0zqwMqJY2xub7O1tcX6+irW5lR1oNcpCR6UrznQtUxdTb+a\nEKwm6oy8LKnqCu8b7KG9Ddcc0VT1hPG4oq4dMWjyrENZdMmzkswWFHmHg8tHmOvOszC3xMLcMvO9\nBebn51lcXGRhYZ7FxTnmF7qUZUmn06EoCsqyQ6fTodPNKTs5RWllYOlrIg6lPOCIOpLlhiw3aAPd\nXonNNLktUFi0tihlkhEchFb6Hz1EjyJRY3Wk9VWJs+GsfMQgQRWtn4qK5iqY8ihff2sn/r3f+728\n+tWvpt/vzz53+fJljh49CsDRo0e5fFniwi5evMjTnva02dedPHmSCxcu/L1fXARq50Ap6tQ5EyMq\nUfNaul8Li7iYYAxIR0mNjhplFJnWTJuGoKXzdY2TdKD0vWad1r7n3P/cbZeFEi/z0OKXOnXjSe6/\nf0OYMQ+02htiGkOv25PUlsQ3j4kOaVEoI8Khjs0gcdd1+7wzRagiujRmVYFgu1TnL/PB9/8V/a2t\nhJeCKmRyG6eR8ok5c8/osvGLO7PcXTWvOPLdB1j/r1s0q54YwK06Dn7bEmEU+MBvfoz7/vAtWD/h\nvo/fzx98718xLMfoBU1zZ833f/7noWJk+eBRBuMhK8ePUdUON6momxGLcz2aIJzv6WiKthnzK0c5\nuLBAVXmW5npsr12ivz1mHOHosaNs7+5Kcr2BjY01bDZP0zjGowllFjl7cZPNwZQj3qFwdDslywcO\ncObeVYKyoKDIHYVxqGbKPefXcbEh+kCnuwgh0kynWF2y+7sjlr5iDt8PjN87paPncaFGhY4IzKL4\npGgj4rFIoKnq2WbtXKtfsPi4J/qS4qpmMF17bVXThJEnppLCUlcVNhdTLUUEJ41LCJFxPUmPjViV\nrBtohHs+44W3kW6BGPUsRcjsExLtX+KI6NNpQafr+e99i15dj4D1Nxbx3/3d3+XIkSPcfvvt3Hnn\nnZ/2a67gQ3+G//9065WvfOXs7895znN4znOe86mPTY8PySvFpc5Ya4PWiF9Kcg1EKZTKxOkPkcpr\no8isJVMG7xxFgkhijPg0uDTGyEBIC+UvAEqLl4rgm3uQCkmpqYLCYCFJ4oU9EFBa0bhIDI6ZeZeO\n+OCk847QC5pD158iqIBWGqM0eBEquUyhNRR15Mlf9kX0omGivGDqRt4qk9JaiIHQ+IRsNvzpj/4Q\nzaktDn/DEm7VsfnaXaKPxEx+kc0Fx9av76IskEMcQ/GYnP4fDXGDgDKK3qEOC9/dm/3+fdfz8NmH\nuPZgj8dfe5Tf/g//N699+x8zvFTx/C+/ha/44s9jvLHGZNRnYfEQ9sABGtew1DQ0lZcNbsHipg15\n5cl6irUzlzmWFVgvEFHs5Ry55iTVcMjpBz7BZNpweXMHYzRVU0GIrG1sMje3wNb6BZYWAvPLi+RZ\nyebGGvW0IbMFrpauc204xDQjFudz+lXN2NegLZkpOLh4kLX1VaJy5PYg1YVN1n5qG6U1hT1AVi6R\nl7kwjLTCNZoQsnQNNAlmixACRkNmNTqAczXaCE+k3fzrIPMVhaGaNAKr+T0Yy1oJLfZK4Rv5/EwJ\nnDb1vS46RcO14qMYUufNbNCqlJXNISadESYNSq+8p0yCdmROLvj+p7E5B+DOO+/8jPf91fXIWX9j\nEX/ve9/LW9/6Vt7+9rcznU7p9/t83dd9HUePHmV1dZWVlRUuXbrEkSNHADhx4gTnzp2bPf78+fOc\nOHHi0z73/iL+mVZEoA+j9vBBkMLaNA6fcEOr9Mx0yjthohglHyq2Rp0KQhRvFcDYPZdCkxlRYEYo\nMhk+tQNNlEInOCOkzvwKcU/6nI8R510aGkWiagemYkmqtKLIcu7+4Icpe12yxKoJIWC1mXXcOkYa\n57j25DVp00hQRbpZ2y4vyzKaJnV23rNx7wOsfNUBuaELLWyKmpmK228l1oOFOAQ0TO+uUJnCLmuK\nz8mZvK+it1Nilgxu3THdrVk5dhjjGnb629z2+Fv5qZsfS2gCndKys7PLfFkwGUR6BxZpvGHp+Em2\nL55n8dA8Ksvp33eahesOEpVj9NAqR44fYhKm9EcTDi4s02nmKHXGuAlYWzCtJlxz/WPIt8csHdD8\n5fvvSaEaiqLTQxnNkaNHiUrEUyFqprXHo9nt98nSIDvPDBc312YeNGXZZTQepuE0oCJldhCyg2iV\no5TAVpnNCYpZInyMV9q7eu/JrUUBVVVhtSYrLRDQOk2J0fhpTWiSWMenE57dg9xq58T0TGm835Pa\nG/aUw+33MyaxqWb4tt6rzWpvKKm1BG6HEMSkax9aOoPjop6pNwW351MKfbs+ubn6kR/5kU//hVfX\nP+v6GzHxV73qVZw7d46HHnqIN77xjTzvec/jDW94Ay960Yt4/etfD8DrX/96vuzLvgyAF73oRbzx\njW+krmseeughHnjgAZ761Kf+w16g1mTGkFuLUUpCkGNMXs8KZSx1iGCzWRdkUNgodDwbE54dwqz7\nmQ0qkYu78U78ylHgAyYqcm0x6JmoqHUU3J9ILtzhOBte+jTnD61Q02i00VJYjKYZT7j48DmKuS4Z\nmlwbSpthtSG3GbkR6qItcsqyJNdWunVtZretVZroPN65GTsnNznF8gL1ucSbX9Tk3ZzeEzugYP5L\ne+g5Je+2UmQ3WA5/+zK6qzj2w4c4/F0H0ErzlFsfx+C1Y6o31AxfN+G//oeXc/DwAYwSvDUrMky3\nxHQ7jFGUvXmszTmwskJx4AB2sYspS1auP4WLnvHumONPfDzNdMrmhz9O99ABlg6tUE89J296LJO5\nBZavu4W1ixeoJ1O0zsk6PfqDCf2dMQ+dPksIgeFwyFy3JzoBpZlOa5qm4dCRo1S14/JGn0kDThnq\nekLXGppqyshXuOgJQVOWJXVdCQsEgSG00hhTonSOsR2MyeS9DIIdxxDRBGxKNrJak+f57BrKskz+\nbUEbQIn/jXMOaw3GaLLMok2k25NZQZZlsw+AEHyiw5rZ9dgW3LaRaJoqXWd7fHStLTORT/qICJyC\nMaCSt5Ckzu59jcqIKiNgiEo+rq5H9/r/xRNvL66Xv/zlvOQlL+F1r3vdjGIIcOutt/KSl7yEW2+9\nFWstP//zP/83Qi1/6/dDIJMWm24ZI8aYWTTbflaJ0RqbKF86kadAuvmghKaokzpz1mm33ysKjGJa\nU60QyKzFRxEbRfWpeDcJxhHfi3QsbYUUgEnfS/tI1IpOXvLnf/AOnveiL8Emif8sITEKc8aEQNCK\nhfl5ttc26Bw7LE9m088b5LXKiUJueI3m2S//d/zxj7yC8gaIG4HHP+axPHDxNGgY/N4InSvMgqb3\nrC7TuypUDrGC4TvHUIP+uOK//+aP4rTl9IOnufnUSa5dOY6PNXZujuU8Z3c4YvnwUepJg+10UdGx\ne8GRZwV68RCLFsa7u6Ad1lroamxhiZd2WTp5CnNgifsevsDJAweJ04refAfnHETH6uo6Z86vsnLN\n9Vw8f4HNrSmrqxeZWzzER89t8KEP3IPVhuX5axns9nn3X53mP//KGzm3tsm3fMHn059kYrFLQ25z\ngqvxidVkjKEoCvr9HWS4JyHbcvlb0MKmCcERgqJy4sMisX8tvVSYQkVZMh2PyYzFWEP0HoXFGIRv\n7oR94rwT8VhsKDsZ3jsyY9JpLpBlGV5DjDoVfUvQ4H3ApNOVStfbHlPFJK56+/nWEqIdclhmeZw6\nQTHRX3FyVMqm63jPH//qenQvFf8ZHHA+2Rv5M63tquK19z+ANnIRhn1sEhsldaflYbewQqYtKkZy\nJdhi1DKjb6PaNMy659YrxUR1hdUsSKGMSh7rWh552PNAiYkpEz7p5/FRyY2TqF7GaHSINIVh0Rte\n+U3fzY+85tX0OwptTRIICR++EzUTAg2eYnXA5cEui9cLHOVaapiXTt+FSO3aQa4hqMDO+cus3vVR\nDi3O80vf+rX80Pf9IL/4K7+KysEsGbpPLYUTXUeKccaXPOW5HD18mE5Z8DVf+kIee/31VDFiQkW1\nOyLPC5o4pcKykOVsbm6Slx2M1+Qdy9hNUdUYm/fw3UU6CuqtizhT0ageJRnjjfP0Tl1DNnY8fO4M\nRx97gsE9D3L59EOYpR4dXaByzekHzzOuNePas7XTZ6vv2J1MKHtL3HvmHBfPX+S+y2d58dOfzL/+\nly/izNlzTIYjXvNbf8CznvAkzl2ecM9Dq4xiw7VZTmE9p8dbTBrodBdYWVnhwoULQs3UmqgsSmcY\nXRKNIkSfFL+KoEBhcE1DWRhAS3E1lsZ7NJAZKyygIHMUY1s1QguBGIxJGHkKKwlerq/9tFUF1M0e\nVu7DniAIkjo4UWijFzqh1no2RJdiHYS+GO3sniBqNJ7gqyuVpLQwYvLrMYq/fv87uf76a/+33bdX\n1z/tekQrNiFBEyHMxDTCBzc03qcItlrk9EFYLC65znkdUFFcChUBvEfuMxFG5FrCln0MGGX2GC5h\nr7ufWYHG1ttC7XGBrVjNqkQAV0GKttdtNqKZYfIhh04dGOqGjjaoTDo3EjzkvUA5tQkYr3EqEBc0\nk3NbLKiTRA3GidRfZYroHFpFCiM0v5oIQbFwfIX54yfw3vOJyZRfePWP8eVf/kJe/opXcd/pTzB4\n+5iyW3DDdSf5mq9+Id//7d+EKQpUFDtfNGR4fBMpOgXRBRQFRWZogiPPLWWmiZkmGEPHdKiVIhpD\nxwbcYJOxC/SOX0s+HDC5tMPisRM8/Ncf4vBtn8WJW29h8LEPsn76IWLj6GaHMd1lDh46wsPnNnH9\nNYpijsWDy/TmIVxaZ3Owy1zWQSdJ+TOe+XTybs7NN17P+QuXZROMkZ3BmNpHcqUwVjOphsl+wbJ8\naJGi0yOomNgZFq3ExdLjCQ1kRUlwFd4FNIos03TLAq3l+W0mTYHVhjpdc03jMNYCHq0zuQ73nfCc\nk0ZBIQN4rdWseLcB36EVCgUR/mgVZs9hrU0FP1k/GIFFlJbGoG0oAAlKQaODks2DKJ250UQfBGI0\nhiolXtmk3FRXqSmP+vWIL+IiZd7jaus2DSfRDn2ifkUVybQUd2ulY1IqBcoGR2G13GQEGRS1MIYL\neKsJUVJ6ZCgk6T77VZcADsk3REsE20wJpxRoJbj9PrMiPXvdLomOhJ7prSJGh3dyrPU+5XMGsdJ1\n3tPNS3Z2djgG1N4L/bCFjRKPPSb+uZZUX4gK5wU3/p3T57jtttt4wTOeydPf/QdcuutBXvPfXsep\nEyt83//1Mnzj0YVsZFmWywbkGmJmUUVONRjS6XZkIOw8ylg63S4o0CYjKINVknqjtBQbVfSYKztk\njWM49WTHDrG5u8HKyRupRoFOx9LkyyxdY9nd2GR55VqGU8e5c+cYjIb4CL1Ol0sXN9ja2MZ2Fihy\nzXB4iUF/TCRgdaSupqyeX8U5+bkvr4+4tD6gwbFQBhYXCtYv17KBpvSl1dXVfQ6UKSRBKWJoiCim\n0yFWZ5AInyFMMXkhEJwxwhHRGoz8/BAxya5BOnU/4/QDV1w3LQSo911T1loiEd84sszOAnpEBCT+\n30opKeQhUuT5ngI4fa8rTpP7HDhbamMIMlTXSvzyjTFotxecYhJM8xknm1fXo2I9sou4UhQ2wybV\nYkQ6B20yyaVUUMdUXNFMqqlgsc7Nvj6GSJ5luBjxTYM3Fh08tp3pKpOUncwGZ0oLI6HtcmbOhTqF\nQqi2cJMGnioNSD2Z0vgYMdbQNI0cQY1g4kYr3GhCZWSo5r1LN6B02REx0ep2O4TRlKZuUhSdkhg4\nSK9NNommaWbDTaNa3rxgoqvB8HvnzpB/8ENc2lnnSU94Ah/66Md44QueLfivDjjnKcqSGJIjntKE\nxqFDZK7XwzvhtaPllFH0ugzHI8oiR2Ul0TXkRPk9BUWFZn6uy9bDF1g8vELTTPH9Ke7YSYbDPtv3\n3s98nkHWYdJ41tYuc+nCKsevuZYjR48xGIw4c2kN7wK1hzxYtrZ32R1O0TanyHOKvCB4iCpjY6tP\n4yIPXdxk4hRKNTz2putYxtDfWcOGgImaXm+OatpHYYi4vVlEcBht8cFJxJ8pyYwlxoZet4P3DaAI\niQ4ZQsAahdJ7xTPTFu/U7L2eqYf13iynVW627xnsUVdt2giauibLMowRLlXT1Fgrw1yjDEYbfBpq\nWquJvsFaTV3XFEVxhSitqeW15lcwXGTj75S5vAYl0YfOJX761fWoXY/oIq6AQhtKnc3sONsbI5hI\n7R2ZNuAdISburRI2i7YZMYoLIUh/FdVed1Q1jXTsBKJrpdWJQqjUbGqvlBJlp7HCFQNUoioSJTgh\n6j0r0SYGAgHvIjGEVGRFIGSj4tpT11GriAmgdTZLPleomXCjqmusD4xHU9kktJbjcbrX2iKeZVkq\nGHJ81lqCAFCK0Di+/1u+jQsf/JAk/1SBF7/oi/mCz3sOCtk4NKnwa8AI59k7j9UWV1Voa8XTxYBv\naoo8o/CFdJR5BkZRu5osy4kRptMp1WBKvrhIDIHh5ja9YpGF5Xny0IciZ3MwoBqOOXLkEE0M9PKM\ns2fPUhQFq+uboDKyQlOHMWcevMDlrTEbO32KuS5hDJcubzAZDhgMG85c6DOpG6aTPt50OHHwAMdX\nDjE4ewmVgoTzPCfPc8SPLM48TYj7TjZKBtqZkROSNVqyXZUlpKg/GaxneCdUSJ8GmESNtUlBmQp4\nW+BbOmpbqGcnyVkylVhJiA5AYTODUhFrZbg+mYzllKTirODKMDOmYat09G0BV1EcOFWWvocW5Wcw\nMkwtigzfOHKbScMShThwdT261yO+iFvEOwKYcbmVgjr4PUhES0G1yLFRo7AIeyN66aBbfjVJOKSN\npvKOxrtZlxTDnu1nG63W3iA+BCxSbMVyohUe7R2RAZzUUAyg2+O2FiqZMhmrq6uMXc0cZUoEkp/V\nhUhUXvD5ENA240/f9rs868VfwkQH2SgiiWXTpg3tBVS0vy+I+BC59KG7WHvoXo7++wOoTNFcdrzt\nl9/JV33Dd3DPfQ+gFLz2v/w4T3vK7dT1BKNExKSLXHj0RmHznCZGTNQUuSU6EbyoEAmpu/QhUOYd\n1i6vceyaw0w3xlRlzrC/jbOaxYNHOHf3Rxmfvps8ZCw85mZ0EGVjXddEbcmyyPrWFmhDPWkYThsa\nbxiMarb7Iyof6G9uoVBcWt1g0MmZNpb7H7zIYDShU3bIbOSGa07iKk8MCqMsUIlPjm9PVcn0SWl8\nKuZG7alym6YS3L8sAel4bSp4jU8D0XR1aaXFwhhNQK4ha+0svHu/WrOFQYyR01lRFDNPFd/UFJnF\nW2G0lHlOUSpiUBSF8OOl4EbKPJdgkSybMVr2D+ONManQW2lotMaHGmOSWZdG6IdwxSZwlaby6F6P\n6CIOiSmgNN5FXBCVmfeNYOFJlBFINKwkiBCanyeEiEvDG2X2Oo4QpQhZK2HILQdbaTW7CaMiOcHt\nSfGxmRTvIF2vUYrWAa59DXnYK7IgXVYkI/cBawxZr0PP5AQvNgEhtiwWQxMVVeJ9x+g4/pgbidZC\ncNgI3sgmBGmQpZLAw0eUirh0L3rvmW6tk61kqCzxy48Y6qrhOc9+Jr/xv36Bxjsm/anQGk3aUDLI\nIozHY/JuF2yGjgpX16i8wOkaZQqBbpoxynTJbJeqqTl0dJnNEczlAbOxSrF4jMnmeaamz8r111Pc\ncBNn7r6foYs0GhbznOnaOpX3jAYjtvs1O4MRm5sDKkpWNwfUqoMqKy6u3Y+PDS44fu533ioRe+l0\nAVCNLrGkFphfeAIhaObmuqnLteS5pVvmlLmlmkTkavGiXAyaaGwKtdbMlXbmU7M3VBRueKyk0Asn\nPBklBEfjBNKaKYvTe5+rTFSWGprGS0E2eva87TWlTCbitBhBexEBaY22ChXEqC2zcvppGlGneufR\nmRR3HxDjt2TvYDOIsUlui+LFskeNdaBzSKdOMcz6x7x/r65/ivWILuIRqDwY5WmCJyjxj3DRo2IS\n7IQUfeUiRgn1K3n/iPiC1uIzXjEYbVFApT6pUJMwxEzc6XzwIjBSwlUx1hKcF7/x6GWoyH57gNZw\nP20MCXtv8JiJ47OedPtMzj/7/ulPlXjldTXBKLjlpseClxmA0h7aQeK+x7Q0s7YzbwMsDt5yM9Of\nmVKeh+yEZfxnU4wxfOe3fSPOREyjmF8wBBdR1soxPrMoZel1e2lzVKkQWIKrgUjR6RLHU3bX1zlw\n4hqcjuRZB99U2E5G7jqsj6d0liIc7qIWlthd2yYMtlhaWmC4vc3i4hKbl1bZ3t5l7BzTumJjq8/E\nKfqN4sLWFvefvoztFqxtX2CuXOLm6x6HURXvvf8vOPRtS2Qrlum9FdtvHHLt0nU840mfjQuBblHg\nR8l4LEBZlizMzaH1ehLziGhGIAotfH1rxXQqnXJaCmmMkaqqpIjHPaOz9r1rdQt5nst73DTkeU5V\nVSgbKQoZgGotJxsfa1wthRglSVJKqxn7RGcZGJ2UojJw1Fpjs2SwpqSJUTqiI3SLkrquIYIxlsya\nGezYngRiTKdApdLfaxQkHrv5ezuMXl2PnPXILuIxCiUqeAJ7qsgYFAH5fG5sEupowS5DQCEydcmm\n3OtcP5lt0nLMa9dAlK4W3eKLgAKbpvrOJcOsFNoszbuwWiIkiwszK9Cxlcm35liZ5RMfuYuv/Fcv\nZRA8hj1nQlr8VIk1QJHnaKNZW71MqGpiIWlFbazY/pu0vWl98MnCVBGiYun4Cs/+vpfzrp/+Sdy4\nz9LxI9x6yym+6Vu/h4/c83Ge/ITH81Ov+mG63XlMnsl5Qkuh0Erh6wadbDsi4NPQNwZQWcHC/CKD\nnR16i0u4yZTdrW06C0sMBn2KrKSbl1QXhmzef5ljj7uFD184y02HDvB9P/ULvOuuj7PQLfmJr/9K\nyoUldkaeX3nnnWwPh+S2oLQHMcUcW/1t6uDQ1rAzHDIYbmCOGLIVuWzLWwpUNuSaY4fo9Qq2B7ss\nzPXkMcqitaEsS/HeDhqNQc8EMUK5k0KGeOwYNSug7aatIri6EfM11MzfvsW+dVIQa22IWmONxZQa\nFT11XRGiI88LvG9wvp6J1PK8oK4m6KBn4q2mcYBAHEVRUFWyKegkIrNlkQaiRnJZowztBeYBayxN\ncIjNT7IXIF7hgulo4cP0M5qrkRCP9vWI3oYj4LzQ20BhlaZnO3RMMfNc9okSKBSwjCiOyUQt8W2N\n9/h2eJjw7ZZzPnMZNBqMiIcCkaAE3sgSztkWdfVJj5OOW6iLKTJAXOyYMf7EMAuovOPBj9/HoWNH\n8THh54lFA/vEHWl+6QkcXzlKpqEoc3EujP6Kr21/phCCIPVtIY+BPEaue/b/wVf/zlv52rf8Pk97\n+Q9xz8fv4zu+9ev4q7/4Y3q9ee74uV/CdkuCtagsQ6m9gqA1KAPTZkoMRuxd0TT1lKaZoOfmBaMf\njPDTMVrD8OIFzl+8gO3Os7s7JL/mCAduvY6LH/oAK4Mxo0+c47mPu5Gf/o6vQ2vD1HsG04o3vPPP\nOHbgKM/9rGcTnGZnusNwuknjKrTJiFqztr3BNEKz7vBD+Z01qyJcuukx19GvhmRZgbFSSMV8Sory\ndDQSCEFZ4WKnggxKumalZl1sW/DaeYdKzB+rDb6umU6nextnwtqjFxGZUckkLUa8l0Jf5B1iEBRM\nUWBMIapgIMvEgyXK1JXcWPI8n50GWuw8pucMzsugOzUk+22KMytDWPm3np0QtQZrtYiYgpsJjPI8\nn9kGXMXEH93rEV3EIeLxNL5GGy1OcTpiVCBD4Ru5wWvlqAI0EeoAdQhMXU3QOqWOa3xikog3xt6g\nSahlVvDvpNBUWhOdiICM0jOhROtEkWm5sWIy8p/h395DiFd+RBmFaWMYbW6zMx2JQ6IShog4MGqU\nMrPwhxgFR33qs57O+tlzVOMxjXfirpiKS7tkOCU3rnTKMaUuStFXwVFogz22wtKRIzz5KU/C68iL\nv/xL+PBdHwOTchljS+NMHajSOFfT7ZSEECl6XZxv0CiqccXUOTpZQX9zjeCCvA9NzakbbyB2SjSB\n8b0Pc/oP/oTpeIf5aw7SzyO3nTpJdI66qdnc2mVjZ8C95y/iJ5GtwZQjB08xrXbxoZK5g84IUeEJ\nwtpRJWv/ZYuNX9xh4xd3eOJNj6fTKRmNK4w15JnGh0ZMrGKgyDLmFubolIlVozQEMDrHOTFXa+oa\n1zR47xLNVKAHFWXeUE9r6qpBK0OeZVIEbYbRmsyKQti3+U62jhQAACAASURBVK/JayfPC7KsmNE+\ntdaUeTG7LqIXW4eWHqiVQiUmiwwhTfLN0RRFiVL7/09jtQzxFSp5vQSxBkiv3WYZeV7Mivx+JsvM\nMoJPDfa+uh596xFdxBWKnjZom+N8pPGGiTPsOsNEG7AV0WvwXWKUzq4KnnHj8BhqF/FBUbtI7aB2\niEGQkg5NcjBBh4iNGh0VmTLYRFOMweOaJglahB/uiTTBi7PhPgUe7PlGtwwXEN53ZnIgMj83xyh6\nCp2Lr0f6Gb0PNJI4QRM8jRPMf+7aFf74zW+jdo6AJrgr4+RanFbuyZQmoxUeh1MRiyVTkalumJ+b\nJ2SWV/zoT/P+932IP37Xn/P4Wx9H8C2ur8RQDIV4fSkyneGmDTY3KKshBnxVyxHDNYwnQwQAUIzG\nU5aOHGVtdZ1Q1VSba+AqRpMBx4+d5KG7P8FCt8e4aXBeNqqHzl7m/jPrDKcTTDHH+bVN+lUl1r1R\njvwtpc4HCVAoTZdMz6PWO5xYOM6zPvcpONdQ6g69hQ5lnpGXuagzY6TXKVFWEzWUZS6ugzpDqdZ0\nKpBZk9glZtbdGmPELCzPMdYmoytLbqxoF7SmsJl0z2VOXmTYzIhFRJqL2DzD5hJEoY0lKNCZRRkt\nmoPZTENUmOKc6KRoB0X0MoA11mCsQWmDzSzGZpjMStHP7GwO00rwlY44V88k+vvhlCzLkngpom06\naf6j38lX1z/memRj4kCF4lA9RDUN82WHoCu2mgED1wXTwekKrz3BCcOi9ZSIMUDwZJkwDmgdBxFc\nxOaZdM4KstbKNqEUuhWxKZVgjIhSQSCF/XBK+mhZDPsdDluucIhB5OBlzukzp3n+4hw744qgUpfe\nfm+l0jfVgmuHwOZkwH0fuYsvQIRNygldUuT/IRVuUPuk2gK5BHTcs801IfKuV/84g/EaP/6zP8Or\nfvKnue3WW/nTd741cdD3vncIEr7hasFclY4EbdF1RZhU2DIn2MBwa4P5hUM0oynj9VUKC9EVLCz2\n6NqczvwiD517mPkDB1jb2UGXJQ9fXKW3uMDawxdwPrBbGy6sbxAjnL20hjOWpvXOJaC0wblagGmC\nnCwArSxWw5OfeBvz3S6rF9ZYXFrk8IElSq1Z81E8bIwhz3OaRgpaCF6KmMqYOi/DwCzDZiKwkVR6\nsQQ2EmxKXdfMzc2l9yTiZr7iYj+7f4XgE688EpNWwftGmEtZJtenFtqp857C5vi6wTkniT6ZwWSF\nCMFwRMQczBh5d+pa2FeKlPFqbXodrTLVz6AgcUkUk6sQwn7z2hlvvX3c1fXoXo/oIr6Uw/c/ocSp\nk+R0MWhCHDBu1njgzF/z0d3IQ/4g42xZnPOCdDUtnKCzjKig8Z6QqFvBSXfnZ+ILk06WUjyFQqiI\nuqVliedy8BFMGowavXf7qtZPPA1ME+Ye9vm9RGMwvubUDdezNRoQgsVkgou2g9aAGPqj9m4slVls\n1OQ2pwlRhmtGzTjCzT7jJIFT9pgIrYijcZ6Ne+7l4offx6HvnENlCrfluffnH6BIrIq951DoiAzN\ngoOYUoW8YzIaYq1lY2ONxcOHmZ9fZDzoQ13R0aCbmkkzJet0mPb77Jy/wGB3l/7mDqOFmsubWywd\nOsx47KjIqF3g4Y0RD2+LubnLNLV3uFAlgZYMH2VQ23q7B9qE9kJHbjh1gv5OnyZAOZczP98hDKcp\nlk943M6JkrLb7aJ1TlVNhYOd6Jl5luTrVmFUljbHPafL3lwHVKBxksazd9oSO1jnGrwXCmGe58J9\njxC0JgSxRgCR0+Nl8wXJY1VKxEhFmcn7hgjJfGiSZYMRymAICUeXQaacTEjXZ5xRHJumoa7rfZJ8\n2ZwIsulk2tDsu+Za0dDVVvzRvR7RRdxNdzn30Z9lef4InRPPwXQej1aG+djhcSsL2PrDxIfPcWnh\nc9juHRA4IA0GrdY06SbSShOUTOq01jReLnAXouTESsxkMvwXiT6BGRXNWkNgL7NTtUIO9mxC2w5o\n5njYFnfv5djsGr7iq76CS90MU2ckY4/kUrf3OhsnhVlep+P2xz0BEyKNVuACLh2R92PxJOhBXq9g\n6yptUkorJjvbZIf3ccYPGEym2d3ZpdvtJOvSNnggCMRCCpO2FldNKMqcejqmN7eAdpFARhZH6Fgz\nHg74H29+B2/8k/fgvOOlL3g2L33a7WysrzGaTMkVqLLD/Q+dYTTVfOz+h4lKszEc47Wm11tmONkg\nK+ZwzQBjS7RKhRwBekK7wUUN0XHzzac4eniZj9z1CUJKdAo+MBkOEzVUPOe73R7Ly8sMdgPO7eKc\nZlo3ZHm2p3zNkwAGDVpwaAhpQCoCHZ/EPsbI4LEockJwGJvT1DKgznNNVQnlUHQDce9nUJHcGLyL\nNKmbdsGhTC6ddgzkeQZa0zQRk1w4jdYynI9QdrrCnknxe3VdJ2ESM9gkTx4rOrG1dGpqxJlWbBT2\nw3Ex7imBr65H53pkF/EQOb86pBrtQnU/yze9EN/5SrBTyngtt9yoObT4EL/5nneQX/MstooVgp0n\n1BvkURN0gfaRRtVMM8XBWM6OwzGKd3OLKTdBbtoYoxT0EGmiRxcGJ6nAZCqZ7pO8vY2lrt0Vr7lW\nNcZk0lG13PMY0WXO77/lt/ns//NrCKamQw6ZoXaO3Bqm0ynRMuuwlRKq4Jd8xZfRb2o6uscgqymD\nFBXMHvVRqWSItA/iCToQlccHOHTzjVQPV1SnIb8uY/JXFUsLC7zwS78GtLy+B8+c5T/+0A/yb77l\n69MmJf7m0Qk8E8YOjybvZjTrawzHHudHHKwz3nX2Ev/v7/0J7/q1X8R1u3z5N/4bbjkwhx8NmEbL\naHdCrcfs1I5f/cM7OX3xEo339EcfFzMtLSk4VTVAa0uvdwiPnIBUq2/SCoLBZ4GiVtxy/WOY1J7B\ntMHmBTrCeFQxHA6FihoFfrGZ5tCBQ2xuDNncknT5PMsIRmGVOE0WWYGrG3QmxVvpQOMqiqwU+mGu\nkIQfnXJRPVUzJc8yiiwjaE1urPiuKJg2tUA+ecFkOqLb7cgm7xvKsoNrAoPBiDzL8V52p4XFRUaj\nPrnOQEdCqIXr7v0srKKFRYQNJX8Pbs86GZWGm1FEaFol+qMxNM6BgjyJjYy2xOBwzZW++lfXo289\nsot443j43CUGC4boSrabd3HqcUcYb3+CnckONusw3e1zPKv46F2/T/mkFzMMimhyRrogKI3VDbaB\nBa8Zxim50jMYw5iU2GPbju9KT3FrLd45CZvYx6f1CWsO3gFX4uMqkyLbZohH2S2ItefEyjHa5KFA\nTDmHAr9keU4kzhSjAHmWce+Z09x083HGlUNneyZHNrMzb2zgCjzU+5S9GYSW2Vk+wHP//St493++\ng82tTR576w38zh/+T245dSNRB4LzXHPT7XzpCz8fVze03OI7fuYX+LXffDNKKW67+SZ+7o5XUGaK\nyXDE/MIc2+sjHnzgApfXN7jlmhXOnL6f7sGj/Ivbb+MdH7yLL3ryE+jvDBiMRvgi5+P3nuMZn/VU\njiyucvrCJuuT86jjNcsvXMCte3Z+a0CZLSI2MTM51uz32PLoe90O1526jo2tTUIIdMsCxd5swntP\nVdUEDb1el5hOFq0OwLtAUzeUeYFKUnhiTJ4mMuTtdecBYYmoKNa0SlmMBh/FObOq69SVF2Icltgv\nRVHgKodREYNYB2d5RhMidSWRb91uF5J1rQ8O1zQsLCxQTWqslc25rmUzt1k6mVV1iuVrrmCatEwr\ngfRIQ1JhoOjkAWQ06ESjzLIs2eleyXS6uh6d6xFdxH2IrK33GU8ceTzIUbXO3e9/LW7YMKgqxq7D\noF9x/uKQ82e2uTZasAvYbg+yOar8AObkKZwpKb0mqEaGZd6RGQvJGVB0QXID7nmW6xlzQ/lIDKBb\n/LTtehOEITqfdpCZFKTR7+GVMZKHyMGFJYxo5YlRCnnbNbauh60roXg9Z5x6wq385R/fyZOe93mo\nUOF9Mr5KeGZbvNshZuuMJ6IniAGsUpz87Nv5mt/4LQ6Mdnnl859JLxl/KQJ/9Kd/xg3Xn+Ka4yso\nD1pFzpw7z397wxu5573vwDcVL/vOH+RNv/VWXvy8pzOX5YwGO/QvXCQnctOxQ/zY/ac5e/YM3fUt\n3vHuv+TEwSWmWNZ3x2wMBmS9JYZ1wcfuO0tQlklwNG7Eka9axiyIgKd6sMF9ZILWNumaEjdeRWLw\nxAhGKW56zLXYPGdre0i308NaQ6cU33OKAm1s8hlX2EzjJtO0T0eKrqQJZTFQT8VbJbNWVL1I0XYJ\n0irLLjGGNBwdoVSg7Amk0c4jfADjgwi6lKIsCmrXYHPZcMoiRylmojPvA2VZ0jQCoRVlTnCy+Rpt\nZkNH4bS3qVWNWDbkRtgqucW7PaOsmRNi1Kio8D4ZnGmNMRmj0WhGX9SaVMBjGtr/U9/VV9f/7vWI\nLuIxRMaThoXSM24i27sZXg1x0wWqQcNuPWR9PGSnmefP3v0Q/8IscuTUNXgX6XQLnM+oh48l3vRZ\n1OVBOl4sbLPESmiHPLVr6GYFNnXANpdup9spic7LkNJoaieFIbh2iCnFXCmdBl8QUxdkBJRJQ8/I\nytw8oyDDUQBH8obeJxyBvVxFYwyu8VyY9nnoo/fwxOc+m7LICXXCwpXIvPerUGeDKsAHcUUU7N/h\ngqQCjTGMjWEu+ZG7xvGm33gzL33xlxKdDDMb7/8/9t482NLzru/8PMu7nuUu3bd3SS1ZtrXakmXL\nCLwRLAMTMDYMBkMlJmEIRUIRUhMY8FSmYGom2BSThUmgYGIHQwBjDMFm8yZbxpss2ZJsyy1bqyV1\nS73e7Szv+z7r/PG853Q3S+EiNRmpqp+qruq+p++5557leX/P7/f9fr5UuSbTmq2z51jJYDLZ4Yr9\na5TecOb0WUYbGwyKAR//5CfJ1lf43le/nLf+p98n15qjB/exO53z6PGzWFGz1RpOnHiauZE8eWYz\nuVyjR0hBmEXUOL3eYZIUNz1Nl6RI6WVzQiTEb4i88AVXsTubMW8dEkmWK+qqoMhyQpY08yYk3reU\ngiyXrK2t4r/2DBHZX/wieZ5R5EUaHGqF7KWGi/xL5yxFkTEYVjhvkk481+SZYj6D+bxNEW46Vbdt\n04AQVIMa03YgAlrn/c/rIVmD9N7z3mONxbl0kci0ZD6fMxwOiTHiXMB0PUURlzCyRYkgve4B2+eG\nGrRKShwNNL5LG3gfOmJ9R5b3+AidDGZlmS/xAMaYS4PN5/h6Vm/iIUbazuC7EbOuxZycUFUNbWeY\neU8715i2pG09uYKd7W2qUcFqvcJsa8rhyzcIzTPsPLMHe3QVrzRVTJhB731yZ8qUUZl+YI9Himnw\nabrU2nB9yyOGVLlE+n/78310SBtvZ+3CHb+slKVS7Gxu8djjj3H19TcTgiX2ffOFfnfR81ys5MLL\n2X/VUZ687wtLciL0kV39prCoxBccD6B3oSYEgA92eX8AoSjY6jr2S/DR45zhT/78I7z9f/tpRAzp\n/8fI2rDin/+jH+AF3/g6qiLnm265gVuvuZzNp48zWh3z8IPHePKRr1AfWCV4uGys+MnXvxpRV/z+\nHXdRZwU7cwdZzT1feopZsMzMDEdEikiMlkwOOPefdxi+qsKd8phHHXVeJgWHWLgqY/8nbeTra3vY\nt2+drXNTEBllkVFXFXkmMW2Dtw6lNBGoBwMOHTrAnvV1Jt1pVlbG7E7mPQ1S4HzooVJ62VpYVsJS\nIkRkdW1MXZdY2yKlhhgQASqd4ZXHhWTLV0UCZYWY1CB5kV0wDJXkedXDryyLhJ+6HrGzM0luS+9T\nxe8MdVUDFu8FdV4TYnqtTdMuX+dM9PWAlkhSde9lJIRUCIQQKMsMHfokIplOJarH6TqXeOQxZlwy\n3j+317O6IRYB6xU7Xct0JzKfT5nOwDjDZMez03h2pgGtKkIwhK7j2H0PcPb413jeAU2ct8SdTfKv\nfQ792GexwWK1wwmPtZ6u64jCo2OGDZImSlyE4D02ClxM/U/vAsEGPBFPinBbWPFtZzDGEEKgs5YQ\nPcYYXITORgKapjMcqQvGR69GonBocBIRZa98sKlqTvKLpPF2AeMMUub843/4ZkKpKWSJlikIWosU\nxKxkgRQ5RI0gg6jTH0AoTcpUVOgoGPhAm2v+6+e/ShAlEssH/vwOXnLTjawf2Eg8ah+wXnLskSf4\nD//5t/nsb/wSH/z3P0XwkXf+zvs5u73Fsce/hp82PH7iNFvzObNg2Q2KTx17ig/8xZe4/+HjXP28\nF3L/V5/krvsexJqOYAKEAqXBuYgVmlIPqcIa848F3Jc1db43ORWlIkRHxBCxLE40SkquufIgZZ4z\nby0IScSjle+fa8faoEqhE85TZIHxeMjG/j2UZclgWJAVIvFFQq8O6jfvReiDlIGqKIjeEWNHXeV4\n65NhKyTAWiY1mZLUZU6uY38hKYkBCBLTJib7sB5QZBlKCqoyR6qAVKAzSV5oIp6iyAjepcq7MVjj\n+jzPpJH3oWPBE9dFlkxCUiBljlAKLyNt9FiZhABCC7KyICsLRG9qEqL3Gseeua/PA8IWXoNL67m7\nntWVeIzQdoImV4joyTPIbdK+zlrP1AQ6m6rNSEoSP3t2i4PrFd7tZTafkJWrzLYnSS43mZG/6DuY\nuSmiBOct2ha0YU6mZOJ5RIGPkqz3L/qeeOidI0px0UApxBSrtpA1LvrSi2HRovpVSjHQOYcuO5IC\nAHq2hXMGQQIwiURBWvKtnU/gJ9cZZrOGwe6UNquRMvXRiaTMTZK65kIok/c+3SbSIE8KBVrhCIzb\nyFfNJh858SS/8wtv44N/fgff8spvQjSGJnjyEHDW8qUvPcCNz7uMfSsDtgm8+qZruPuBB3n1y57P\nV776KOcmkafnOX/8x3ezsmedD9z1achFv9FlfOrex3n61FnaTGCkp4kt47UVxDZkRU7tPaIqUHaN\nnGkaKmrZ80gMQi+GdudPK9EZXvjCq4kI5rMGIRWDQZlkkkCpCzYGIx5/eo53kbKq0XmBMR6tC4TI\n6VrbM8LbpcW+qlKfvC5zqirHm8igKsjyikIXNLZJF+y2Q4RIpjOElIxGA1SrkZnEuXQB1yoxSbJM\nEIInLzRKJexrnRUEFZZzi9YbiixHS010gU6k+DfTddT1gJWVFaxJlfv5gXffPpMapSSDfICP5wfy\ni5nOwu6/YI53XXeRFDa9T3tz2KVC/Dm9vq5N/OjRo4zH42W/8O6772Zzc5Pv+77v44knnuDo0aO8\n5z3vYXV1FYBf+IVf4J3vfCdKKX75l3+Z173udX+nBxejYN5CmQus82Q6UARBFIFpA3MTcFFhbSCQ\no2WBNZFmtoN1c8zcUpdjmp1tRDOhnJxltv0Eo+fdTLNxLVBhgsWqgkJ4suBI6NhIjJKokpsxEPvq\nR17c9oi9MSem20NIsKTFh2ah4dVac/yRx/DrQwhggkWJFN6gddKrp2Ny6OVjLqkogkWqjFOTXTj2\nEPtvvhkffdIJi/Otk8UmDhdAtXr87kKn570niEj0nkljeMNtrya7xjM5N+P9d32Yn/z5/53/62f+\nJU4KpAxctm/M/V95lOMnT2I6y598/C7WRxWfuP8J7n3gGR776tewsWK3jdzz1D2sft+I6saSGCOb\nv7HLw6cfQwxrVi67jMte+Y2s3/hifD0mazY598HPsHXXXUwmZ1HBYaRCyUBwfRtDa0JwfThGGjCH\nENizMmTfvlV2NufJPSsD45WatbUxXWdQzqIzjekMQQiyIqesMkxnaRqDtwE8mDZVt2VZpplIr9TI\nC03Xtdg2MBhU1FWNbS2uc+AjVZFcwbP5LMGpREQXmqLIsdbh/RypInmh8aHtGSeCskhqkDIvcM7R\nWJeGnlkBQmCMJWowtqMuBxe4gqEqCkL0VEWBs/2JpJ9l6Cz1tltjl+TDdLKLNE2zfE9lWbZ0mOpc\nM597slxdFOp8aT1319e1iQshuPPOO1lfX19+7W1vexu33347P/3TP83b3/523va2t/G2t72NY8eO\n8Xu/93scO3aMEydO8NrXvpaHHnro7yRlihGc18zmHklAKRiKDBcdrZH4qIlSYm1ABIlxESkLijLH\nGstsp2V38hQiK8EZ8JGhjdSP3knxxL2UB65nduh68qCIIkPkOZKIJuFsU4/bJFhRrxpZVG/p8cWE\n+pNJfeBjQIY+BUhlLFjibTdn/2iN03noNd4sq6IYRX+0jSndJ6a4NKUVKgRms47v/if/mDv/+M8S\nPCnpIHHeAakNcKFZYyk1jDENvbTuI10S0MkUglN3fA55MDD89orht1f4aeDX/+27+dmf+JG08RDZ\nu5LTuZZbfuhnEEJwYM8al6/v4de/fAcdQ7ZsR10oDu7fQ3j8EbIj2fK9kl+hGV97G8/7oX8CQiRk\ngVLk3rOSHaH9nm9l7Ruv4donT/GRd7+HJzcbtJSY6BFonA1onaUQmhiTS5PAy295Mfs21jnx5KP4\nIMjLROeTArQUrA6HlFXFma1NHJ4DB/dy803X8MX7HqVtGtq2QQpBM2/Q2fkgYt2zUaKAqq4JvsU4\nz6xpaTA9hyQpjXQUOCFw0VPmGtoupe3kGXW9B2td6nmHDKkkzlqyQUVW6WXPvaoquq5DCiiLirqs\nmE6nVEUOIfZDSI3oOeNZptFK462DCKPBkHZulievslTLoIlF/NuiAk8KV9+jAuSyELPW9QPc867f\nS+u5ub7unfVC/CnA+9//ft7ylrcA8Ja3vIU/+qM/AuB973sfb37zm8myjKNHj3L11Vdz9913/50e\nXIyRWdsx3Q3MJmC6jN1tR9MoTOfxIYUfd/OG0PcRQ1QomTGftRjgxKmn0dKR+Q5tO/LdBrN9mjh7\nnMGTH+fA3b+FfPBjlFtPkIWICwIfEqJ0Op8l16eg1+2a5QYOafDqQ6oSXZ+/uRiKVVWFMWYp75I2\n4ETEWZPcmb3DLh2DU9iykgm5K3v9sOtaqrri8Z2zXHn5EYosT5hd4jJWK0YuOkIvWBoqCnLdB0p7\nj4gROo8yls7Zi155IZMSaO/qAerhkM51/Oy/fwdbe1v2/fQ6az+8wpnZLk+ebXB1wYQdsjqnGQvc\nTZex97prmH28I/qI2/K0X4jsv/5mVNeREwmzDtsFGjJOaYMzGn3oBdyzUrE7GHPdtc/jjd/9HayM\nBwTfa6Bj4n+LqNAyo8xrLjt8CGNbus6SMAkK0V+gQnDs3Vjn8qNXYvqh9dVXX8EtN1/H9TdcixBg\nTYdSgjxTDAaDpeZ60YJqO0MUAiFzfJDMmpZZ26CLEqEVYomr1YxXVtLznKWNuWma5WZeFAVSaoIH\nKTVSaNbGa8vAYqUUq6urvV67oWtm6XHlmiLLqIqUnkToGbbeoRDkSuOMIXpP0zRA3+PuAVdt29J1\nHVqniLnF12OMtG3b/z29R+q6oigzyrK86D19aT331tddib/2ta9FKcWP/uiP8iM/8iOcOnWK/fv3\nA7B//35OnToFwNNPP803fMM3LL/3yJEjnDhx4u/04GKEnZnDKEGeK0yX2inKeYIEHT1K5+zsTmiM\nop0ZiqJhMNzPrFEoGRlWA6IXGC9wsYHgyPIEhfKyRbDN6s5ZwpkHsaMN4voVZHuO4Ef7aGKOsgWu\niOi2I+j8oovZeYpgwr+GEPBaokKg61q8CGghkJ1lfc8a2u3iKYnBYHujjlhowkXEy6Q3X+QkWlmT\nhUgjNdfUqzyQGzIje7ORIvYfbhGTtDEKMC7hYhdGICUEznkg4iQgcq76xm/ii7/5TqZ/0aAPKuaf\ncDz/m1/F3Vbz4pV9nH7qBHd86j7G/2yAGivUWFG8JKc5VXPLP/2n1AcPMI1gpSLInLWdOV/+5f+T\nkz9/DKTk6Pf/IKOXvCRdbpwjzxTetWRBURhFKAXGWva86CWsfl/BPb/6Gzz4yAcYDQd87/d+O+9/\n//s4etXVfPWBBxgVI2IM7Ns75orLDzDd7ZjPOqTwVJlCK4XzKdWprAtidGztdgTpUIBpWsx8ggZG\nwxXm81OEGDEGlCqTqsOni6lpG2bMgWTvb6aGPM+IcUqRSbrWUK2MkDHQdXNCFOR5ATKZdzIhE3vG\nWAqlyUpJnmdkWcas6SiKgizLmM/TzyjrEmc1IOk6S4wWmcXeAJRY9M568iwnSoGLgXJQoZRiRfbI\nB5cyT6VPEYQJFSBp25Yyy9F5xc5kmrjhUpDQ+RnWRQQZeR4vbeLP8fV1beKf+tSnOHjwIGfOnOH2\n22/nmmuuuej2xbDkb1p/3W0/93M/t/z7a17zGl7zmtf8lf8TIrRW4LqOoaxwwRJFqjJ1phBZejN6\nF5nNGk6e3qQqR0ymc7w3lPWIGCVb2zsM6grvA05qQnQIkwY/3neQzSiNomhPM9h+DHWiZJ6tAiXb\na1cirr2Nkhrn2iW0KAXvnv/dFxU4ITnmIgk1KpVkr6j5xV/8ZW78n3+YqAIhOqTIl711SR8g0eNo\niQuTjiTagJeRR598gm5PhRCpcjKmlz96j0LgFumR3iO0Xn7oAaJMHBhrHTrLKFZWuP3t/4b73/X/\n0Bzf4rJbX8IVb3wTv/TZ++hEmx7PoMad86hx0p2Hbcm+V76C+ZHLmYWkkPAIjA2o0YjrfuYXkLZB\n5zlRBIT3yeRCCo3OhEIj6DAMugzpI1SCbDjCI7Eusrm9w3ve+4dkWvLIQ48wqIbImHCxz3/+UYbj\nIafPnKDr2qS4kJJAYLI7o8wjr37NbYRGsLm1iyDFzFk7wxpPawxt1/TSuwoffWpZKUk9yJnN5ksY\nljEOgU48cGeTxNT5FPxgDFmWPjZ1VYBQdF3DsKzIegxCcrxmCBEZDAZUVcVs1uDc+VCJdJHtQ0r6\n01SqimM/d7F4F6nrcilVzPoUn0VFn1pOKgVsIxAetEqSQtcZsqpenlClVpR5gRSJw6Jk+hP+Eonx\nwnXnnXdy5513/o23X1rPjvV1beIHDx4EYGNjgze+yCy+QAAAIABJREFU8Y3cfffd7N+/n5MnT3Lg\nwAGeeeYZ9u3bB8Dhw4d56qmnlt97/PhxDh8+/Ffu88JN/G9aMULTWsZVgY8CrXIiyfQhXMTIlPoT\nkMxnLZubkqIMbKzmNE1L3qY2QZ4ledXKaMR0Ok/2a5LjrSgKhMmZtwZbWGQRkN6QmzPUaB7fmjJ+\nwc14ymXW4oUb94V878VROVjXy/rg0Qe+yE1Hr+CeD32Aoz/0BoaDvQhZEELE971261LVWEpF07UI\nJTHeo1UKBkAq3vDm7+d9jz3I3AqC72WIATrryKRCKIkPnigk1vVpRzGR+tIANSMTut8gIqODR7jt\nf/lXeGPI0eACBBgUK3gnuOkHfozP/ad/Q3mTI2wKxM6QA6+6HRNEYpW7FLwgiUhrIEZ0UUB0iN4M\nJfqTSqYE6oKhbzSOLpcMd2b84dv/b6quRcjEZ4/WJkBZlEid4vWGg5yDB/fSGce5sxOkVOR52Xcb\nAirPqUrJrJny6IOnaDqLELC2OibEwPZkvoSeaa3wTkAMFLnuQ0I8RE8IoHUOMWCsAeGoq4K8LGhm\nU/K+wh2PN1A6XRQzrYlZckUOyzpVw72CqarKi7T7o9EIpRRbW1vJvFOn1J+TJ08jRLpYSQlFUVDX\nQ2azNJx0Tlw0UJdSkuk8PZciXQA675AitfFypQk2sVIWevciz8l1EgEoISiK1ErKeqDXX7f+cnH1\n8z//83/rZ/bS+u+//tae+Hw+ZzKZADCbzfjQhz7EjTfeyOtf/3re9a53AfCud72LN7zhDQC8/vWv\n593vfjfGGB5//HEefvhhbr311r/TgxMCirIghGSHTqxmgSBVIS4kPvhsPiPPCuYzQ9cKzp1rcb5k\na6vB+tTjns5atjZ3MZ3DO8h0QQiSpjFsuU1aGlozR5gOdneZGsHEWFbikKFRBGWXzspFoITqiXAL\nWaFzrh8igWlmTE4c56ZDB7GuwSMZDEapjdNHjAshsM7hY6Czhs55olC4QKIR+kAXAjbAAw89hN+e\nYUJStRAlzqUwYx/B9s9NRBIifTxY7Dd0aDu71LN7n8IusBGJwgjHPPds54YuNBjRcPAVt3Db//pz\nHDr0HRy57fu5+f/4RbIqp7KWtc5QArUUVEAlYKgURQhkPqJjJBeSXEp0DKiY8KrOm3Ta0CCj59O/\n9luM2y5pwYVDLoaHMkPpLLlghaCoMjYOrDLvLCFkffVqEVGiUBS5ZM/ePYz3HmTWwbxrGYw0N9xw\nLd5lnNvcoe1anE+5l4vXseu65euW2mKylyNmFGXOaFSiM0nTNCilGK+tMBgM8MFRlxWHDxxgz+oK\ndZGzd30tmWuUQKjzJ7QFy6aua2azGfP5PPXf2xbTmX4wWS436QULPMsyiiLDObuMUbvwxLdAL4SQ\nyJZ5mScHZ9NirWUwGKTsTiWoiuQvUEJS6IJcZ2glWRkNyJS6pDB8jq+/tRI/deoUb3zjG4E03PvB\nH/xBXve61/HSl76UN73pTbzjHe9YSgwBrrvuOt70pjdx3XXXobXmV37lV/7OPbekHpCUKuUlyh7U\nLwh47/AiEvojpPcWZwRGRx595Az5dTk2Oqo6BdDariEWHpsptLZY6/t4NJBbEj0oCZln4jxCgw4d\nXYhsPX2WE4NjXHbbjUjcUmO7qMAvrMIXnGcRIqZp+bM/+AP+/s0vghtfRNi4nIacQfS9q6//QGqF\nMx6pFZaQlC59PqMUic3h8IzW1vAnTyHqESGGNAxVSdkiosTHkMBM/QYuYh+qHHzigRiDzs+HAUBq\ns7gQ0tDMSjKjIJeAQ6rIyuEr2Lj8WnxoCUJiTUgcEwmyT/+BdLFBgPIGrdJjUYQkg1OqD0sIOBEo\nRDIytc+covniQ7S5Q9uO4ATIjExl6WIkYGF93X9wHytrY85uNhibLu7OWaKvkRG8bdjYv4d8tIeH\nH30SHz3DUYmScObUDieeeYaz5zbZ2Z0ilUKJDOe7i05RoodFlWXNdLqbwi0GSdanlCUET2c7BlWd\nNn5rETKyUo+pipL5dEpd13TWsjPZRStFUZQY0wFQFIlkmIafqR2XBpGJP57kgV3anEOg62Y4l5Qp\nZVkuB5kL2FWR1+xOd2itoagKFjmhOzs7VFWFlgprDQLRs1r6wgOJzhP+djqd9cCvS+u5vP7WTfzK\nK6/k/vvv/ytfX19f5yMf+chf+z1vfetbeetb3/rf/OCEgFor8lwRoyfPNCmGOGFalRCIqFNUmta4\n0CFkRjao+cqjz3DZ5ftoGs/xc6dYXx1g3IyD+w/gCTgETduiM0U+KNjxUwZ5gYwR6SRbkymdyXn8\n6RNY+3muvfYwu4MR9E636Cy+1IyNYDrMWXeRTWOoRMAqgRwN+d4f/nFMqZhFSzc7i7aGNqbNWjmP\nRiWbeARpPE4lkFLqcwI+YpVHB3jk+NPnU4BiIAiBtw6hJE74pV49BRKljTaxzFNgBVpge6u+s70O\n3TmcdUSlUvxcHhDR9zzy1NO3dHgRiTH1epM2Plnho3fLvFKEoBMC4fuQi86hlMAR8c6SxVSVTk3H\nXiQf/KVfoY4t0kdc0EgViMLReZCiQCNxeExr2Nh/AKl9rwBpk4klk3TRsjvZYVSvcNm110OW86X7\nv0pUgrxYY2dzwoNfeowTx08xnTSY3jjTtjsU5YJpklRFUkrabkbEUdVZcgeE5PiUfTVdZjkC37cz\nUsiDc45xPWJQVTSmITiPLnKE9721PdnkJ5MdjDEMBgOMMVRVRVmWSCnZ3d3tTxdZqoy1ZncyxVuL\n6wJCdBchimMMTOcThFAoFNhIlms6Z1FSJTxtIYlElBLE6BAyoJRIbPyQ2n1FUfTV/3/zR/XS+v9x\nPasvwwLIM4H3c7IMrElDobY1xJCq8BgCksS9zvOK3Z0ZIWaEoJnPPOfOzYmxoDMKZxSnTp/j9OlN\nzm3uMG8sbWNp2o6mMUxmDfN5x3TeILVG6lW2z3To0xOO/cEHWNMFPk+SMa1ySpHT5hmrTcqAfMWo\nZt3vMvTbrNkptW5Zn+7w9wb7Oby2itcWWeTUXbJMG+nposFmkXnml2qXhWHHRociYqzDZ5r77v48\nKqZKPdFEIi6mzSb0WuBFZbnQDRMjwaf/s2BqxBjpui4hTRfALOcIffiAj2Bc+rtbxI31970MuvhL\nktPUWzYIHNF3hGjwOIJzKC8JQaCiYoDnrl/9TbLWEHrnqehTlLwPhODxweDoCNFRjzP2bIxTC6Kx\neJfmCHVdpwGykOR5waG9a8S54d4v3YdxLYcP7WcwqNnendB1Bq2z3t0al4CrhcQQOJ8arxR1VfZU\nxIzZdIIUMKwrdKYYj4eMx2MgDbhH4wE+OrRO7BStclZH46X5ZjAYLFsko9FoeZILIbC7u0vXpUo9\ngalKhFJIpRitrqSKWidnr7Xd8v60Tnme8/msr8wlPiTd98rKuFfc+GX77EI56yJa7sLX8pJl87m9\nnt22eyIhWqSMGNPgfUyp70JCZ9F5hnALtjJ4F1GqYDZNFfaZ07usrNQMqpLdHYOUsL4+IFOSc5sT\nRsMK6jLZvYPAujQAbLsW4R0zrzi9OUFWO9Rn4OO/8wfc9g++hyYuWORQKQ+q48evvZWhmFG7Id09\nj5G/7CoaIqNzLWwI/uv/+O3c+8GP8/RNN/HEvj2UoSBKRWE9WcwwRKK0SzJh7F2g2gVCltH4wGc+\n+nFecPu3pI+coN8EIzLShxWkzTZR7hZ5n0lv7Kxd6pwX/fxFUvoy6SVEZG93B5bGphAuVuJIKTGm\n6w1cieIohFjGi4kISifNe3Aespw2OkZE7v7t92IffJhCRqwMF8VUpiCMgBC+/10kK6s1e/atMJsb\n2jY9Py46qlpTlyVZlZMVmoEKnHz8Sc7sbhEkXHH55UynU85u7dLMO4xJm3UIgUymOLSFdnqxoa2v\nrpFpyaBK4SFFJhnUI0LwrIwGrK6uEvGYLt3XwhGZl5q8KPHThiJz1HW9jMdr29SjLoqiH1Km/vtg\nMKBpGqy1dF3HIo1eZXk6IWpNXdfkOkvqI+9oOkvbdYQQCSKiiwznHVrovsK3OJsG4vMm/UxjDAB5\nnvdMlvO8/POttUs82ufyelZv4kQw1mNdk/TT/rxbMlcBbQ2DwTCxv2NEBI/SaWI/mTasjAc084Cz\nc4iWQV3QdZHjZ05y4OAGQubsThp2J7P+A+moqrx3tpWcPr3FfL7D9tZZJJ4NnfPJd76b2/7Rm2ij\nRznPSBp+5oaXsVka1rbnfPF3/4jLn4mcOrzCuqhQ1YCTn/44l8cpn/rMJ6k/dj/6pqsYfOe3sCMj\n22e22Th4GTu+ZVyMlhu4Dx6RK4RNkW9T4XjeFVewzPPs2XOqH5LGPhRByFQRTuezpJzoXaaZVDQX\nZHJaa5chC8vB7OK47l26iHjfZ4aeD4Be4HNTsMbi9BCX/V6lMiQ9RCw4NGnjqhSc+vQ9tJ/7MlEH\nZI8dUCJlRy6GekJEIJ0YNCVlXaCUZD7vsMZjrKPMFo9fQigAyHB87dHHmbYdSmmcdZw7u83ZzV1C\nAGf7NlHPIclyvZTqLfrQ42FNlinmsylVVaCVYM/6ClmWMaxqhoOSzpl+8FgAgSzXVGVF2xqcC2RZ\nQdd15HmyxM/n8+VGutiwF0ESw+GQkydPLmPVjDFpVkIiXxZZUpQoIXA2EEVLZx1tO0cWkrIumc3m\nBALWG3Z2dil1TtsTEc/TGNN7pK5r5vN0gVi4eS+8/dJ6bq5n9SYeYmRzZ4oPDinomz899jV4ijKj\nMxYlRkgt8N4RnSREj1I501kKA8hzxaDUmM5x+swWdb2CtZHT57YZ1MmAgZAUeZL7ddYSVc5nP3sv\nWbbCfOsMZcjZzc+g2jmf+9OPccvrXsF3XHk1t2yMsdOz1I+cwY8KRrdchx5XZCdOULzkFk599gvs\n03v54pf/nMe+cIwTRqEfuB/3Jx9j9doXIAtFddM1XPG8I5w5eAVRalSPy22MRQoNwdJIx5UvfB6x\n89giGZ6EiISuwyH7/MnUPllUWrZPhiGC9W7JU1l8uENIWY9tZ9KAVwradp5QrjGk3npM6paFtHJR\ntXKBzPJ8pmOi4jnvcdYh8tSf9ToysJI7/+BPGVvHbg3a90k9MbIIqV6EFEM64PvoOXLZQcoyZ2tz\nk/m8Tc7L3h1bFGlGUpclwTo+/ZnP0jpLEIqtrQlf+MJXOH3yLJPpDOdTqvxwWEMmCBEGVUWMAWcN\neZZhTYczsLq6wsbGOnmReORlWTGoKjrTURQlRVmyO5lh+vaeVIKV8RjbpotM5+xyfrFQLC0SdbJ+\nY2/ajnnTYowjhCR31VrQOEeIASksRkTKLCdTOUUu6awhBIVchH7EFLeWLvqBwWBAdH3gMlAWBd4r\nBoMa7z07O9vUw2G6qGcZZsH3uVSIP6fXs3oTdy7w9NO7ZKpXVYg0UAshUOqSEHYZjgr27qmhB/2k\n4Y9MrQGZfj1rPJ1I0KCs0BS5YnurYTAqaVpB0xoEnkFdgAQfkiqgKse03hL9jLObp7DSskdEqrvu\n441vfj23HNhDdC2FN+w8cD933P9FbvreH2D39/6UE3JKnEc29o656w/fy713fYZd47Eozohd5Lyh\nuucMYwejJ5+iOHyE+NIbiN/0Uhw50gdKL/A5FGR0sWDv8ABeeaKPqDawXYBUgdKk3rgTkWD7DNHE\nGb2AaCeWx+dF1QtgfVJeAElDnGkCyXNE36K5UA+/ZKRfwMJZ3C6EoLFt+qIAlbhRiMby0Xf/Earr\nmGUBZQEhUMi+ylc9Q/z849NCYkXHxt5VgnHM5y0EepRrRlGU5EXOoMpZH6+wdW6XL335IWxMhrCd\nnRnSBqa7u7RderxFnhN8xHuXQoeNxTvH6tqAveurlLlCSsHBg/sZjWtsX3WPR+NkLlIS4UNSQoUO\n4wxZVmOs7QenHQGBzjIkgqZplm2URWDHbDZjPmuwJoG38jxHqeTiXIYbC8AHqqzAecOkc1RFxqiu\nmLWWLC+YziaUeUEmVZ+9Jph3s74dlZ6j4D2ZShdSawyShD4eDobJEOQc1rlLe/hzfD2rN/EQItvn\nDESLVOICfklExwaEZf/BMVWR+oRSXhCKIEQyBoVk7DBekAlJFiWbmzuEYBkOV9je3CUvNKPRAGMi\nrTGMV1dwXtIZh9Q5IRps2GS6rRjmJYcOBV5x1RG2JIiBRt3zKPce+xzf9s/+J7aNo8o0z3/pC/Ef\nuxt3y1Vcv7bKHfMJ816S12aeEaCcIbZzOHuSzAbsVx9hvG8vW887io4KqT1We2SbrPOf/9p9vObF\nV+E6S2shCwJBxHlPlGJZaSfSXWp7hNhHwPWtD9G3UFK6TopnI8Y0rNUZxpuLqnVgaV5Z9G4Xg80F\nlwPSYPDCfND0GCRzEaiOn6Y59jCZDH3iUC9/pC/E+7W4LyllkmpKGI9H7O5OaRtH8On+1YI3IwRC\nCvbuXWey2/LMmTOJH6MKilyhJGR5Rkl2ERyqKAqqMg03u9axOh6ysWcNpQN1PUjAsnqDslpjZ2eH\nEANFlto2mhS4kecFUmRYY9HaM5lM8L0pRymB6Vs1i5bKeDxmd3sbZwyFzqjKCgE47xPnJNP98yeI\nPlBkmjLXWBtpraOZdwgpMdZirCM4T+NTEpALHu9835Kx5EpjTJecpUqyM50AIslYjSfWyU/gl7OL\nS+u5vJ7Vr2AMEde1xB6gLYVALxCs9MdGAfNmB6XOby6LzSdVnBIhFG1rMVIybxvyXFMWBafPnCXP\nFGU95OyZHfJCIbOM7d2Ws6e2EhK116GjPLtil7Wzmp9916+xXWcMdidsffZeGqG4+pW3w9d2iPkO\nj1YNRx8+w1dHlrVuykc/8Umu+YZbOX73F7BNSmWRoSOXkdU9BVE1nH36cWIH7nc/yO5rbqF6+Usp\njCDkkYaIcp49Wc7+DKIQnMsiemrpKkHmkrHH960UIVIYsFQSFxaqlTQsVFItVSkxno8jXipXxHn1\nyeK5NMZcpEZZ9O0vpDk65y5Sx0gpCVJQB/jk77ybgbUY2bPUZWp9yQsuOgu07uL+EJKDB/azd22V\n7TPnsJ1YBijHmNohxgRCEajLimYeOHX2XO/mzNm3dx1pLWVR0nTN8jEXRdFrwpMB58DGKtEbtI4o\nnVEUOevra3Rtij/b2NiT8jCjpzNtMmLpPt7PtGRZgVKa0DtMldDMp8kcVxRp46+qivl8nk44pN+h\nGg4QWrG9vZ1ImYDKMmJw6DxDKc183iWOubP4GHG2fz1sQ5mVGJ8kprlOVvuiqpCyZT6fU1VlaqdY\nh1QZOs9SFKBvmbdpxlTWdfIsXOqJP6fXs3oTh4RPlReE5krRb+iqTyJHMZ20aF2dR68uVkh9XSEE\nUeq0CcgVjPO0bcNgoPFBMj99juGgIqBoGsPGyjrTSZO+VyXdsnOGQnom7ZNcd9VVWNsiCs2grHh6\n9gTNJz/Lia0p1x++jIM650/e9yG2b3w+V+25nB/7/ffyEze8DD+boEXByMKtL7me6tyU7/q2b+a/\n/OZvM8xKtro57r57KDZPo4Yr+GufT25m7J/s8Oqrn8+V/+JHuVpYtrYMb3/sIR7WBWWTI5XEOkvo\nteFKqSQ/9ElVkgKfExfdWotaQLuEwniPCx4lZJItXtAaWapW4sUyw0W1fZFx6AIYGIAPARsN8stP\nkO3OCcKjPKAScRARiaQQZLF4G4rz6e1RKI5cdihVtZ0jeIn3FpUVPXNcYYzFdJ7ZbMaTp06ztTsl\nCk2Rl5R5hekc01lLjJYsE0iZZH/OOcbjmrqsqIqCPCvZu2eVjQNrDEdDsiznxPFThOCwVvQDQN23\nPAqapiUqyd69e7Gd6QOuc3YmM6oyZzAYLHGwp0+fZnV1NT1XUrCytkrbGqbzGTH0SiJr0gYeA3lV\np/e41Exnc7xNw3akxgtP08xwpiPogrxKdEUlFZVSuBCWpp6sNxTFEMjyLJm6Mk1nFB6BvUCtc9Fx\n6NJ6zq1n9yYuIrroaKkoAmgPXkWsBjqBzpKEbmtrkuz4F9icVf+mRiabvpIKKTUqE/hQMxwfYnv7\nGXI7pxYZapizfW6TerhKrVepVyvmJ59BqwlCREo1ZhY6Do0LHv/1d3Hgiv0Mbrmer33ig6xNd8ht\nx+NhApvP0G2eY7M5yw3jl/HYF47xzIGPIoXh9le8jPuOPYI7s0P70CMcb7f55B+3XLZxkLu+9gg1\nGYfXS46dOMWZj36E2y/P+YlDt0J3D/7hz/PIA55zZ5/izF2P8prDhxkePcjjVx5hS6yi/ZyZLBiE\nAhnmBGRvxFGIkFx+jjTcTBV7UpjEKIhBEaToWxSQJsgLtUkaOF64UqV+8fMtpUQojaYHeTlPl0nu\nveNOMtMSiowgXJL3+YAISaUR0CAuYFrLZBxyDsaDknnrmZuIiB4lc5zzS862AvAR3xhOPHOOzgck\ngWAtm5vbmG5GWeXkIaOdzZea7eHKmNVRkdLjVeTwkQPs3bvOvoPreB8pi5r5+hDnPGtrY7yPnD2z\nRVXWWJss7pkuyJSm9U16PmS64E9nDXlekIsMITKqcszuTsP6+jpdt4OIKTZvPm/IpECrSOc8VT0k\nhMBs3pIpjUIwnaXwiUgAKfHO4gPovCLIpGkv8qQJ90Qmkznz+Zw8V8ybXcqiojM2uT2VJsw7ZB8S\nba3H+0X78b/DZ/nS+v9sPas3cYlA6BFV11COKoIC7UC3Ea8X+nBN23RImXqcC2XGwmDhQkQpvWR1\n4wNKeOazbQ4fOsLJp5+kk4GnT55FKsF4peTBBx9h3q1w9OjzeeqpB3GhI8qWOkoOlAf512/7FZSb\nc9PNV3NgJeNFN1/H8VMnuPX5N9JuTTielXzX9/wAf/yO32XLB37tzg/xY9/3Zu78i79gbmasrBbc\neOM1fOvr/wc+/I5388TJ0xRCUQ1rTk22GLSC15aab9uzDmKX+ckJp+w23fGnaFuHOTzmhisv48Tv\nfIQ9t1zHA7e9mMeqNcbziCsmNKJGu8TchtTaMJ1L8WlLOV9CDgTvQSQFCuJiU8+FQcyLFReSxqVi\nhV7NkpCobYxELQhFjjSW137/G7nj3/47Ku9xeoDvh6gxJJOK7D24y9W7QbXKOHjgAKZtcJ1BLjTq\nQi6NOUpKVsZDOmM5ffos3nn6rDuMNb18LuWR1oOS4SiRBuu6piolR44cIssFe/euUdcVIdAPxjuK\nImc0ytizZ53pdI5Su0iRUZb1kiW0SAWCNDcYjUaYLrlggwjMmim7013W1taIMlIXJW1ryLOC7XYL\nei24tK5P5Ems76qsmE2nhJ4770m6/CxP3690RoiOohwhpSD0/PssS7+blAKlBLNpkyScWrG9vYNz\njr379hCi7yWhHQlhdmk9l9ezehMXSjJYy/FGYboJlx86wHSnocFiXOrpBp9kbcvear+89wiV7NNK\nKlI7ZnF7+uCdPbvJy1/+bXzh/o8znztKFJ2RmC5xvmdzw5HLr+fxJ7+IDFPGreaMKjhRCqINDKTg\n7HbDU3d8mhc9/2o+eufHODPf4ZZbX86v/tp/5Kd+8ic5fewYJ48f5/5PforJ1g6VEvz9b/sWrtrY\ny31//mEmkwmN82R5zlqmOOE6Gt3ynd/1as4+9DCrrztK9l2v5OAdn2U/khMq8On3vo9vWd3gnH0a\n/UDDCzpD+eIXceyKVWqvcDEgw/kLGrHXnpvkBA3J008gwZMukgrG8/3uhfEo+MXmn04+Ukpc6Hno\niP7rfdvFWgpZIL1DypzNPSsMXnAZxRMn2DEGHyNKyBSWQEL2LpaM5y8SVZVT5wXdtEX4dBpw3iH6\ndpnrDPVwwKCuOHtui4cefYwg0klCKklZpSDoPapgPptQ5DnDYZ2q1yJj794RG/tWEj9HRhCeLCuX\nYR7j8QDrkk0/BUjkOJveY2VZ0jbmvNyStKEXRUkMgt2dXepBkXTyRcZkPmVt7zqz7Y7ZZEpReIb1\ngOlkl0yXDIdDdmfTBLoqKrqmRfTBIj4GvHMQU+jDsk0SQ2+40rRdi48+SWszhUCyO5lBTLyahRu0\nLEu07h26Pp1+uq75KyetS+u5tZ7Vm3ixtofX/Kt/h3n6IT78u7+LzzTjVYVXZwm74CycO7cNyIs2\n8EV/NkVblcuvLTTTKRw2HdE/f+/dtE2LICFclcoxbk6mAruTLYwdc/TINZw48SB79q+wvTOliQ7t\nHX/2ua+gMk2lDWtfeYQXbWzwljd8F09PzvFT/+InmT/+OHfc+SFuvPnl3PeJz/CC629gQ+7hpS94\nIcefeoIzX30CF2DmOtZX1iidY+AlMxeQew5R37Cfc3fczfqVV0DbUX7LK9l6z/s5PN7Hsfd9mL11\nwfqedZ74whe5sjuHeewQ3au+meBaXBRIBN5FQkhDR6UFMcHFU7iukohey6yUAg9CJrlfCpKQxLAg\nLkqECOfjv4RM6e7E8wlFnUfnyZ2JipRKEwy8+tu/gyvbbf7jr76DstxDcAZCMmglSXy/sfTp61Ir\nDhzYYG11jROPP5kCE2AZWJ0QrIFMCUZ1xdMnTvLEE8cJ/aB0NByQK5nQCJkmU1DmOWWZEfEE3zEc\n7ifGQFVXOJeYJj4unI2eoqpYryp2d6dMJtMU46bSxafruiWNcGFhVyoZaHZ2tpeqnbIsMcYsTzQ6\nzwhEhBJMJzNCjKlyzguYTdP7tg++llJhXGpTeZvag7KnXuo8Q4mCEAWbW1s9RiCpkdL3pvs1xjCd\nTnv2uCRG3z/X6aKoMwkUl8w+z/H1rN7EQxSc7DKqfS/iVf/8OrLZKeIj96A+9SG2Q2B3p0umEiFB\nhL9SjUt5Pp5q8UYNMtnNdUysD6SjyDKCM4zHQ06eOUmIGdI1oA2ZXqXZtVx56IVMnj6Bx+O7DovE\nZhKCYWYFU3K2zkz43Dt/i6tGI47d/QX2j0ZcdvTFfOBTn8dqzcte8XIQgWe2t7ni772KNbHKn374\nQ5QGxjPPrvBsx5ZXfvftiCMH0EQK2XF8Z4siDOGNAAAgAElEQVQy01R/9GdcVQ44eNsN6OuvYkvC\n9mbDaOMA9933Za4/M+VEM0Xd9goekxrB+d8/hIhvLaKn1sUY8TbibUBKTbQRJc7rmf865cmCOZLn\nGcEmu/3C8SeFRJQKrGEVQTE3fPXeT/DEZ7/M5yY71HGHPOR08wmSNCzsibqoIAmkZBrrIy+75eVc\n88JDtF2LtQ4hJTZ4VJYR+raDFOlxZD2jpHO+l+hp1serrAwHaOGBjFwnkqIA6qpmPB6ysjJmY2MD\nRGAw2EuMnu3dLeq6YDweI5RmNmtpG4OzSVOC8DgHxiT9+GLAq5SimzmaaYNWGmc7BvUonQZjUqx4\nGwgChE6zmsFoxHR3h84YbJNCleu65uQzp6jrOrkqne018woVRVIJych4ZUyW5TRNk17jPg+WCLP5\njLZt0SrD9TF1dVHge+noYDCgbdslnuFSP/y5v57Vmzgk1940FARnKEZHOPACwaHjDzB/4ARaSToE\nhdIUocNGTZDgfACvU2BEAE2C/HghIPpU0ZEGaISAFIGQKZo2IryGzBKChBiYbJ9ib72G32kJ0jKZ\nN0QVMd5S4ICk1miJGKfoQobbnLO51fCqWw7y2AMPM7OGf/ljP86VG+v88W/+F9TMkJ+b8qE/+wib\nzpFVFRAIGobe89p/+EOIlZpzv/9nvOAVt7L7+NfIJNx37Evc9kP/AL3V8vl3/QHf8J2vQR6Z8+H/\n8E4Ov/A65jvbXHHSIf78T+EV38gj6wewwTP0Kf1dygzvBTZ6VEyCt6zI+r63XOJ045KGmKq7zEPo\nB5wCgQwChcYTEDJiuoa6LKjOzbn7vb/H9NRpMhcQPpLFQCY8iBqvHCpEghCEvo2ikNiY2gP56iov\nu/U2/HzCuNTMJ3OscbiwOEGcV1REDTYk3XpGhrENyEAQmmkzAQJlVSCUJi9SmENdV+zZu8poVBO0\nBeXZu7qHyfYuZV4wrEdIpSkHqV0y2d1mOm8Zj9aZzzfJc00ICWFsOotQBWjF9k4iFAbv6UxDWVZM\nZ7vJyJNJXLBs7WyS5ynIYdbMqOsh9aBmZ2eHlbV1cq2YNy1CCWbNrIdlgbUGJyStTb/r4cNJsbPQ\n67fdnEiBcAItM0xrCR6MT2yhJTrXJQfp9tYEpRTNvFumU8VwaSd/Lq9n9SYeiRgieTtBKY/1GZt6\nhez6b6V99F2Yc1MqqSDm/y97bxqsaVrWef7u7Xmedz958uRWWVkrVWBRLIqAC7YMAgKuPW3jKDNB\naNAxTsdEaPhBp4l2QmfGAGemY2yxjQlHZdB2bG2lQR0UmqWkaEUKSkCoKmqhlqzK9Wzv8qz3Nh/u\n530zS6Rx2oiOyoi8v+TJPOc9+a7Xc9/X9f///nhZ4ESHJpIRQba42DGaHKesHM5aMhF7NgdXtVZI\nw04lkYFe8SCIwkGUKOmJtMxXB9R+RYdLocOAdS4VseBBapyGQ+molWQpIk//1V8y0IZZ2/Jv/u17\necM3fgOX9/YJy5r7P/M5gpJY7yldS5fltJfn3P2ab+PU3S/kwXs/zQtf8208/m//iMMzI0Zn9/i6\nb30VFz79Bc689BWcedO3IM9eZv6lB/mu138HT+0dstetuPO2Wzi451OUTy140Wv+AU/cdpI9pRBi\ngOuWZEKiQz9MlCY5W0XaeQcfaZq2H4ypTQh07GPEiJJgk948GE8uJWp/zn2/8dvknUdVJVmwTKPH\nC0DplMLU99NjFCADojcZxRCIQhBlxg2nT3Lni19MWbUMBxqtFDYKrAt0ncfkg+TyVAqjFUUm8M5y\neDhntb9gVZZpVxoluc4YFBlKSqazCZkpsLYjyzVHd2ZkmSQQU5A0kZOndiBEpnqLvYN9lDSI2DLI\nC0aDMYcHS7IscUYmk1H6PlUK8mhS+s5isdiodLIso6pX1HVN27abU0zbtpuw7aZp0EJg8gJtNM4H\nFovlxmSVWoEmFdoQN8TEzKTdf1m1+D4wuW1bRqMRy3JF159UQghkeU7Ra9Xrut6EKq8JlzHGzWD2\n+rp213O6iOMcpq3wYgQx8a9bKxnu3Mnoxq9jcWHBdKRoCLTBUkSDiAqkwUl41Te/kO/6nu/jY3/2\neT727z+KbA4gpA/B1TtNLwNBjtJwSkeIPYMZcE7QdJEuVDSxJchIjJ7oA0Lr3nIEbfQQBNtB45xn\noSBDErzCZ4YvXtzl4h99gJt3tsBIHj1/HiWSQvr49g6rpubQR974Y/8E30VO3XUnFz7wIU5Kh/qr\nhzh28iR/de8nufXrv4Hq4CLD7TF7n32Iyakdiq0djk2HXFjtcv/9n2HgK26Ml3nsN3+NO1/xKs6/\n/CU8dfIIVuR0wmEkCEQyAvkrF7UYIy6knE9NckXGELASdBdRKZ2axkTMhQMe/NCfUT3yGBPhCRlI\nEbHS40UAqSEmyZ9AJKlnNIBHxADRg1BEobjz7pcwHQ9YLEtm0ymhOqRaVayWJW3niCG1ErqmQeoM\nET1mWHD6xHFu2D7CBauRWU5sHSJEjmxN0SpQFAbvOlo8kZhyJoeavNB0tUtqjlFOkWUgIotVzWy2\nhW37hKYQWMwPKPIC4dIFpW1aFosFtgvUTUvrk3Im9BptKSXL5ZLONhsU7LoYJwBVkgEOh8lpqbXi\ncLFgtaoT9CyC1oboA9EHRoMh2kgmk8mGw9J1HfPDMt0Pm1Razi6p6pqubRkMBqld0nWMhkMWi8VG\nSSOl3Nymruve2Xx9J34tr+d0EW+XS+5/92/x0h/5MQI6UfWip0Gw/YY3c/urXsuFz32eRz79aca+\nAVHiPCgR2Mo0/+Z338O//r338dRTj2PbGhUDsh+irak/LgakAZWP6NoKJVpAo6RIxSZEOtdRdxVe\nWCISkEiVBnH0ZiLnAyFazsXEro5OMJCKVljGAnIl8UJSXrrMyXxITkuhNXlUXNqdc7ktecs/+RFG\nL7oVs6hpPvYJqg99nMNvuIGbp9v86w//MScHM04+cJb5zpTjD5zjwXrOaHSC/ark4b/4JNMGjt14\nBneLJJ8UmPyLVM88werCeV7x0jt46ta7OTspaIVAEeicQ8Qrve+1nFAphev7sQCjlWdlJK12HKta\n7vudP8BcOgQR0DKgRSS0jigNMipklGiRQoxtjAi5HpwFJJooUoSdJXL81A3k4xGrrmY6ndE2LQMk\nIiTdc90kI42ta6KLRNeCF0xu2ObY9lH2Ll/kvvs/y6ppiUIiZeTUyaOcOnWUTAuEzNP91IbZ1gwp\nIluTCUfObPcZkxKlU5Gsmo6ms1gbcZ1PbBHvMCKSFxndsma5WFGWFXmWesuOyHCwTrFPhdu7CIKN\n0iWl9tgN2ncdilzXFSCZzqb4AE3TolVSSXa2SUEUg8mm4K4NWlXZbCLjrt5NR2Ky73uHJMkOd3d3\nN5TK9QVgXbyvzoy9vq7d9Zwu4iJG8sefYtAd0pgJQfYyQZPh7IDHtUR+25u49VtfS+YqtvQA6Nii\n4W1veA2PPnOZ//cDH+XRLzyM8hIhCxx+Y1DJs5zBoKBd7qf+rgchHDJqgkyEPIEEoeicQ2nwMUns\nhJS9prmf+iMSIlZJpI8MomCoBVqmUOdaC7TUZApC1HhhqYks24aFkpzLFC/SQwb3PcT+vZ/Fzc9S\nD1oe+uBf8u8uH2Bj4Na7TnPBNsyWDe/7yAd5wbe8mCIqHn/wQb79Td/OH3zgg7TtIdneAUW2Rbi0\n4LH5HqV17Ow9gTr6Oabf+Z3sbd+IDREf15r61FZaU/eM0anI9mjaS8ZxpAwcfOIzPP3QA2TlnC6T\nDKJK1EQhcNqgvSeq9Bp1waKiJBMmqYEAiIQokm1eRGSRc/r25xGVYKDTqUgCR2ZbeNdjFERSazgX\nsI1NQcdC0tQNzjaMhyO2j+4QIilo2TvOnDnF9pEJo4FhPDmCydQml7WqSm67+RaGk4LLl/cYD4aU\nZc1qlfCzu7u7tNaRac3BfE4+GqJzvdFip4AF3aNeYTBK84y1zrvrOmIQaCO/AhJWVdXGv7D+2vV5\nm86l1kiR603izkb1EwJKmXQS7TqQEq2z/v+84gfIBiadMCMQruCBiyIptPI83zwGuMLEuV7Er+31\nnC7ixIgTNX/+v76Ll/z0P8XpCc55hkTaAFJmYAVg8GLKbudQccZCRe4+dYJ//s53ce8991F0FU5B\n5yIZOWhPDBJtDUcGExaqofGHdBKcMMjoyJVA+AwnJM41bBVD5r5MDGtS/5hNbBkgemZLiEglMSpH\nENFCpN2VECmGTQj2u4YBCmMbVjZymBe0gxH/6vd+i5ve/16MdVitqGJg4QUPzfchzzj87F9xyyCn\n/vOPcWJ7h/nZyzyy3fJf/5+/yAf/t3fxPW/8h3z63o+zf2nFLXeeoFUS6w657cQJRgFWTzzJ4AP3\ncuQfvoGLqqCOESUhxr43HUNqJfVuTykzGucpusjDv/k75M0K4yJogUHhU5scCMgQU0hFj7eNpIg5\nH12Cc21e0pooNE5mvOjrX865/V3G+QRNx3Q6o6orylyQxZDi5/rM0CwrwEactXij8c6ze2mPen/O\nY488iSWpk2SRMZ2MOTKdIZQizwyjyQCjB5t4trJcsD/fZTaecPKGG5jPD9k/OKArA8Wgd4UqGI1G\nSJk4PVXVkhcDVosFREHdLCkKTV03ZJnBubAZFGa5ZjwZsVisKAYD2rajbS1axw2LPAVFFH0wREpV\nGg2GtF2V2ObTlNDjnKNuO8bDDBETHCt18FI+qzAZ5WoPQWQr28aYpHuvygalNXmRWOnrXE+pQPeq\nIi1VQgpcL+LX9HpuF3ESuEnYFZc+9Al23vgGhC5orE2KhxhTpiNJ8+y1wZmWd7/lh/ngx/6UP3zv\nnzAuLUvhyLsBOy/6Bm75obfQaUc+r2Fgaf78P7D3kU8j3JKha8m0STwVpxh940v51te/lk/+i39J\nJVqiS0lDAtVHisWeuR0RQqF1hnCWTAhCdAQiQaYhZxEUWZR4KZhnkcZbFIrLA0nVlZzuCg6tolzN\n0VohMwPCo/KCLMtTYn2IXOgsSuaEywecDx3/6L//Gf76iUd52Y/9ML/63/x3fPeZF/BEfJynnnyS\ndn/O6cEEYT1nF4fsScPk0jPs/cGfIP7R9xJURnCeGNOgTyqDEoK27UFiIu2a3Wf+mvF8RaQFaegU\nqKsMPl8JpO4zOIXoC07sDVkQZUE0Oc+/+8XsLw6ZFkNMrim0pq4rCqUhROqq61nb/XxCpN1tlo3Q\nebqAdm2DMRlSmzQ4FZGt2YzpeJxwtUXC1QqRtO11XWEyiXUtZ26+megDTVUxXyzY2z/gYL9kPl8i\npMagQEBnA8hIWdZUlaVpUrBDxCOkRmlNWZabnbhSqrf3q36A2dH23O51G8Va2+dqymTesTbpv3uc\nwGQyuYrRHgnOU2Q5tU/c8KZrqduGsmrorGU8HjHIcyaTGda2VPUKHywigFIZUV6Bmq2Dmr1Pksx1\n3/76unbXc7yIpzWKlsufvI+bX/vtLFXa7VjVhxDEkKLIvOOELjgz0tyUd/zT33kv7VO7tJlnZDWz\nV30j269/IyJYXICBHrA0mpMnbqaaPc7+MrCUhnI6Iz95M9/+j3+Qfa1orCOPgnmo0SJhVAUywZu4\nYiJaFwoTe/OMNsRe96xtpMwgqsCEyDAqViogRcFF79jOC6Z1w2WpyY2k6FOLcilomkOG2oCHMlrE\ndIirPdoFjk0mVLu7lHGbx89d4OyT57jnqX2G4wIxHjN1nsNVzfnlgkvRUfiMKq44fPwx3EOPYe6+\nmygiQkmi93gXcAI0AqE0rbeYABcf+DwT0eGlQHqQ6tk7t40G/6q4LynThQFAEAg+IlWOE4IXv+wb\nOWwaZlvbKOcIIYVf5JlhXAzxtsbLlLnZtR4tBFlmQMr+JOSJ3rE4PCAXA3b393ExoQQylfriRWEI\nMpAPc0ym2b28T4geo3K2j+0wHI2Z7x+yt3uJg/mCpnMImaF0Rucd1bLp20ueprEc7C8QXMnmVDpD\nm5yLu/ubQWGWZQwGg6Szl5rhcMxyucKYrDfhpCAO5zxZll81f3Ab9cq69TGdTjdFPwT6lovDedfr\nvMVGrZNnGUpC01T4YJPT0zsGg8GGse+D65OHzOb1WocvX6cYXtvr71TEDw8Pedvb3sYXv/hFhBC8\n+93v5o477uAHf/AHefLJJ7nlllv4vd/7Pba2tgB4xzvewW/8xm+glOKXfumXeP3rX//3uIuBVgdc\n7PjLX/sNGqmQPiKcBGtBppzIKBVfzCwPf/ID/Mtf+7/5xJ/+BzLjyFxESMOFz/w15z/zKIKAFwHp\nNCFXDO+4na2dCQflLsorpsUW7aLiL377dxjnI44YQWgrhkLRQW+gkSlVvGdye++I0SJExAuNDxET\nNT6atCkNFT5Gau/xQuGjxCLo6PDWU6icTtl0onABX3cooWiVwmuFDCnI4Ju/5zu48/tfzUTm/Ob/\n8D9hn3mG+a/+Ni/4llfy5fu/wLHpNntYLpRzphciF+Z7ZKpgHgKHJkN0kXm01Epx8603crFtEUoT\nXUhQKinwCuhCUu1Ez8gJQtPgiViRJJhpl55eHSH+Fh5L8P1FLrHcRYx4JDZEzrzgeVR121tUIqPp\nOKXMNCuKYoita3LhadoO69ZZkEnJssYHFMWAO++8g61csdyrE9617+2evuEYN505xWigyadjplsz\ntNRIGTEm49ixY3Sd5YEHHqapGqTQ7B8sqDsLRFrXUpY1deOw1jGdTjDG0NQOLcH5dNFuyoYQK1Zl\nsrcnS/uVfrb3gbbtWCyWjEcTmrrFupatra1NfJuQKZEpKURgPB5TV8tNsPE6ys1oQ1PXfRpQRWM7\nqrIjRsFwWDAY5CnCLThsa/tQ5jFVVabC7xxSKqRaG7+eLWO8XsKv7fV3KuI//uM/zpve9CZ+//d/\nH+ccZVny8z//87zuda/jp37qp/iFX/gF3vnOd/LOd76TBx54gN/93d/lgQce4JlnnuG1r30tDz/8\n8LOGPP+/7+SyxU80w/OXkIUiC9BKiYweQSQKRTEa85IXvwSx2OWX/6//h0Fr0LrEyozSKIadJ8gV\nkGGkI8ga0Ug+96XPYLxOe0bhKS88BgSccHg0+1IhRoJ4oNCZYk34i9H3UK21Z6gDEXAAUSB0QZ6N\nGGY5T8+fYNR5pmtTkAmooKmxjExODHCgJAUSH3z6sGkwAfCBQoAqNM/75q8nCzk+au7+xlfy5L+/\nF/voBT5+7r2Uq5qd0QxsBKm5eGkPxgYbBS5KrDSIkcSuOmLI2R0DS4vrmSkpUEJQOUeucpxtUUag\nXGRsJZlIPXCAIEH1UfXPbqeI1P4S66i1mCBmIiKF5OjJU2wdP0ouDfP9OePBEIxEiEiuFZ1tyZUG\n72hdbxEXIQUvKIEZDOmqjsJrBrnB2ZaqrinrGtHHob3g657HmTOnGGaBbDpiNM6RKISc0jQd589f\n4KEHH6GNMB1N6RrL5d0DXIiMxhlaG0yWc+nSgkhKhs9Nkv0tD+dEoTac8LZtMVpvHn9SnKTwY+fT\n95u6JTN5CmWWiWeeZVmf+pNR9WHNQgjqJqUiSSlp2xZI+u7MFAjSbjz0LZHBYIj3qdedZzlEj4hi\nozUfDDK8z2hb1/fqr4DMjDFXWjUhfEUz7Pq6ttbXrKzz+Zx7772XH/3RHwXSEWw2m/GHf/iHvPWt\nbwXgrW99K+973/sAeP/7388P/dAPYYzhlltu4XnPex6f+tSn/pPvYIyRpohI39Gq3j0YItpFIgHh\nPNHDqTvu5I//3Xv41d/6Ay49+gRBlbieC5HZmKLLoiDSYWPEo7HKYPywB0IlNYzoU8K0M8ROoZuA\nqmuCatMHBSAki7pPknIEEilMmvLFgFCW2q7oItTeIZxMrPIYaIGqDRy4lq5pKLIIwqK1IQgBUeFG\nQ57/8pdTeos3Cus8wyB58jOfZ7m/R3nuPPf86YdoEXShoSlrCiVZlAesXMtkdgw5LNiSOUFEBlJR\n+EjZBapouPN734haBLQPZL5DB0eOJIuCKYraNtgQEC7S5eC7mlaADAGrAiYYYkg66vQapQBUIUDI\nSMQi+x14EAGLQGQFN9x+G64NdI3l5LEdlosFXdMhQkSaEVEY9vb3kF4gvYfg8N4ShKTuIl3dpbZJ\niFy8cJmqrrm0v8/BqkbIiAyeI3lOZiSzo1sc2zlB03oOLx9w4exFHn/4LJ/97JeYLx2LxYqD+ZIL\nu3usqmTvB0FZNiznZcL4BoESGW1jWcxXCJWGhE3ToE3OZOsIeZ6RVKtJobJaVnQ2UNU1B8sV0SiW\n9YrZ1oQsM5RNTdk2HBzOU+ScD1RlSbVa4axlPB4D9Jb4tOvf27/M/mJO2dR0PjAcTdAERrlmPDBI\nJZBa431gPB73JqAOITTRB5QwdLWnaxyZztHSED0oZSjL+rpj8xpfX3Mn/vjjj3Ps2DF+5Ed+hM99\n7nO87GUv4xd/8Re5ePEiJ06cAODEiRNcvHgRgHPnzvFN3/RNm9vfeOONPPPMM3+/exnX/JPUukhn\n0A7jYjKCqMDzX3QXdd3w3t//YwozRglPT3Tq0Zv97xKm7wGmaK8QLUSVdiNRXvm52CGkRMaketCq\n6KV4KZ4r8fzYDDVjECip0zAzNjhadpdPo2XEKI2LkUwoGusx2tDGjpFJ8CQbAk2MFEJQacF/9d/+\nKDYXvPL7vpN/9TP/MzsIKtvx+T/6GH/5/o+QZZpT+RjhHI2MKceSmGSB3nN+7zJjpRkoxYqI9AIl\nFfO6xsshlz73AN0jz2CUQYiAkRKBwnqHyiTTPE8tISnIlWI/z3G+JZ1A+qfxqj7qla+vhEesB5lS\nZgQid73kpVy6fJnBcEg2GNI620OaHHudRQtN13Y0ZcOFsmM20Yn34tOOXEpJiOBDxDrHqmkY5onb\n4mJIZh4pyXXKscwLyWz7JKdO38hhtkfZdGR5x3Qy4tLuPrZ1qIni2M42sh8orspVsv9nBmMUSqX4\ntcuXd7HW9mqVtO9xzqFVCopYVUtmkynWWqqqgl6CGkJqSw3ypMfO84LFYoHSmizLWSyWeNexWi6Z\nTWdkWUZZlr2CJYWAO2txPm7knt46ZJaRDQZA2lSt2TZaJzhXnufpeSPJGeu6Yzgc4oMlBIeUoLWk\nbRuMUddb4tf4+ppF3DnH/fffzy//8i/z8pe/nJ/4iZ/gne9857N+5mtpTf+27/3sz/7s5utXv/rV\nvPrVr/4qt01a7BACQvrET/YiTd9jxEvF1s6Ef/GO/5E3/+Mf4KkvP8WgGNB1iZ/Bhlad/lTR9tyO\n9Ob1eKRMgCRJYnQIkXqsACFGjBE0K4vUqZikaLjUWumtMklWqHOQGdYuCKFFKkGIqT/sPLRC40Ik\nRKi7jtl4mC4EQhKkxIWQ2Bl4ismMZdfho8QpyUKlsIOh1nSdTUW/75uOiwFaCUKUaJPjEYS6IghJ\naTvKkHNoHSEYvM6oDhaIw4o610kWKK6AnFSEJiSVReUDlQ8bG3d6Sp79Wv7NrM316534KwofYHb8\nBEFJRpMhMYj+GiqoqwqpFFFqmlXN5YsX2L94gduPn2I8HG+Ki3MOFz3ZZMYwz5AKmqam1GBdwMUA\nErQS5IVmb/cy5WrBxUtLxrMxs9mMneMnUarAs8tRBEdIqNcsy2i7mvl8jlIGrQVRJi/AfH6IFCaZ\ndTr/LGphCIHVarUpoCl4OOVlWp/QBEVRpD+N2RipsixnVVZokQp9ng+IIfXUpRS0XcoAbdpkDgph\nDRpT2L5HrhAIGXsEwdpIZEkjfknTJKVMnie6odYa711SPWmJ9Q7Xuo0W/avtw++55x7uueeer/Ld\n6+u5sr5mEb/xxhu58cYbefnLXw7AD/zAD/COd7yDkydPcuHCBU6ePMn58+c5fvw4AKdPn+bs2bOb\n2z/99NOcPn36K37v1UX8a611AEHEI4RBaYkIGUTP8VtO8X/84v/O5z/+Uf7szz7JcFjguxZ1Fa2P\n3mUJSVkRgiTGfkce03FdKt3vMpPOOXV8PVJInA0UxZAuJAa3EKKPEmPDUQFApAuBMbp349GzuiHT\nGU3XEUUk+AYhNEqk9PQU/AsIiYqSsw88wote8mI++aGPMTYFTduiXMQqhVOCzgW0VlTOo3WWQpB9\n6j1HITk4nHPmxHGs7Vh2NctMc6GpyYstOlFgOzB4Omcx7grRW0iJzzN8cNiQLm5KZAyHQ5arr83Y\nWJuGNksqojTc/oK7uHiwhxaSxWJF9J4iNxw9ss3lS5ew3rN39hyrxQLtHU1T4v0A75PTsutqlNR0\nXYPShq3ZjO3JmEmRcdEvaK0jFmC0YTgcJGyszmiqlku7u9RVizFZGhIOC1rvaBrHqqqBtJs9OFiC\nT/OOqkrqj8Fg2Mscw6YPvmaPBO82Q8M19XFd3LXWWJduJ5Wi7Tq8SIPLw/0D2q5DZql4266DIIgh\n4Ho0bZ7nhNhRN23KEq1Tf3z9u5WQ+GA36pKyLAHIihyl0klECIFIc//EuokRQcC1aaiZmR6TK/VX\n3YD9zc3Vz/3cz33N98D19Z9/fc0ifvLkSc6cOcPDDz/MnXfeyYc//GFe+MIX8sIXvpD3vOc9/PRP\n/zTvec97+P7v/34Avvd7v5cf/uEf5id/8id55plneOSRR3jFK17xn3wHQ4goqYn4ZEqJfYgvCjLB\nG7/njbz2v/gHfPerX4dCY20H2L7Pl+BLaRee3qjWRyAjn24TncdkEpxACoHsWdohemhrrEtHWCED\nRil8M09tAq4Mg64a6WFthw8NIbQI4fHBo6Sk84HQDwKFjPgYyKXZDAC9D2RKE70DH7jvo/dy/0c/\nTh5k0sIjyUh8cNt0+N6Ugw9p190zT6xUuMUhx0Yjnj48wNYdTZExF4JWapx1yFwjokLGmABjMu2k\nlZS4CMJ3KUIsXTmxvqWYDJgvDtOFUdDTDPvHLcSz/kzPswSRFDhHThxnVVW0dUvM0kCtrFbMjpzk\n3Pnz5KrgyYceRPoW4Tti8GgZIYZEke7zXTYAACAASURBVFytkMoQSW2Ukcg4vnOUU0cnNMslh/MS\niyV6zdZ0xngwoG0tnQ1IlaNVxrgfWAYi89WKy3t7DAYjRqMR+wcHWOdx3jHMR9i2o7MtEs1wMMTb\nFfPVCqMTelZJgdYZi70lh4tl4n63ltCHVXfW4TsLIhX8pm0hBCrbJddnD8BSMoVpZMWAzBhCcBit\nESLSdpaDwznWecq6xlvP9pEjZEWRwsKNYjwYYK0n+D6Nqb96+t64lf4PnSLd/PqzI1FCkvdadaW/\negG/vq6d9XdSp7zrXe/iLW95C13Xcfvtt/Pud78b7z1vfvOb+fVf//WNxBDgrrvu4s1vfjN33XUX\nWmt+5Vd+5e/1RlFKp2EjAh/TMDMK0Ggq33LjDaf56Ec+wee+8CiFTmTBGH1SiMhUwoVIe2vnHCoT\nRBc4deNJzj30IK5NNmWL7Ad0qUQrEr3PhYAChItkJk87M+FJAcxywwWJ60GrChvGs+gZIUIKbEwX\nBIlMdm0jaKwjk2CUxsbIwBiC7ShIO3LZF3kJeBGpfUCFgJAS55NWemAULkaUGfC0b7hJFLTesvSe\nqA0Vkt22ZTrcoqw76q4kyjR4jD4xrpWUSDKCD7hor4QY9K2Del6jlUmuVJEYHes0n2e9tkKQ+jOK\nIBRRa25/wfNxnSNYRxNhkGXsHNshujSg/NKDX0T5DhcaYuhQpBORjBC8AyRdZ8kyiZKJ5d1UDe3Q\nsHt5l8eeeAZ0REXB7bfcyonjx8nzAah0uslVQWlbynJFjIKmtRT5AEJguVgmGeHWjDwr2NvfQxcZ\nE20S/9sFsiznyJZJ9EGZAh1iTG2IrutwvQHHiiTTjH34tFIK27X4NS9FacqqRKorALZBkZQq8/mc\n2WyWlCJCUJYV3kNVJ275cFiAEuQmFV8bI0MlaJYNXZcK9FpnvqorQNB1LsHNYjpFCJlaPkWW+uU+\nBsLaoXsdKn5Nr79TEX/JS17Cfffd9xX//uEPf/hv/fm3v/3tvP3tb//73TPSLjcdV5PJIkWBBaSQ\neOnwUfC2t/0YL37+3TgHzrf98NMTQkqpWUvPpJTk+RBLjVdQNxUEhyFiJRBSoZdSJlSqSqoXLSUi\nJpiTjBlZXtB0835AlAakkHZdIdIjV3vHo0wxb+sPyZXEeKhsy0APqV1AYRnmA1rryYVGxohMGc94\n+rrYP/5OgCKiYkAJwXQ2w9YNhyGQeTg53uLx+hIERZVrdn2gChK3apgdPUouVT8ITaaksAZfqYjv\nLErKNB8wgs4lhrXr+6rWuo007atdmNdtBYhkxiCIFIOcEDyFLji6fQRbWcrDBY89/AC5jjjfQN+m\nElHhekNM8Elup0UiKtrYpcdVrZjPEylx1bZInYHzjPOC4XCYzDFtQ9N2CKFYNY75YklV1SnuLATG\ngwKtDUobpNB0nce6iMfRVMmdK4VEGQ3BkY8GCBFxNlBVJau6SUEMAlT/unZtt9F7VVVqpw2HQ2KM\nlGXJkekRDpeHTCYjpsMRu7u7lLXqQygkELl06RJCauq2Q2vNdDpGKfr3ccombRvPgZ3Ttl3fx9fp\nPd9fkIUQyBAwRqFVn9wj0oWnapuNLt15R6av68Sv9fWcdmwKUr9yrYpYa5Kv1A/JPR/7OHuX99ka\nFJQhDTITOEhcUaGI9Ma2NvUfEZpF42h1niiEvcJESEXnLEqnqDIpVNrN9L/HRzi6tcN84Smrg03B\nEkIQYp9RueaG9CyPNUkkPSDZBxKn5PnKWvKsoAmBYDtEr5JJuZbJqRhFJIaYYtOCRyPQUWL6Yezl\nvX20yjgnW+40M75U7qPRtEpzMUYOI3RIopScu3wBIVXCwgr6+5mIgVcPp9eAMKBPr/F9/vCzd23P\nTlGSm1NPuoAlSp5SkvPnzxNj5KbTp1nuH/Dkl5+kXa3IRSDYKqFcRS9XFJGuD0BIFxmxMdikjaUj\nWoeQmrJaUDdpziBFyuXc27tMEBInJEIpnGupm/RYiqLAh4g2hq2tMc4HyrLi8OAAozOUSLOT8WRK\n27S0jaVtWobDQU8MFMyXe5RNimdLvfBAQNH0lEERoe4Z42VZMhwON2EQVbVkNBpudvExRgaDrIdp\nBYRQ2Ahd1WC07gembZrzeE/sd81VVZHliiwvCCGwrMp+qB7T6Sp4ijxDa00MSdliXVKtmP6+rHv5\n4TqI9ppfz+kijhA9xW39V9Efsz1CC2bDGf/sn/1zQnQ0bYkIAbFRvq8LTti4CiFJuUP0HD26jVyu\nkvNQKYJPcKU8M1jbgNCIGFEiFRZEJCCp2wThX0dzrQu57I0TV/7tips5isBmixbT8MwLKNuOcTZM\n90EISsATCQQyLckFqJhcjyEEMm3IRSTYgAsQM0MTIkFIBiLnoK5YGBh4xaFQrGTCm2Z5xsLaFMgg\n++GjSCYVSeidfK4nEvb3X6aBpxeBaAOd73fKvZJlfTq42jQi+q+VUkilmE4n/deSm246Q7Va8dhD\nj2K7ClyJiO4qy3e62MYQ8NHhfbqw0g/znA2YXJEphSCFEhfFCGsd0aQRQTEcsFgsMMWQqDIgWf9H\nw5ysU1jvEyaYtFM3JoUnJzOMYDqcUlUNZVljjMH7QF035EVG07Q0dUdZ1azKqn8eYo95TSqhyXhC\nRKHyDK0VWZZIg8k6H9g+OsX6SFXVdA4mkynOO0LwWOupqpq2Te0soTT1aoE2AiE0QnjKcpX040Sc\nlThXIWWKIazrmizXSERS03iHwOJ6GmSWZ+l1C2meISD15/UazXx9XavruV3EIxANMdQpXKA/Fkah\nwUXq1ZKqXJJpjXW905FN76FXSqy1JmnpGOmM4uD8edrlPkGkQGBC+kC6CCJEOu1TKrtIu2uJQMUh\nvruMVIrtnVPsXayJIuFDY/DQNYjgcT45DJNdPBLiVVmfpMGg1BnOByY7N3Bw8QIGkCKAMnTCM5US\n0XRkUjDICkTnidbhpUipNIOMJkacgGgtQgpWedKj7ynHXugoXUaFIjMa31Y4odMwV0u8q5FC4ANI\nrYg+kCuNd13arQuJkBoRAlFJfHQoMqKXRFqENleKd1+IY0whFwkhq8kGI2KQHN06yVOPPcnlc89g\n5BJvW6SEQEgDibgO742IKCGAF9A6SwyJuqeVoO1aptNjHJsMmV++xIOPnKUNDTEoBrnh1IkZMcuw\nwHKxRBkDSqJwjCcTiB7nO8aDIcu6QShJVTYMixHeR+qyIQboGkcMnsPDfcaTEcHHZPYRiq5tUFKA\nUYiQLlhlUyNFkpkKkR4/FgY6w0aLCiRyoXeUqxKCYDad4YNDBMHF3UsYU3D+wkW8jeR5Rh1XKdM0\nKppl0o4XWY7zHqN1Ams5z3AwRImAdw1RDVB5RlAKGZPtX0rFbDaj7eo+6ELhfbLmZ1nWK76uN1Su\n5fXcLuKsB2dpl3Y1LS+GgFYGH2PimIivtA9fHfa7+VpAlILg+4DgKNHCb5CqCIgyooNGKoUNpDYI\nkOWG73zd63j/+z7IN7/iZfzFJz7P4bKPw4qJQ5GZAW3bUtcVUqbdmhCBdRtIrnfC0fDKV76SQmdo\nZajKJcv5Icp6BoUmdJatnjYXQyAjUCiFUxKCpnGRFrAkul+QisO2QQ4GVC5QYjhoA4OtLb77+76L\nLFfsLnepljVt64gO2rbBBUfTdgQX0UKxqlf4QC+X83Rti2stWoNtoWsCIfztu7eU25ko7F5I8nzE\nE48+yXK5YHmwD6Gjc0mqmKLM/vbXPNH20vPZtTahWkNAKYHSkulshrcBoc8TRLqQbE1mnDl9ip2d\nY5RlRYiSKBVRBLrWsaxWSK3QSqTQZWFYHKxompa27pItXvRZnjH1n43JESiWy5LVqoIoN9Q/rTV1\nWxPasAFYWWsTITAGmrrXdCvFYrUkz3NcdAipMFpzMD9MiIXeQLZcLhPcS6WZyng8JssyQFBXqQAX\nwwHDwYCmbek6i5CKpmmYjoYUxQCjk2zWOYcWgrxISIe2bfGhH1R76Lp0YtQmPc7r69pez/kino7n\nmujsVa2SlK+jEPheKoWQePyzbveV8re+iMdI21oIIkn0REFknWgOQiULt/cNuZHcfvstvOCu57Oz\nc5Q3fMcr+dM//GAqBra5QjFE4Al0NiCkZra13QcBLAk9YY8IMSqOHdvh5pvuRJsBKEU2O0LIC8az\nHRZ7++xXcwYomhgwIjKTgpEEYkrQKYxGKYFwDiMlTgTaEHDGMLeeJsJhF2gi3HHLGc6dewxnV0RV\n0HUNhSkYT6Yc+hUmODKp0KqgbSwqn2K0pmtKOtvRDSTCj5htjSkXLWefvExqUzz7OU5Pru8DInJu\nuu0OuiZw8ewFvC8hNBBqpMyI0W8kl8Sv3AWmQbSiqurNMDsNPQO2qdnf36NrI48/cy6RFWXk+NFt\nZqMxg8EAbQxq1dB5h4+OohjQ2A6lU9GrqorYJVqhtSnByOQZ3oZkpKpbui61dObzBSFEgk/vI9Mb\nd4xJJ5HFYpFs7yohb+s27eZ1ln7O9jTBRBL0FMWAsiwJPjFMtJG0q4oQPIMix3WW8XhIlunNe18V\nRU9ADMgIVVkiRMrlzLLU6onOJcZMnnreddts+CproJZzbjMsjvg+ONt/xfN/fV1b6zlfxIUQxNCb\ndWKyYIcYN7bmdU/2b45n/uYR8eohnJEKrSVWgY2R2Pe3jRIMBzknTxzjphtnfN0dt+K7BbfdfIyj\nR7dYHjbcfKJABseZW27lyPYjLJ+aI/rbx7iOIhNY6/HBMRiMibFPkQ/pZxbzhi984a8J/cA1mXRA\nCYnykag0jWvJAkjnqLVkJ89pY2BMpCYQG0uW59gQqGwgmIxOgEeyqEpaHzEmZ/fieYb5Dk19yBNP\nVdxw6ihx3PHlRx7kyGyLfFBw9vFnMPmQECWVbdk5MqWtV0xmU3b399FiyP7uRYTMaF1STbBW31x1\noQxR0gnF8dOn0VnOk48+Bq5FhBpim4a0mzShK8qeZ71upAFr23RJstcPnYHkpoyevCiobcOqtT0u\nIXBy5yiL5ZxgUo9Y6wyTa6pqRYiOwhiCFBR5jteaKBR0ASHy3mXpkkJJJGRr29pNtJrWikW16N87\niZHT1F1qQ0nVtyoCW0eOEpEcruZMjhzh8PCQ2WyG1prOOWKE3d1dlDRIrfAxYut2Y6k3UjIYJyph\nnme0bUe5qtBaMxqNcM6xbFaMigGNS8Ar5ywm0+gsBWUYk5Rcg/GYtu0wOuuRBaGXjnabWLfU+nHX\nJYbX+HrOF3FIBDkXPBtqngDf28CllDjv/s4TdhmSWb5cLRkUktvvuJXXvOaVfPurvpW77ryNkzvb\nZErgiTRtQ5RQtzVlXXJwYZ/SNzivGOc5Xb1KH4zYK1RINv5N+KxMR3ex7huLnrNCeizEZENKxT2k\n1kBUWJFYKJ1zjLMBC9fR1A2FksyUQQtFpjUxBILStEQckVoI9usVpbMEYRBSs7u74vLuHsZEaqc5\nfGSfosiQwnD+0jkGRU5w4MuKLkSKYU5ZO7yVtLsVjdUI25HlBqU1Sl350P/NC6VXmjO33kprA+fP\nPk10LSGuULheobMm/v3HEQ1rl63fhDhfGaoGb5kfHrKoAlXTJlloiGlAGTyLxYIszxmPNUYaju8c\no6wbqrbBti1KaSQKKx0xdEhS8nznPF3TEvz6pNZSFDnWtn0WZUIPGJmKZCD2LTOJUoJikIK2F8sl\nrXO0u7tMp1NWqxUhhDQM7xk1re3IRIYPAd2z2Z215AODloLoPbZrkEiGgwGh56I0TYOWCtdZYvRo\nYxgMhxRGYpuaPBvS2K7H4fp0wfKp3aT6AeY6EMJ73yNq5X/k1bi+roX1nC7iEXBAoQYEHESPkhEj\nUhtEab3ZrUUCQSQ53ybwt9/VRSmTQSMIrFJ8/Ytv4eHHvsh7/+j93HDmGFvFNoUpelNRoHMNtW2o\nfWJZNM7TAWVUBOdovU2MapUn2RvJVCGi3JwIrs459CE5NRPHP4VapGCguPY3AuAJWJHMRkKAV5FD\n15BLQ1AZ82rFnrIYrdExkCtFLqFB0HSOhWvpYkRqjZKSFo3JBhTZjK7uiKEkxgFtvQZmqcRnkZLT\nd7+MbnID2XbG/kc+gvMrYlRIqVHRM5zMsM719VfiARNSkLQXgiAUd770BTxzYUm5WMFqD+VbpPBE\nlV4bwtoA1begesNQEGsFjyCQvm/7sAq1HhQimE4mTKdDZrMZB9UchycqyI1hazYg1wqZFzjbZ11G\ngVJZUoc4jwstxggsAV+nPnbddFjvaTtL7FraJtA1HaNc9xp/QVfWqAAKicggVxplBc51CbHgctrW\n03QLFqsSGUFmhtVqxapOcWs6MxQ6R6jINB/TtS3eBarW4TrH9mybYB1RBHyMaJn1rkqFbTsO5/s4\n52mbLj0fEnzXMcgycJFgoelNblpIsjzHeZtCPyJ4F3tGS4bM5Sa4ObjA9Y34tb2e00VcEBHeMZoF\n2qqE6IhBECKMaBhkI/IiZz6viDGQ9zbiyWzMeDyjqkv25wcJONXvYsrO8tpveRn/y8/8BO3lXe57\n5AE+ff9nGeZDhEjo1GKU4XzLcDAiBMdsPCTXkixk3PD8mxjnivFsjO6DkEMIhF6iJ2MyZsTeLk+M\nKUlBrDUyaZJkVdrxyas+QNqnlyPpw9NuLwjovCAvBsQiMC8XDEUKKNbOIfDE2NE4jwWQGm2y5FbM\nc1znKOuSTGlsVCgpsUL2GnxBMRxy7PTtyMkO80WNM1NOftvrefLeP0E1h0SxwgbJ3sVVojpKjRAa\nL5KLVCkFUvG8O+/gySf3GRWKxeoiipooAlJkiKg3nJoufiUBMcY0UBa9pBSSjJQQERKMUtRdg+sD\njM8+9QxfeuI8NgSiVMwmU44f3SbLNNkw9ZxXqwXj8ZTlMoHLhsNh4ns3LWgNIg3EN2qS4JFSk2UR\nJQ0hOpzz+OZKi0JKCUokXsmqYrWqqaoK7z2nTt/AYnU5tfdcQhbv7+0hpGR7e7tvtSVOeNWHIzdN\nk6LcAK0kPgi6vrUihKCqqk1SvRCCpq77gatBRE8UAu8cWZan00PTMOr76s6mU0cMEal08gZISdMk\nk9IadbtYLNLzf31ds+s5XcRHRc5/+c0vYigiWt3C4vCQrFdztLRkWUHTtFy4IBkMCqZbWwwGQ/b2\n9ghRMDp+AsQJQLJYlcQQMVnOQ3/2UR7/1F8gZI7JNflwxGjnKMdO7iByhRSKRRvZ2z3H3vyA2daI\nPNPoqLnxxhlV17C/d0iWF0QkUSZsqoge1/fHpZB417cBSDpvsfYNRciC6P/eF7QQscpf6TTEtEPX\nsSc4ikDXJcWDi57oI40PDIoCGwzkGbnKrqgysOgsp2tWCJk4LgNaUktagFBJDmlXjG68hYf+6lNo\nIVieP8PwW+5GFkeJzSrtiMVV9MaokEIiUT1cSXHk6AnOntvHh8ju/jmUb4nKEFQkoEDm5MbQ1Ac9\nKZJ0cevhTCnKzW/aNGmAFza7yOA9MkKeG6KPeB+YLxd9Uypy8tixniViCX2Rkv6KdG5RrlitVkiZ\nhoEhJIld17n+sdD/P+BsKuZr9+7aDzAcDtPAMCTlkbUOISSDYozJknlmZ2eHS5d2mS+W+OWSkydP\n9iexgLWOTCl8l4xCUQqGRYHwnjzThOBApIGuVoqyrHDWoZREaU3XdckU5ANFkeN8wJFUMsvlktxk\nTPJss6GQ6wu1TP1v3wO5dCZxIdnunXO9ROD6upbXc7qIi+ixe0/x5bLilptuQmeeLBccHuyS5Tlf\nfuJJbrvtNk4dP4a1HRfOPsnWkW2atuP48eMIYHl4QNc6rAtsHzuO9BFCx9kvPcpoeIStI1vslxd5\n2n8pGUYmI2wEM9nmpa98OS94xcu4/etu4+jxbar5koPLj5ObjO3RgMx7ZEwfUhn7otzvILWSaNeh\nlST6NvGijSHXOZPJBGEthcmQSjEaDlkczhnkiqzXXydGhmd0ZIq1Cf5U1SNi9NR1Q1m3ybVY1iw7\nkCiCC3hACg3RYWRARgcxBctZkfIbBUAIRARSaXYvXKCIFh1hu32M/DH4hjvO8OCnv4yRhuAt0dqe\nDGlTopIwqBCIUbA89zS3P//5PPTQ58iCxShFDJogweH5/9o7tyC7ymrf/+Z9znXvXn1Nd0KHkBA7\nQBKNUnW2p0QBOXUUlAIpoQoptXzx4ZQ+eHtzPwhBywex9MXCKsoH0SdFSxAoRDhiGcvAcWv2FjY2\n0kn6ku5et3mf35zfefhWlrI97O0ladLH+atKpXp2rzXWXJexvjm+Mf7/eq3CzK5ZfvevIVLEo9Wl\nGK7AGW5Mq/rs0EIsz7ENk3woGEUhCQZ9sqYLhUaBrpI8BVNjTXKR0ekP8AolZGbaFmmaYRhqJN3z\nqti2A1GCYVoE/oBBPyBJBFmqhm2yTCCyYcdHEpILVeI5byrsui5BFBGGMbblYlkaqVTdLVEUsdXt\nIYRKxLbnEsQRuRA4liqNFEhMQyVpVU4qqFaqWKaOaegUmgSpnpssFcMpTQDVTqukbm1EnmFoJsWw\n3p3nOXEe02w2STNlcKGMmUEWfywvnq/1n99UFplqDPiTEeiSHcglncRBx21MUM0GrJ7Zol7zKJKE\nOMioNcZxvTqdbkAYBkxOtdk1vYs4zYiDmPW1LUSeMTU5ietCInKWlleoOC6zuyaZmruMwSDhldMr\ntMYn0QyDQoNTL56mF4TYlsezz5zAMKFasxkfa3Dz//wf7N03xrils/ziC+ydaXFudZlelEKRU/Ms\n9kzO0KxVqNoWrYpD1bXxhY9IUgzdIE8EURiht2wMw6TT6UA0YPdUkyCN6XU2aI21mGo3KfKULBmA\nbqK7OtLxlHVXVsF2K6SioNvtk0rJWKtNkuaEqWC91yOOTDTLIs4ydE1VdKpOTNVzsDQYb7VAGohM\n0G4I7KmaKgH0N5iUARt+h+sWp7ENjzjLSbOE2lDm1fdDEnS0XODaDnEmiKIzvGXXBIZjgqETBAN0\nLCzLpjHRwrAtmvsPcur0y0RRNHqFR50R2p9chMihWMF5vWspsUwdIRLk0FlHlQU0dB1mpiawLAs/\nzUi6A5UgDZ1GvYVh5ERZRJZmGLpFLjUSkZHHgiwrkIUadIp85YOqaYYqMZBj6GpP4PyXju/7pKKg\nyDUKQz3uJIlxHIcwCsmyjCTJcC2HvFD675ZpEmcpIknRipxatUrFUWP0uciwTH04vq+E0Hrd7kj2\nNk1TXNcd9osrDfXz4/KgrvZ63Z6S3rUttGGpTt3OIc+LoYRvOpTnNRGFIE2Vk5TruqSpeM0wXMnO\n45JO4lIWxIM+taqGZtbY6vXJRcLumWkSv89lu6fICshlzh+Wz1KtuTSqVfbsuYylV04TJAlurU40\n6NOs1zh88HLWVrc4vXyGSqPKWLvBeLNCtz/g/yydxTYK9sxMs9Xv0xo3ODA+y2S7hZQ51VqNcy/9\nC0u/TDgwM86/njiBpelcd9VuLEtNRdY8l9iPyYTAsA0wYBB3cW2XQssoihzLs/DqHnma0u32mWiN\ngQ5JElK1XJq7ZgGJyJQkaiElFddS1YcCcr2gUqlz5vQ6SZbhVTzMTHLm7ApRlmJaBq6mpgPHzIgD\nB2dw7aGEbJFh2+awda5CHGUEQUaexIRxQbXqUq+M0QnP4jkmdsUhjnsEfopjG+SpEgErREKeiqHw\nkoZOhi5jbMcaljwyHFdSrzq41QaJKOhvrtK0Tf77wgyFZtDLBCsbPXpBTCcdoGEoTXRdwzDBNUFq\nBmaRK4lfTaNq2UBOEGeksiDToIJOmsT4IsO2lHpimghkBmcHa6qf3lZv8yKHLBsOvQyTtGXZ6iqm\nWiERAtOwRoqAxbB27XkeqcgQmiQK+2RpShT6QwOGWLntGAa61LFtG4FAk/rINLkoCmzPRaKEsZTZ\ns0u16g2Hv3Kk1MmKAsOwiGOlq2KaJpZlkkuhEnkskZlUeuK5IBUZeaY0zS3HJs5Ue+T5lbZj2RRp\nRr3qkgqBbmoYmYnrWsp7M0tJk0ipGZbsWC7pJF4UBZpp0PA8kjRmrGrgtXZxem0d4UuEZqBpEtvQ\n2DXRZr0Xkpg5GiGX750hSVJ6nT6aEJiaxcraFr1Bn2azycrqOt1exMrGBpPNJuPNKiLo4WoZ/3Tk\nIA1PSYnKaEAqBGQxq2FKFmWILGZmbIJ63aHW8Oj1eliGy+ZmB6RJo9EkzQRhf4DpKFPcIAjwPE+N\nT7susUyYmZ0gilPObW5QyILaRB1dV/6KjUaL/kBpn/QHPv5gQLs9gW5YrK6sKblWXaNWr7KyskUu\nCuoVj87GGoZuMz/msHt2jCQaIITA9TwKw6bb7Q6nC5W0KqhSgudViOOUbj/AskwcV01LRlGCZpiY\nptISSdKQME6o1dSle57FaBrMtMcZRClBMMAyTTyvipAFp0//gSgrVHzNJg4LuoHPRhgTiIICDV1T\n3TZN12S2PUa71WIQ5Wz11DCVqRlkmWop1QqdIE7IpQZFge1amIZOGCZQ8cjySOmsWDZCpGo6URjq\nnNOcJMnQNAPDgGq1RpbldDs9kjgZGoPEwzLKcCrYNAmjiCRNSHMxWpVDQa/XU+2HGsRRRByrUlGh\nqWngwUCZFtu2PTJwOF/a0CXEUYwsrGH7YIJlWQghSNN4NBXqekqFsMhzXMclGzr+ZEIQJ/FIeCyN\nE3JDDE1JLPTh5jq6pmze8hzHNJGa+jlKh45EQryRH/GSC8AlncQ1XQkYLW90uGxuhrzXY2N5jbFa\ni1fjdaRmsHlulcWDB1hfO4emJ0RRRiFs4jijWvfYszAPmsH65oB/+feXOHb4ajbWzlGr1OnFMZv9\ngFq1ysxYg9zO2TXZxrZM1tbXabXb6LqFjBNeXloCdNr1Bgf278WioFZV1lg6Bt2twdA0V6fvd+n3\nfXbv3o2umWx0NpibmyWOY9bWVtQqrGJQq3okiWDhsj34cUwaJuR5RhD4NJtNlNyAQavVxLJs/CDA\nH6REacTY2BhInbXVdfqDhDAIJvFbMQAAERpJREFUmbaaLMxNUPMauE5BUcSYtqksJUwHKdWlv2U5\naJpBFAU0WzX8Qay0qH0f27Zp1lXPc8f31UaqiKlXq8i8QMqUWr2OP/AZ+H2mJyYwdQ2/P0Caqp3P\nNE0kGufWN5VJgtQY+F1000I3Xc71BvTShGxoXKCJmN2zk+xp12nXXQoREUqNPEsxDBshBHmWI4VJ\nGiX0k5ikEJimRrvRYmpihiwTJInAq1TQNZXo2u02SZKQUYDUkWaObVfo9/uqSyRMhjVwB9txEULQ\narYIgpDBQH0ZnZc90DRNaZkPx/Mty2FsbAwpwfcHCJFjm9ZwaKhAN4f+n0KMerPPJ9csUQM+uq6R\nJCn5UFwsiuLRMJRh6LieciMydQM/VCqJaupXR2qq+yhNUyxb/Z1uQLVaJY0zpRMOpHmBbljEYUyU\nJEg0ojQlSVUt39RfOwhXsvO4tJO4pmFo0GrVeOkPp6l5Ner1cbQ8Y2HPDIYJzfEGvSDEcF0mHYlr\nVominM1uj5dffZWDBw/Q6XSpVOvMzU7T6wfEIseyNCYnx7AsjW6/z8zYDEbLYxBGzM1M0J6eRRQ6\np1fXyNKUyxb24ZmSVq3Glt/FtS3c3CFJJCKTdHsDxsbGsUyoNuqMj4+ztbGJZVkE4YCx8Sa2YzI5\n1abRaBD2+yRRQrNWw48jbMchDSMmJseZnGqzurKKH8SEodqwqlSrJJlk9555trodHMfBDyOEKNg1\nM06a1nGsgtmpFqY06McRFJLx8XH6fsRWp4dXMQCTNMnZ3DxHre7heVUajRobG1tUq95rtM9zIWk0\n6uRFRq+nSh6ZSLELNTlb8WqkokB3HOIsJfTVKt+teCB1TMfDrTrkuaA3CMgK2Or5FJqJ5egUaYJV\nSOYm6uybaVLRBCaSfpKSJmCYFoUE3QBL19ElyKzAjxMwdMhzPNshFwJpQJpJZBhTFGq12+8PiMIE\n3VFv8263j+N4GIaJYzpohoVRUebC3d4AXZPDDcU/1paTNCWKIjRDxzRNvKFBcZoK4jjFNC0mJibw\n/YAoVJuGtuORSYbqiOr/890tIlHaMcZQQyWOY/LhXECSZCOFTNdz1JdXLkijGFPTla2brtoDNdMY\nabNkaUq1WsW0DdIkIR72knuui0QShDFC5KRZTJxkSg5ZN9E1DceySgGsHc4lncQNXadZrSLCDlPt\nFq9udBCaxeVzE/h+higEpm2xvLJCr+dzaP/lbG12SbKUXfMzYBS89OLvuWJhAV3XadiWEncCXl7+\nPVcd2E/DklR3TWNrBdVag/XeGqsbW/h+QKfnMz4+QTjoIbMEy9IJ/A5FnuNVW6yureO6NpPTU9Sa\nVTY7HVZWN1m4bA9hGFKtebi2jdeosbq6SpKo6b92u02WSdpT40BBUki6wYAkSUZaz61Wi2ZTJ4wi\n0lSwfHoFKcE2N8mKjJWVFQzTBc1i5eyrtNuTNOo1wrBPEiRYbhXXtuhtdRC5xLNMpSESZYRxyvj4\nBJpW0O/3CYMEKSUTE+NkaUYURZimcmjv9QbYrgGaged41JwGm5118uy85GnBYKujlBVNtQnY7XYR\nhTa0SUuoVSujPmXdsEiiAIHAMUzqts1cewwjU5ZmsZT0Q8hFQZIqVxopC4pcoOkuuSiGmigFhqZM\nO3rdAYZrop+fJtWGQy2aSZZJDEOMNveKoiCJI7RCYjmw1llXia0oSOIQ1/Gwht0ksigwLWUppxtK\nyjbP8+HGrKp5O45DEAQjM+lGvU4Y+viR0hR3HFUOMU2lIJnnuUro/HFlD/yxzKIz1DVRde8oijCl\njmnbww1PTRk0D70yPdfF1FRvOrZBHMUYhoUU6nHmUg6/lDRcx6PIVXtpVuQ4loFllm73O51LOonn\nRYFm2VRaDcyk4C1XLPDbf3+Z//3L37B45SKu4bCx8geOLC6y0dlgdc3n9MoZ/ts/XUsadNFExlh7\njN+8/DuOHDrC4FwPxxVcNjtDmMYsrZzlXUeO0h/06PZDTMdhZqrBIJS8srLC/K4p0jTiwN45xhs1\nBoMejbE2+VaXPCuQmExNz6GZOd21TWYmJtk9O02v6xMGEevr67z1bW+m1+uSBglX7N9DGEacfuUs\nIotY1yStVgtL15hptRhg0t3o0fUD4jjGdV2mJieQRcC+y+fpBxFFqmFbLqaT0Gg0kDKjyOqMVW12\nT7ZJM9goNmk0PYo8ZZAmoNvUai02O5uITLXLjY03SNOUIIiUd6Rh0OsFuE4V04BarULFs4jjiF7X\nx/Fc8iLG3+ohlakOlmMoNb8ooMhzCl0jTcEyHUxdpz3RVl8KYUqWCnq+T65r4BiITGLmCXunx2lX\n1Co3zQSGntOqGeSaTSeKSdMEx9DQNRvLtJGW6mvWJEr0LJdsbnXA0jF1i3q9habDoN8hTjNM28Nx\nnGEnRoKUCZZtUeQFSRjiWRaGbtEb+MhClTTO63Obho7UCrI0p0ggywTxcEPXMHQcy2bQ7xLFmRrc\nqVQI4oBU5lRddVWjdHoMsjgiihIMTafIM+X6OhxuStMU3VAb+a7dIIwGGJqG7VWUm5JU5ihSamoG\nIoeskBimIIwCJUeQFLiFMs5WK3glh2taJp7nkKbaaGjovN5QkiRYpjVUCC3ZqWjyDSiI/UeHmNfj\n3OoK//y/Ps6emQls26Db2aI9NkUQpKx3+wRRwPz8DIk/wO/1ses1/IH6gExNjzPobdFqNQn8hCzJ\n+bc/nGasVWd6rE2/u4XUcpqtGqYGcSSYm5tlo7PF1pZPpkEw6DHdarB4xeXkaUKqgcgE/mCA47m0\nmk2CIARNKRMWhRrkKIqMVrPJxmaHIler6fb4JK6nM+h30TQL13MIw5Akzkaaz+vrq/QGPhNT0xim\nTpoKAj8kFxkTk5Oc29yiHyRESUKcpCRZSrNRZ9xz2TXdIhwE9P0Ix3WRMmN8fAqRCQSCgozOlo9t\n2di2SxAENJrjajy9yIGcJIkQmYlh6YRRwNR0m0ykOIaN7wfEWTpKclIqp5xKpYJlWaosIAqCMCRK\nVe1VddZUyXMI0oR+khIVORINS9cY9wwOzk1CrrRLTMOhkAZhEJPpNpshFIWm9EQ0aNc9KpbBv51d\npZsl6MC+XfPMTrRVa+PQ29S0DExLQ2oamZCjKdBMpFQrSkgqiZQueF5I1ZaapFRcl0IqWzkh1Mq4\nKHLSLCNOYjRNp95oYrsOg34wEo8qZEEhJY7pECaJEkQrGH5pnJch1tB1CyEy1TvuKC9RKSEXuTLQ\nzgss06JWqzIyMZFQDLtfslQgctXLrhk6UioNfaWoqGHbllJ9lJLA9/FcD8uxhyYY6vnK8xzLtkkS\n9TpapskXv/zPTE9PXrDPbcn2ckkn8ZKSkkuH8nN7aVJeR5WUlJTsYP7LJP673/2Oo0ePjv41m00e\neOABtra2uPHGGzlw4ADvfve76Xa7o9vcd9997N+/n4MHD/L4449f1BMoKSkp+UfmryqnFEXB3Nwc\nJ06c4Ktf/SoTExN8+tOf5v7776fT6XD8+HFOnTrFXXfdxS9/+UvOnDnDDTfcwIsvvjiqS0J5WVZS\nshMpP7eXJn9VOeXJJ5/kiiuuYPfu3TzyyCPcc889ANxzzz1873vfA+D73/8+d955J5ZlsbCwwBVX\nXMGJEycu/CMvKSkpKfnrkvjDDz/MnXfeCcDa2hrT09MATE9Ps7a2BsDZs2eZn58f3WZ+fp4zZ85c\nqMdbUlJSUvIn/MVJPE1TfvCDH/CBD3zgz353XsT+9fh//e7zn//86N/TTz/9urf9z353MSnjlnH/\nf4j598R9+umnX/M5Lbk0+YuT+KOPPspb3vIWJidVP+n09DSrq6sArKysMDU1BcDc3BzLy8uj250+\nfZq5ubk/u78/fXNcd911rxt3p73xy7hl3Esp5t8T97rrriuT+A7gL07i3/72t0elFIBbbrmFhx56\nCICHHnqI97///aPjDz/8MGmasrS0xEsvvcTb3va2C/ywS0pKSkrgLxy7D4KAJ598km984xujY5/9\n7Ge54447ePDBB1lYWOC73/0uAIuLi9xxxx0sLi5imiZf//rXS4GdkpKSkovEGzKxed111/HTn/50\nu8OWlJT8HbzjHe94w0pCJa/PG5LES0pKSkouDOXYfUlJSckOpkziJSUlJTuYSzqJP/bYYxw8eJD9\n+/dz//33X7D7/chHPsL09DRXX3316Nh2aMEsLy/zzne+k0OHDnHVVVfxwAMPbEvsOI659tprOXLk\nCIuLi3zuc5/btnMGJX969OhRbr755m2Lu7CwwDXXXMPRo0dH3VHbEbfb7XL77bfzpje9icXFRX7x\ni19c9LilvtE/OPISRQgh9+3bJ5eWlmSapvLw4cPy1KlTF+S+n3nmGXny5El51VVXjY596lOfkvff\nf7+UUsrjx4/Lz3zmM1JKKX/729/Kw4cPyzRN5dLSkty3b5/M8/xviruysiKff/55KaWUg8FAHjhw\nQJ46dWpbYgdBIKWUMssyee2118pnn312W+JKKeWXv/xledddd8mbb75ZSrk9z/XCwoLc3Nx8zbHt\niPuhD31IPvjgg1JK9Vx3u91te56llDLPczkzMyNfffXVbY1b8sZxySbx5557Tt50002jn++77z55\n3333XbD7X1paek0Sv/LKK+Xq6qqUUiXbK6+8Ukop5b333iuPHz8++rubbrpJ/vznP78gj+F973uf\nfOKJJ7Y1dhAE8tixY/I3v/nNtsRdXl6W119/vXzqqafke9/7Xinl9jzXCwsLcmNj4zXHLnbcbrcr\n9+7d+2fHt/P1/fGPfyzf/va3b3vckjeOS7accubMGXbv3j36+WJrsGy3Fswrr7zC888/z7XXXrst\nsYui4MiRI0xPT49KOtsR95Of/CRf+tKXXqNiuR1xNU3jhhtu4NixY6P5hosdd2lpicnJST784Q/z\n5je/mY997GMEQbCt761S3+gfj0s2ib+RA0J/ixbMX4Pv+9x222185StfoV6vb0tsXdd54YUXOH36\nNM888ww/+clPLnrcH/7wh0xNTXH06NHXlTC9WOf7s5/9jOeff55HH32Ur33tazz77LMXPa4QgpMn\nT/Lxj3+ckydPUq1WOX78+EWPe54LrW9UsjO4ZJP4f9RgWV5efs3q4ULz92rB/KVkWcZtt93G3Xff\nPZIq2K7YAM1mk/e85z386le/uuhxn3vuOR555BH27t3LnXfeyVNPPcXdd9+9Lec7OzsLwOTkJLfe\neisnTpy46HHn5+eZn5/nrW99KwC33347J0+eZGZmZlte3wutb1SyM7hkk/ixY8d46aWXeOWVV0jT\nlO985zvccsstFy3edmjBSCn56Ec/yuLiIp/4xCe2LfbGxsaoMyGKIp544gmOHj160ePee++9LC8v\ns7S0xMMPP8y73vUuvvWtb130uGEYMhgMACUZ8fjjj3P11Vdf9LgzMzPs3r2bF198EVD6+4cOHeLm\nm2/eFp2hUt/oH5Q3uij/n/GjH/1IHjhwQO7bt0/ee++9F+x+P/jBD8rZ2VlpWZacn5+X3/zmN+Xm\n5qa8/vrr5f79++WNN94oO53O6O+/8IUvyH379skrr7xSPvbYY39z3GeffVZqmiYPHz4sjxw5Io8c\nOSIfffTRix7717/+tTx69Kg8fPiwvPrqq+UXv/hFKaXclnM+z9NPPz3qTrnYcX//+9/Lw4cPy8OH\nD8tDhw6N3jvbcb4vvPCCPHbsmLzmmmvkrbfeKrvd7rbE9X1ftttt2e/3R8e28/UteeMox+5LSkpK\ndjCXbDmlpKSkpOS/pkziJSUlJTuYMomXlJSU7GDKJF5SUlKygymTeElJSckOpkziJSUlJTuYMomX\nlJSU7GDKJF5SUlKyg/m/oTjbt13IcxYAAAAASUVORK5CYII=\n", "text": [ - "" + "" ] } ], @@ -136,7 +136,7 @@ "\n", "training_images = []\n", "# load landmarked images\n", - "for i in mio.import_images(path_to_lfpw + 'lfpw/trainset/*'):\n", + "for i in mio.import_images(path_to_lfpw + 'lfpw/trainset/*', verbose=True):\n", " # crop image\n", " i.crop_to_landmarks_proportion_inplace(0.1)\n", " # convert it to greyscale if needed\n", @@ -147,7 +147,6496 @@ ], "language": "python", "metadata": {}, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 0%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 1%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 2%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 3%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [ ] 4%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 5%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 6%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 7%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 8%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [= ] 9%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 10%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 11%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 12%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 13%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [== ] 14%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 15%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 16%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 17%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 18%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=== ] 19%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 20%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 21%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 22%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 23%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [==== ] 24%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 25%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 26%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 27%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 28%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [===== ] 29%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 30%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 31%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 32%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 33%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====== ] 34%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 35%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 36%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 37%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 38%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======= ] 39%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 40%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 41%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 42%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 43%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [======== ] 44%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 45%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 46%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 47%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 48%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========= ] 49%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 50%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 51%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 52%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 53%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [========== ] 54%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 55%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 56%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 57%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 58%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=========== ] 59%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 60%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 61%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 62%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 63%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============ ] 64%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 65%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 66%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 67%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 68%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============= ] 69%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 70%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 71%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 72%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 73%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [============== ] 74%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 75%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 76%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 77%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 78%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=============== ] 79%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 80%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 81%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 82%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 83%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================ ] 84%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 85%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 86%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 87%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 88%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================= ] 89%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 90%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 91%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 92%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 93%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [================== ] 94%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 95%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 96%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 97%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 98%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [=================== ] 99%" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\r", + "- Loading 811 assets: [====================] 100%" + ] + } + ], "prompt_number": 3 }, { @@ -193,9 +6682,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD7CAYAAAC2a1UBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n", "text": [ - "" + "" ] } ], @@ -6739,22 +13228,6 @@ "- Normalizing images size: Done\n" ] }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Estimating RAM memory requirements..." - ] - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\r", - "- Approximately 23.77 MB of RAM required to store model.\n" - ] - }, { "output_type": "stream", "stream": "stdout", @@ -26339,7 +32812,7 @@ "output_type": "pyout", "prompt_number": 8, "text": [ - "" + "" ] }, { @@ -26347,7 +32820,7 @@ "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAQAAAAD/CAYAAAAewQgeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkCLFHkZKAClS7GH8P0vt/J6tF7oQAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] }, { @@ -26355,7 +32828,7 @@ "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAQ8AAAD/CAYAAADvylOTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztfVuQJEd19tfTl7nuzOzM7MzsVSukFUJCSAvCijA4pN9i\n4QEjpBCWwFhsAMYOE2EHPFjC4TcTlnaNb4D95JAVGzgC7CdbYMCwgVhkiLAikGSwJSGsvc3Ozn2m\np6enb9Pd9T+sT+n0mZOX6svszG59ERVdnZWVmZWV+eV3TmZVJYIgCBAjRowYEdF1tQsQI0aMnYmY\nPGLEiNEUYvKIESNGU4jJI0aMGE0hJo8YMWI0hZg8YsSI0RRaIo/vfve7uPXWW3HkyBGcPHmyXWWK\nESPGDkCi2XUetVoNb33rW3H69Gns378f7373u/H1r38db3vb29pdxhgxYmxDNK08XnjhBdx88804\nfPgw0uk0PvrRj+Jf//Vf21m2GDFibGM0TR7T09M4ePBg+P/AgQOYnp5uS6FixIix/ZFq9sREItGW\nODFixNjeMHk2mlYe+/fvx9TUVPh/amoKBw4caDa5GDFi7DQETWJjYyN4y1veEpw7dy4ol8vBnXfe\nGbzyyisNcQDEW7zF2w7fTGjabEmlUvjbv/1bfOADH0CtVsOnP/3peKYlRozrCE1P1XolHvs8YsTY\n8Wi7zyNGjBjXN2LyiBEjRlOIySNGjBhNISaPGDFiNIWYPGLEiNEUmp6qjXH1kEqlMDQ0hKGhIfT3\n9yORSDRsXV1dm8LkBsC6L8N4OIF74YMgQL1eRxAEmzY6bgvn6clfbV9uMm/X/yAIUKlUUCqVUCwW\nUavVWr0t1x1i8tiBSKfT2LNnD2644QZMTEwgmUyiq6sr/OX7yWQSyWQyJBUiFtOviYAAbCIS2Tnr\n9TpqtVrDPu+4FE6b7Ng8DGgkCfmfp1Or1cKN/5f7snz5fB7Ly8vY2NiIyaMJxOSxA0HkceTIEdx8\n881IpVLhlkwmw990Oh2GS0KRZGPbTEqEd+ZqtYparbbpV3Zi2Zllp/ZVETytjY0NVKtVr42XbWlp\nCRsbG8jlciiXy1frdu5YXNPkMTg4iJGREYyOjiKdTm8aOTVJbhplWw0zoZmFdP39/bjppptw0003\nYd++fSFZaOSgKQ+T2jApDdvIT53e1El5HP5rUyJy4+Wh/4lEAslkErVaDclkUiUojbh4OXp7e9Hb\n24vh4WGUSqUwH349pVIJ+Xwe+XweGxsbke/VtYxrmjyGh4dxyy234NZbb8XAwACAN0mDdxwe7ru5\nzqHj/FfuRw0jpNNpjI6OYnR0FIODgw2E4OPz0PLQ/A1cCXCSoI6ojexkAnDykOaCZrJovg8fEIkQ\nWfr6O4IgwPDwMMbGxnDw4EFUq9Ww3jY2NkJfyPLyMmZmZrCxsRGTh8A1Tx5HjhzBr/7qr2JkZGST\nja/Z+aaOaOucmv8AwKYOq5GJ/O+rWrjSsEF2RNlJpamg+Su4aUCdiLZKpRLuc/IgkvFRF1o5Tc5b\nW7371qPm+OX3v1wuY21tDblcDtPT09jY2MDS0pK1nq9HbHvyyGQy6O7uRnd3N3p6esJfKanlPgDc\ncMMN2L17N7q6ulCv1xtkL5fEtPHGLG19Hx+BySnpcjxqvxq0Y9oobZrJkNducjpKVSEJQ9ukyWJS\nGpI0TNdoIl1THUvC1upL+2/a6vU6AKBcLmN9fR21Wg0rKyshWZbLZZTLZZRKJVSrVeM9u5ax7cmj\nu7sbw8PDGBoawu7du8Otq6vLOnoFQYDR0VEMDAygWCyG5AFgU6PjjVLzF0hHJP36Oh15PpS/jSQo\njoRNzmtTmXzfZ6aCiMKlMHgcaarYzBPTNfBr1epJErPNd8PT86lD2XaIXJPJJHp6erB7924EQYD+\n/n6srq5ifX0d+XweuVwOKysrYb1dj9j25NHT04OhoSFMTk5i79692LdvX+gkNNnLXD2kUikUi0WU\nSqUwTZME5qTBZzBSqRTS6XTD7AWf3dCmSPl/apC8Y2iQykg7zqGpLpPq0MwSThq1Wi0kiEqlsmmj\ncE4sXKGYZkxkWbTrkerPdH9MRC3J2QZN+WhES+SRTqfR19eH8fHxcGp3eXkZ8/PzqNVqyOfzKBaL\nznyvRWx78uju7sbQ0BAmJiYwNjaGwcFB9Pb2WpWHDKeRwWVXy06vTXnSvgzjhMNVC5EGNxs0G90E\nzanJoSkOG3GYzBOpMMrlcgNpaOaJzUTRyifNNRuJm4jYRh4yD1NdudqMZr7SbB0pWMonlUqhUCiE\n7YDKEQRXFqGtrq4il8tdkwSz7ckjk8lgcHAQ4+PjGB4eRnd39yYJ7NMQbERDv7wRS/NFUyHpdBqZ\nTKbhV6qTer2+iUgAbGrwppHZ1PlcIycnDU4cclpVmilSaZjUBlcZciSXCoL2+TVopqPJ7JP3wuTY\nlnXE4aPSTIvVkslk2BYHBgZCRZvJZLBr1y7UajX09vair68P6XQ6PDeXy+H8+fM4f/58TB5XA1x5\n9Pb2hnP6plGY33TXKkYZTpC2NlcSkjjImUtbrVZDJpNRSYsIBECDE1dTIbLT0fXJ65W/2rVKU0X6\nLaTqkL+a0uBqQ5aDym/btzmbpcqwkYfJ36G1DVt74fXEN47u7m50dXUhk8mgt7cXu3btwtjYGJLJ\nJAYHBzE0NISenp4wPTJt5ufn1TLtdGxL8ujv78euXbuwa9cuHDp0CKOjo+jp6UEmk1FnLwjaCCw7\nEHVa3uj5TIwkH5KqtBhJ+glMax4ymQwymQzq9TpSqZSxg7mmWnlcIhPNVKF9eb0mc4WX2bT606Qq\nZLm5T0d2ONsMh4k8TMvtebg0/9pBIBp5UN3xspKqzGQy6OvrQ1dXF/r6+tDX14dUKhXWbTqdxsjI\nCG644YbQ1E4kEqhWq8jlclhdXd3RimRbksfQ0BAOHjyIgwcPYnx8HHv27An9Ctpow2EbhW2Ng0jC\n5jPg+66pTW1kBq7YyHz0pU5nIkTb9fHrdHUCE+lpjk5ZZhNhUJhmFkpozlFtetv1nI5LdbgIxNVW\ntI0GDSoDDSSZTCZ8JoZMVJrCpW1oaAhHjhzBgQMHQtIpFAo4d+4czp07F5NHuzE0NIQbbrgBd9xx\nB/r7+0N/gpStJvVhG4m1pdKJRKKBQEw+Fa5Eurq6wo4opzV7eno2dUJZViondUibAtF8IjY/h408\nTARiWo8hSUJ2fukfkOXUfB02J6lNeUjVIf0cvgrEVI9SrfF2QnlrJg0fTCqVCgqFAgqFAqrVKgYH\nBzE2NtbgG1tdXUW9XsfCwgIWFhacZdyu2DbkMTAwEJoqhw8fxuTkZOgglZKVGpCP+tCUh/bMA40o\nFG4aSWV+PE1a4ryxsWEkOemEk2lr5oCWL6Vl2mwEYiILrSzUcfj1ckeoNuvFr5OX3UQg2pSrSY1x\n082kcnjdaWaT9p/XsyRJqgPpJOZ1QuUNggDd3d3hPeCkQVsQXFmDtG/fvtCspVk6KgM3bQqFgvE6\nryac5PGpT30K//Zv/4bx8XH8/Oc/BwAsLy/j0UcfxYULF3D48GH88z//M4aHh1sqyPDwMA4dOoRD\nhw5hYmICe/bs2aQ4pPIA7KOLyWFqemhKe3DL1LFkw6Z4fLGVjTw08M7lmomR0Pw8/Ho1MrH5NKSp\nwsMkaXClZlIgpmvUzBhZp1o+UgnJeuMkw4+byFiaYJw8Tf4ySourI5qN6+vr2zQI8XR2796NQ4cO\nYdeuXejr60Nvby+6u7vD6+GmzY4lj09+8pP4gz/4A3ziE58Iw06cOIFjx47h8ccfx8mTJ3HixAmc\nOHGipYIMDw/jxhtvxJ133om+vr6QpeW6Cak8APPiKVOH0pyHkkykhOXpcp8Fb+hShWgko5WXwEd6\n2aHlKCpHeRNxSLXlUhyUn+xIVAd81Oeml8mM0qARlElF8rrlM1RSHZh8H1retjBOMHRtJr8Zv04+\nk0bpVKvVcAk7H5CSyWQ4WE5OToYvdurr6wvrY3V1FUEQYGlpCbOzs+q1XG04yePXfu3XcP78+Yaw\nZ599FmfOnAEAHD9+HPfdd1/L5JFOp9Hf3x+aKtLLLpWHrYEA5gVTtg5Dzi/qLHyk4OfJkU4bMenc\narWqmjAmYpGdltIzEYhmKmijnbavmTvy+uS1ShVggywPpSM7PicoSSa2OrORkEYmPmGyTfB7wsMl\nicpjiUSiwTQl05gGw8HBwdCH0t/fj4GBgXANU71ex8bGBsbGxnDo0KGGPGhV63ZY2dqUz2Nubg4T\nExMAgImJCczNzbVcELr5/OU1kjx4GJ3DwRur7GSyI/I8TVLb1Eg06a0RCHnoyRciZxd4HrbrsZEk\nxdM2zWwzkalJJfC6cJXJVA4bYctfX8KwxddMLRvZuEiHoJlEWtuR6XATi8+wEVnQuiEADYvzhoaG\ncNNNN2F0dDTMq1Qq4dKlS5ient6Z5MHhUgBR0uF2o0YesuNpaZhuphYmGxtBjvSykZgar2bG8BkO\nbYqR78vO1ky92jqvD4FoBGr7rykfma7Jd2SqT5NC4P9p35cAtLim6V/bdUsVql2/JBwiBg6akeN1\nRAvyisUiKpUKBgcHMTg4COBNx3w+n0cikcDq6upVX3zWFHlMTExgdnYWk5OTmJmZwfj4eMsFIZnH\nn1jlN1d2TsC9HF12FpPtatq0TsbLK8vPwfO1KRBtNDQRSBQy8enUWv3J+D55+NSxiaRshCWv3UQy\nrjo1xZODlWYWa3Uuy6UpUled8f98FocWnyUSiQZ/Hx3v7e3Fvn37sLa2BuBNUiHSkQ+BdhJNkccD\nDzyAU6dO4YknnsCpU6fw4IMPtlwQqTzkzdY6p7TfXba91rB9GrpWVlNn1wiMFAi/JhOZkN2v5Wn7\n74KJEExEa9pkevI6pZPWdT9MzltXvUtCkKQgicREHPKBRql6fQjBRHbatWgqmNROKpVCb28vUqlU\ng8Od1zMATE5Ool6vY3h4OFxbVCwWsbCwgLm5ue1DHh/72Mdw5swZLC4u4uDBg/jTP/1TfOELX8Aj\njzyCp59+Gof/b6q2VdBNpZuoyXppEphmEjQyMDValxNRltFGHBI8PyIPk/rgXn2byrGZYC7Yyuhj\nYsh0TMQhF+KZiFq7byZ1YjNX+Cad06Z4NLLT1GqtVgsfIyBS0e65qb5tJGMiErouXsZUKtXgOKWN\nkEqlsHfvXgwMDGD//v0olUoolUrI5XLo6uoKXxuwFXCSx9e//nU1/PTp020tiElqcshGTr4E7lvw\nbbgm1aKNgCa7Wb47k+ITpJKg8/j7MqkxkzeeZne0+jH9N8l5LVzWpw02c8emtExKRN4X272Sm8tk\n0cjBRBy0EXnUarWQQOr1uqpCbHWr3QcTuJljCqf2xNszN436+/uRSqXQ19cXkkdvb2/oK+GOXeDN\n9U61Wi18N2s73ha/bVaY2iArgRMHf1O3JBKtgZoaKrG7Nurzhqitdq3X6+ENl7+UBpWfFAhPl69u\n1UZ+30bpatym/zblIhWATamYiNhEFtqvTQHaCEQjdxOB0P3j5EEEQuXgr1PQiMlFID73y6ZYKQ4f\nSIhESSHRcXoNxP79+5HJZDA2NtZQj9Q3KpUKFhYWsLi4eO2Th5R7vBFq76PQnhClhml7nNwlkzUb\nmX61NPj8Pk+HiIPCKU1aC8Kls1YXNjvad5P1asuD56WRhq+fRN47qT40YtfuCy+7TV1pykRTi5I8\nJIlwFUKDQRAEDemZ6tOXRHgdE6Hwdkfn87ognyC9IqJaraK7uxuZTAbDw8PhazepTmnqt1gsIplM\nolgstuWFztuGPPhDRQA2fWeFKw7+MJr2liuT8rA928HtSs1U4Y2H4shf2ellQ6Z8EomEdYWrzIvS\n4r+2fHwIRKZJ/hsX6cg4EtJs4+nzB8v49dJ942XiUl1ep0ldmDop1Tnlx9Wey19GBEIqRL7UierN\ndm98wkzgfjVqo7xeZZ3QYktev5w81tfXwxWvNDvT7HqRbUMeGxsbKBQKyOVyABB6nQGzr6NSqaBc\nLjeQiEldmBqGRh4EPjXMbxQpCFqRSmWkePRLjZZ3Tt6QTT4A6SSTZdDKycvB8/VRIdpoLcF9MVr6\nHPx6ufObEy3dQ2rcdA95OL9HvINoK47lg4aUh6xbKj/3Mfls/A1h2kON5N+iMko/jYQ8zn07mvLk\neWj3i8pFa0o0f1sikcCePXvCFa6zs7OYm5vb+eRB89S5XC6Uk7wypfIgU4XetcnfeiUbHmB/dN0k\nj+UNlgTC05VxKG26ufymy4apKRCT78U0ajWjPmTj45tGJiZS0spCv9zM4+dwUzOVSqFSqYThsnzU\nKbmvQr7ukdKnOiN1Svnw+qb0ozhs6V6b6p7KaFIhUdSGDSbikARKTniu+vjS+PHxcSSTSRQKhaYX\nm20b8qC56rW1NfT09KC3tzc8prExjSySSGQjkQ2cy1eqXDnSS4cVVT41WOmJ5xudTwSlNSheHh9/\nAZ3jIg8++rnUB49LjU+aHLIueYOksmvp8n3+Xld+jJQjPX0syRpAQ6fmPiftnbFk5tI18Fcs8oVf\nnPR5XpLMtSlgXhbNRybvhw/ByjB+v+VgR/eFg5tQRB42kuvq6gpfn9nf36+ufvXFtiEPmkbK5/MY\nGBjAxsZGQ+OU3m6CtJs5CdAoJVcNcmksfSTcKUYbfx8Df4ep9oyNVEuy82teezpPU0QmmPL0UR2S\n7Hh6FIfKIstEHZ+XVyoUTrD8PRa8DJVKJVQc/PrlNVG+3EzhafL3yfJr4A51UqblcjlsI1Jh8QVh\nGoGbFImvOrSRvrx/mv9Mmr1yOhZAwzFTWTWSbxbbhjz4R4WLxWLYQKVq4Jv0gRDhyLl8eqEQH31o\nVOrq6mpw1vFK5iMdf8kxMTcfrev1N2d0CLbGJUmQxzc1Tp6OTFdLXyoQHqb5CYA3FYfsONxnYCMO\nAGGd8xdEc/IA0KDitA7KFRTt809hUNqcSHid0v0g8iiXy+HKTbpP/Bqj3A/TPTG1U99Oqt1XeR8k\naUi1aCqvvFfynjWDbUMeyWQS3d3d6OvrQ09Pz6alwdSZqYFpH17ilcM7PTlfqfOQZJarEbn64HYi\nNdSenp7wk5dESPzmcJ8LLzu/Bi6/Zf4aNGKQx2wKhZ9L+1J283jchJGNlhOjlgedx9WZNCvk6A40\nvrSJmwnSbKF7TWTR3d3dYMJIdam9zkH71gyVQ5vG5b4V0xPe0sSRI7uLOKSKNJGUHKykApHqRA4m\n3OSS7bMZbBvyoE/77d27FyMjI+GLUaTSoDluajzc6UVfMacbTMRBb7WmG03rKjTy4J2FvyVb+14u\nzQYBaFAzvHECjTeIpyvLoDVCrfFJ0pAjlhaX9rVGJdOQjZeuRZZJG6kBqD4OqSKpgwJoqCfqsPIl\n0ryjmr6TI80weZ2ckDTy4IQg1/PIT43KmR4bcWiEr9WbrHuTgjD5PfhxjUQ4cbRqsgDbkDz27dsX\nvvSYIBs5jYKSOMh+phtMjlf6GA/daO0VgYnEm7a8JA9OHHwjIpOmEJ86lp2Gj2ymxufaeL3YVIep\n0crGJNOSjZnqm3dyE6GRQuQzIDwtnjfv8NK/pM2QaKqAd2SeF91Dfg5f/MWJgzsjqfxSIWpkIYnf\nRBw+o7xG3LxsBK4g+P3h1yzNPp+21Ay2DXnQE4WDg4OhfcxHP35T6/V6+E0Uqii+0Ehz1slPN/A0\nKb40Wzh5cJOF0pSmktZY6vX6phGMj5SaFDapD9kIuYPNBn6eVBwmwuDgZgudK0dpnof0OfHr4GWi\n88ikIfLgzm+6H1JBaDNessxB8OZjAnIaVjqDATQQgGaW2O6Rjfj5PTBBIw85s6ORAlcTPmQRtVw2\nbBvykCMydWTeyOhCeYVS55F2cyKRCG1iOZJQOuQXIZnMGxgnD/KdcCLiDVYbUamclA91DDl1aWuU\npk5ng2lUsTUg7rsxpcnLSveGE64pL359stFK25vqiFSlNJ94mjZyNTk4XQ5QWW4TSfgQhqlzyv+S\nvE1l5gSnEYSse65QNPOFyt4Kth15UMekBiSZFdjsfAQaH5qjSqEXKGsjPHUCksl8Co/y4N59Pj3L\nOwPvcJzoJInwaUauPLj6camPZqCpDpfy0O4Nb8R8NOe/WjqaIuNlo3urpWkrl2v0tF2X7JhaXUmC\niGJSRh3VTQSnHZNEwOvCtJmUSivtCthG5FEoFLC4uIgLFy6EDk65lkK7gdzGA9AwCnJvOe+gAELn\nKx/p+LmyU2uzOpQOV0FcARGk7S3XnpiII6rENI1yspHxUcmHPPhx23oH2dC1cplGXv7fpoJc5bSB\n3zMtPVtndJmQmgIwwXTNfF8SRlSTxEYg7SAOYBuRx9LSEl577TUUi0Xs3bsXk5OTmJycDJ8p0CQX\nrxTeeYE3HUmad1x2fE22awpAEgdBGyW0higVkLymVonD1rFkOrwxuSDrxUUets7vupZOkIbM15WW\nb4fkafp0Ro006FerM830kMpBUxLawKrFbRXbhjwWFxdRKBRw8eJF3HrrrajX6xgZGUFvb2+D2SJt\nTm4L0tOPnEw0JxjQeLNto49PR+a2Oz9XnqfZzRRus+NbudFauQhUF1Hg8h9I5RWFRKJ2Ph+Y1ICW\nlkYI9NsMeZgUDv33qUtJHHKthktZuI610ra2DXnQo8FLS0sYGRlBPp8PnWbAZj8HVTDvkNJuJviO\nHjyuPM8GUyOTTikbqZi2ZiDLrI1GLnVgg63Ra8pEnkdlkmU2HdPyljCd45uurUxR241NYfAwrR65\n6awRh60tN2PatIJtQx4SrovmHYubA5rPgafJ05Zhtl+ZhqmsprLb8rc5SLUbLa8tkdA/o9hsY3HF\n08w0H/+HT8dvpUHbOr9P+rZ7q6Xn20a0eqB7ppkqUnkAm59otpkrprbXTuIAtil52C5YMz+4bScd\nesDmd23IPLRfGc9WVp+bZkpbuy6T6aJdh4kkZQPhI5PtWnyOaZ3B5fQzldWVf5RG7nN/fc4xxTHd\nPxdM9cUJxKY8TERB4abjWjnbSSLbkjyIBPgDTECj6SKdpqabYJPnvg1MO4f/5+XQbpwpbQrTfCG+\nN5eTium4qYP4dCgt3EQKJsJohTxs4aY4PgOD9FM1k7+r3fB2y8mCh0lIgudtxFdpaEQh/7dDfWxb\n8qhUKiiVSuEzDoBOHnK60SWdNTRLHq6bp6Vp8sVIMrQpFh9/hWsUcpl2tjCXCvH5bSZf13ku0naR\nh2+e7TjHNz1JOFJtmNZtmFQKj9sqnOQxNTWFT3ziE5ifn0cikcDv/u7v4g//8A+xvLyMRx99FBcu\nXMDhw1e+3TI8PNxygQCET6iWSqXw1XTAm5UnfzlMxGFyYlG62r4G082RYSZo/gpNeWgqxgVTZ/C9\nPls8VzlMTkH6NTlOffKOUlZflaWZgFpcrazaPWwnuMKTBMBnYDhxaM5SmeaWK490Oo2//uu/xl13\n3YV8Po93vetdOHbsGJ555hkcO3YMjz/+OE6ePIkTJ07gxIkTLRWGQA+ZSfIgSAVCYYDb3paN2Lcz\nybz5vkkl8DLx/GTDlWRhU0LNKA7ZGH2u1TVyazARh+mYlm67iMN1zFd1ybiuNmM6n+57lHsh2xnf\n11SFiSBsxNEKgTjJgxZrAcDAwADe9ra3YXp6Gs8++yzOnDkDADh+/Djuu+++tpGHTXm4KkHrsNov\n7UftTLwc2n4U8JsvlYdPWi4i4Xn4NFyts9muzUVuPsRhyteGKAopSj261ImswyjwJRAe5iIPLY6m\nUFznNotIPo/z58/jpZdewj333IO5uTlMTEwAuPLh67m5uZYKwkHKg15urCkP+V/rcK7GG4X9TeGm\nEVrmo422/GY3u7LUhqjpmMijHQQi911p+Ia3EsdGALJt+HR67XyT09REQjIP6aPwUSGm5eym+mkW\n3uSRz+fx8MMP48tf/jJ27dq1qSDtKAxBc5iaKtGkRAi2xutj95qOmRqnSfmY0pbqI0qHlyRli8fL\n4pOuLJ+t8TVLIM006CiqwxVuqjutc0siMKVhUzEmArGdb/uNQhy2e9ksvMhjY2MDDz/8MB577DE8\n+OCDAK6ojdnZWUxOTmJmZgbj4+NtKRDg5/OQ/30ZNoqt69NQbTfC5Viz3dxWb7BLJfj4e2z1afrl\n6Wv7/H+Ua3Td16jEwY9p98lEGra4mlqR8eSvrbym+LY2w2dhOkUaBCd5BEGAT3/607jtttvwuc99\nLgx/4IEHcOrUKTzxxBM4depUSCrtgMnnYUPUURvQ7UstXZ//shH55Nsqafg4T/lvFNmsEaesXxuB\n+MxSREVUgvCtS63cUQiEw9cMiaIYbWrDRSSa36NdcJLHj3/8Y/zjP/4j3vGOd+Do0aMAgKeeegpf\n+MIX8Mgjj+Dpp5/G4cNXpmrbBfqKGH3Nm14P6IKpcfucx39d8UxhvKFoKzm1kUM+JOdTDi1NW5lN\ndrcss418ZflcZK1dQ6vkoaFV4tDOi0IaNvNDI2qZjq2cpnJodS+Vh889ahVO8njve99rXNJ8+vTp\nthaGUKvVUC6Xw+9q8u+EaM5HiWYqrRXi4I3DJXG1MroaRFT4jGy+jVgrsxZuSyNKuaKi3eThMue0\nuL7miSmuCT7xTQrQ1K542VvFtlxhWq1WG8iDXiRMcJGIq+KiwtY5TGm7HGO2cvqM4jIvn/LL+L4d\nz/Rfq9+dTCA+xGEjBtfxKMQh40VRH66BKcpAbMO2JA+SX6aX95g2mUanycOXOEyOMZfyaLXMtNmc\nfNp52r5vnj7n2Y630pjbdZ95WSQp+Bx3+TWiEqiNhCjMV31EHZhs2JbkwT/DMDo6ir6+PgBv+hLk\nq+cJppHDJ8wlH03p+EK7ac0SSKsjBqVtM1tsjdE3frPlApojkVbJg+CjJkykQed1wr8j4aMItfvW\n6vtiCNuePOhtYnRDNLXhMl9on4dHgc+5JnVhGoV8JWY7YCJKUx6+ysEknX3T6QSazdNEpCbi0EiD\nzo2i9NoNWf/a/SFV32o725bkoXUi7bsb/IlaV3r8V+77nm/67+P0kg2OHzd1Phei2MyuMH5M7vuU\nyUcOXw25XiJfAAAgAElEQVQy8YVJ8WgKzeTvkOe3oqKilNtmjmhEry1IbAbbkjxyuRympqbCDxV3\nd3djz549VsXhe4O0zuFylPmOxL6OS+3GuYjN11SRjdplf7cTUUj6ahBJs2Qrw7dSSTQDG3E0O1Bp\n2Jbksba2hlqthuXlZaTTaYyNjW36ghgnENON5KRga9C+5GDKQ4tvkrK+yoPvR3W8bQcCse2b4gPN\nrT51wTdNFzlEqcOrQTCy/WjH2qE4CNuSPPjLkPft2xe+DFn7ZgiHPObqqPJcGdf239bQfGxgk/Jo\n142VqqoZArGZW775y31THFdcU/milKUTnTmqWdgMTArbV0nZFG8r2JbkIaE5Sk3OU9P5zagLE4FE\n6Yg+pkwU30JUSOJwEYnLvufHWi1Xq/BJw0XkrcJUh6726FsOl4kexZyV/69Js0XChzB8iYTDp/JM\npNJqI2zV/rSZQkC02R+fuJryarbx+aiSViHrxlRXV9N34crbpmh9YDLZ2zVgbXvykL4NzWlqYmeT\n+SIRlUSiOs7k6BfVL8CP+6oeqZL4vm+ZbXF9yMul5jpFHLJ82v9WEFU1dCK/ZtKWhHHdKw8bmcg0\n2kEizZTVlJemPEz+kChkYQpvxudhyt9FoCblYtrvBKISiMt/1UyH9SVqV7vRBkgtDQmT6X3NOkw5\nfInDRCLy5vs670zxXDfPZo9qBGG7iXJ0tzUOTQVoHcfVgTTysY18Pp3DRSCy3K60XGXW4kdVi1Hy\n2KpzfercNljx/Xb4PFpbn7pFCIJAnWnxVR9Rbl6USrWNEr55uojERmpagzClzeNHaTQmQraRtele\ntHqPOqlStDJondVEpNp1N5OnTNMVJwq0tnZN+zw4fBqsrbFqzr9WbXDKw0RuNpjIwte8MikRW7hL\ngdiUBs+Xv+5Opi/35flaXpqJYSsDD7sa8Bn9NRXqGnBMpGoikmbbmS3cFzuGPHwIw0YiGnEQfEwW\nU4fiZdK+k+uTp8nPYTpH62S2jic7qItI+H9JGhza+zIladjqQMvPZc5cLbLQ4FMWF8m4iKSVvDmk\n6rgufB6A3Z9gIwwZz4dAolaqj+qR+bSqdkx+DVd8H+LQ4CIQ2Sg5gdhIhcqmqQ+bYrnaiNIOeZyo\nacswk/rQ4pvKyL9MQKu2m8W2J4+oSsPUgW0Eoo3MUcrFl83Lm8FJSe77qCBerlZh831EzUMbLU3X\naAqT50QlCt+4URWCKX5UQogy4JnS81UfNtKi7z7TC7by+TxyuRxWVlZQKpWs12DDticPwD26u2Sf\n1iibaaimm2tqALaOxOOYnFjaSEx5auWyXY92jim+qb58CUO7LpMiMeVnQ7tNGx/iMB33IQEbOTRb\nLl8VAjR+BymXy2FpaQlLS0tYWVlBsViMVCaObU8exJj5fB7pdBqJRALpdNpLddCv3EyNz9Wh5L6m\nPGSaWifysTs1ApHHZJltDUkjLb5vIkbtmKwLX/LQyi2JxUUkLtOmVfXke8yHMHzybAdceXPlsba2\nhqWlJczOziKbzaJcLjed77Ynj9XVVZw7dw6pVAqHDh3C/v37ceDAAaRSV4puIgkeFhWyAfsqDlfn\ndREGjyfD2t3oovoRfAiEE4KmMnyVCU9T7kctpyueNoLb9m3py+Om+LaBz9aGtfS1NLW8arUaarUa\nisUi1tbWsLKygvX1dVQqFUst2WElj1KphHvvvTf87OOHP/xhPPXUU1heXsajjz6KCxcu4PDhK59d\nGB4ebroQNmSzWZw7dw5ra2soFotIp9OYmJhAJpOxqgut0vl/V2Ns5qbLtKN0HI1c5CjbDgLRrttH\ncWkjeysEYjqmpdVOmBSk73H6byMSXxXiW1YXabjKQMq4Wq2iVCo1kMfGxkZTZQMci8R6enrw3HPP\n4eWXX8bPfvYzPPfcc/iP//gPnDhxAseOHcPrr7+O+++/v20fuNaQz+cxPT2NV155BefPn8fy8rL6\nKYYoxMHDJaLKTZfyMPkENEjisB2X6fuoGlN6GrmZ8rTVN3caa+teKNy24E8e42n6jthRR3N+bdq+\ndt0+4fL8KDARl29ZZdnq9XrDJ01yuRyKxSKq1WqkcnE4V5jSy4fpy227d+/Gs88+i+PHjwMAjh8/\njn/5l39pugAuEGNubGyEU0ta5UQlEhO5UBiHLT+tM5jgUxYtrlYOGc9WNjkbZOuQWjm18vBw+XpI\nLW8XmWhllOU0hUclF9O9sN1v27103WOfe2VrDz4E5dOu+SAhPzTWDJw+j3q9jne+851444038Pu/\n//u4/fbbMTc3h4mJCQBXvlk7NzfXUiFc+dNvtVoNPz3JGw29yzTKTbGZASYnoaujara7BlsndZ3j\nKo9PWU352Rqt6792zUEQRHpDN6UhHagA1HCbn8Q3P23fpy54PFu43G8HbOU2lYGTBn+HaStwkkdX\nVxdefvllrK6u4gMf+ACee+65huPtKIQNQRCEhMGVByeOqASieewpL5NPwJeYtDRt1+YbR8a3kZj2\n60MernxsecvzqQ74ZzJskGSg+XtM5OxLIC6/jen6tXO0azel1QyJuO6Ti/hkGFcbJhM1KrxnW4aG\nhvDBD34QP/3pTzExMYHZ2VlMTk5iZmYG4+PjTRcgKnw7sqmzSDaWnd51c33zoX3qOPxmccnIOwR1\ndi1P7RpM5KGZCppp5XOtpvyonPJ6o6gvk4PURkYyLtWhL4HIa9PqwdZmXKRhIggb+fi2WS1fV7l4\nW+fKQ/tGclRYh4TFxUVks1kAV94r+v3vfx9Hjx7FAw88gFOnTgEATp06hQcffLDpAkSBT+eJSigu\nAoiSHx/t6Z2rNEVGJhffd/kFXHa/3Ch9vlWrVXXb2NgwbhRHS482lz+jmXvqqmuTqmrGB8Lz8rnH\nMo5sJyYCcoWZ6sTUFk15mcpMkP6Ojvs8ZmZmcPz48bCBPPbYY7j//vtx9OhRPPLII3j66afDqdqt\nQhQicMUBdBNDjn6+efE0+NfKeVp00/hHd7jJJZWHb+eizmLr3CbnLr9uTdKaOpsNUX0PrmlpiqOd\n04wJw+PLfduvrQ7aQSA2QvJNR7uvABpIox1+Dyt53HHHHXjxxRc3hY+MjOD06dNNZ9oKeCfw8XPQ\nOa7ODkRbgq6xu2mVKZ8hohuYSqUaiILOk/4BX9Lg6kOqEBnO43NIOWsjEh5G58q4tmlqk83t29k1\ngtdIw0Ymto4q76/23/RrGnhc99JFHFqbM0HG05THNfm5SRNkh/G5GT7E4puv62bLkR5AQxgAJJNJ\nJJPJ0Aks5aOLvGzmjclUkr88LoEaVSqVUu1iSSZ0jvRxSLIwnUP7/NfnPmgkZjpu2tfOM4VppGAj\nElub1M41XadPmA842bZ7xmXHkYfPQqOtJA/ZiDSzgTouAKRSKaRSqfA5HbqJlJZmi0qSkDa+pi7o\nYSi+RkbzYxASiURYtlQqhWQyGX7TVJO6vCHKepRxTCTCf6O0AS0squqwpSfDTZ3fFUem7UMivu2x\nGbRKFhI7ijwAO4FocU2bnOZ15cnPI2idguJojskgCJBOp5FOp8Pl9RSfOq2U/7yxRXGUEnnQxp2n\n/Fxbx+b7/LvAnDg0D75JsTSrOEz3hJdRduSoZostfRtxmBSKjUg00tHiRDnXdk38HlWrVRQKBayu\nrqJQKLS0PH1HkYccgW03SiMLamTcXwLY1yKY0ubg0p2UwMbGBiqVCiqVCsrlMsrlckgemUxm0xJ7\nUiPa18vldUgzhasK/quRB/d5kNKx+TlkB08mkw3XbSMLkx9E/kYZSX1HaxuBRM3HRBDaca1NmtKM\nqj5cJGE6L5FIhAqSkwe1jWax48iDy/BkMol6vY5kMqkSBp0jVQMRBycNPgrz/GQatptOcalDb2xs\noFQqoVQqoVgsol6vI5PJhJ2Zn5PJZEIFonVa3uGl2nBNx0qThV8T+WCkatCc0rxONOebj8PVZLr4\ndGpX59Hiu8yWqHnZiEGWyRSm5aWl6VMeU1yeJt0H8rUVi0XkcjlrGj7YUeSxvr6O+fl5vPHGG5ic\nnMTo6ChGR0eRSqWcasNGLhI+N5zAO1AymUQqlUKtVkM6nQ5/uVqgkbtWq6FSqYTlq1aryGQym3wh\nPH8f8uDh1GHIEUoky8F9G9znQfEluUhfCD8mTRmNPOQ+D2tGFdiO2cyZKOm7VAj9aoMNP8+lYm2D\nlUzDVa6twI4ij0KhgPn5eZw9ezYcpYeHh43k4NoAvaFooz79yvjcJ0BKiAiETBE6j6sNMm0onJRH\nrVZTF/FIUuTOUY08tOlhKq9JNWiEoRGH3Lc5VHkdyXqV5OhDID4jc9QwF1yd1KdN2dqQiUy0Mtjy\nsuXRCexI8gCATCaDoaEh4+P5LtVhqnzTyKSdw+NSh+KdW67lkJ2bmxTcj8E7p8zfRB70y9dyuByb\nmrmibT7xfEnDpTpMBOKrNjrRaXxG+yiKRO43Uw4ZbiO1TmFHkUelUsHa2hq6urowPj4e+hG476IZ\n5cE7GoX5euWlc5FGcFITwJsjvzQpZBpEKBRXU0BEHtoKUk4UQRAYSUPr+D4kYjNNWplRabaBRyGN\nVjuRi0Bov1kS8W2vzVyTj7JpBjuSPCqVCrLZLAqFQtgRm7khFJeDOmGUSqaOxNMkPww5qohQtJWe\nBDomOyIvm1QgskFw88SkILRZEhlui6PNqHSSOGwdR7t/7cjTdZ6JHHyUia2d+pTXpjRc5W8ngew4\n8iACyWazKBaLm8gjKpNTZwXsZotPOHXcZDKJdDodhpEvxLSYSy4qs/kGtIZn82OYZlM0QpD7pmNU\npq1QHLbOYSKQqOlEhYsUfOLY1IQrjqk82v9OqQ5gh5GHhI+qcN0gU7rSTufxbR2DdyaaWUkkEiEp\nyMVpNH2mLW233XTuqOWdWxKFjThsCkIjBhu4YrPVl69SMHV2bcT3Sc90rJkOZSuD775LffiQneta\nm1FlUbBjyYMqx7ZUnceTI7XWyF1wKRSeLnd28pGckwT9J2WiPbhG+1o5fQhDmxWJsvneC61OeX1p\ndcjPN6Vr2/dVE612IhvpRBmgfNqmFu5TZle8KCrNFzuWPIDGSjY9LCfj+d4Q6gi2TqGBj+QE8odI\nJycnDbnUnJs3WkPkhGSbXjUpDl5Wvh/VBLERh1ZfPiOzTL/ZfVM6PuG+55pIzVWmKKSjpdMJMoiK\nHUseQfDmMvCNjQ0kEgl1sZhpypbSsDV4W0fQlIu88XL05s5MqVI4obheFMTT4GShkYbNJOHXoxGK\ndlzeAxdx8HjyXNt/LdzWIVshkKjwzVtrGz7E0kx8V/lspNQsdix50BLwSqWCarUarqmgUd612Rq7\nzXaX52gynI7zXwKVj87n5SWC4OtFuGKRpCedmy6/hkYaprLajkslYatLHk9DlHCf0TxKHq5jtni2\n/E2d13R+K+rHFl8bLNtJIjuaPLjysH2C0qY+CC7CkGRBcMlHE5nROdo+Td/afDlUNsojisqw7cs6\nccXh1x7Vh9QKobSDjJqFVg6TQjDdY1M6UfP3jdtu1QHsYPIol8tYWVnB5cuXUavVMDo6ikwm0/D8\nhqujStXgY7YQTERiUyoyzPRLhCOJh8fheXAF4kMc/FwXZBwf/4fpWLNhMrxZJdGODmQiCFc+PqRh\nGvzkcVs+Wr7lcjl8krbVr8Rx7FjyKJVKWF5exqVLl9DV1YXu7m4MDQ0B2CzP5D5XIUBzZksUSOJw\nORBN5ZbxefomwpA+jGbhm4arfmyNP6qy6MRoaoKLIHxG+GZVhy8ZaWUi8mjXJyY5djR5rKysYHp6\nGj09PRgaGtrkF6Bfua9Vtq/ZwmEbafn5tv88rWb3NWenS3WY8u4EWrk2n3S2Gq2YHu0gkKjnSfJo\n5ePWHDuWPMrlMrLZLLq6ujA8PIx9+/Y1rDYFoktdmxNUhrvMgCijvaZEojYW26yJj6nRTGeMYiK4\nFJYtnisdgu0626G+TPnbyC7qNbQbQRCEH7heX19HuVxueLq7FXiRR61Ww913340DBw7gm9/8JpaX\nl/Hoo4/iwoULOHz4yqcXhoeH21IgX5TLZayurqJSqWBsbAzr6+ubnrAFzDdb80doHcmHNCgNmR4/\nZjpH24/aqUyzITby0AjTtyGbzD2tbL5mmXbcNz2N7OW1t7uTtmKedaI8pvSDIMDGxkbo92gneXi9\ne/3LX/4ybrvttvBGnDhxAseOHcPrr7+O+++/HydOnGhLYaKAlMfs7CyWlpawvr6uPucC+EtibaQI\nAvfHhEx5mPwPcjM9i2J7l0aUhWGmtR/SwRp1BSpdl1a3JnPRVo/yuJyq9tlM6bUT7VIOW0EgXHm0\nmzycyuPSpUv49re/jT/5kz/BX/3VXwEAnn32WZw5cwYAcPz4cdx3331bTiC8YcqGxld3+qZlMlXk\nPh+pTYrENSJrSofSs0lxlzrQZn+kc9g0+kfpEL5mh+mYT3l80zeZay6V2A642oqJTE3puAgv6n0i\nyEGqXdfvJI/Pf/7z+NKXvtTwzsO5uTlMTEwAACYmJjA3N9eWwjQLOZr5niNHTUkgWiOQjdM2m2Fq\nwL7pmfwqUUYsTSG5Rmdfme2r7KIQiI1UNNjUnRaXp9UJEolyrBPpmgYFei3ElpHHt771LYyPj+Po\n0aP44Q9/qMZp11Rgq2hWpppUB09TxrVds+YzMUFTMfyY/JXqx3ZN8peTq9y3kYfPtTQbRyM123H6\ndZmDUnnK+vLxYZlgU1au6/WNH7UMpjyo/qhOyMzdEvL4yU9+gmeffRbf/va3USqVkMvl8Nhjj2Fi\nYgKzs7OYnJzEzMwMxsfH21KYVmAaSX1uikl1mNLycUj65q11AtNqUXmOzMemKlzEEWXUt/2XdWRL\ny9TgTWG8rmwvL9JMV+kYboVAtDqwXZNtX55rI/Ko5eNpEXm0c7C3kseTTz6JJ598EgBw5swZ/MVf\n/AW+9rWv4fHHH8epU6fwxBNP4NSpU3jwwQfbUphW4TsquM6VnUxbP2JSGK6OyGEaPbW3e9mclry8\n2vMwkixczkpt5Hddi1QGvI4oT9/6147J+tGcywQbgcg0feE7CMm4zRJBM3FNg4ist3Yh0joPquwv\nfOELeOSRR/D000/j8P9N1V5NaB2/lbRMnVHrTKb4WmfUoElw39kSOk97rN80C2Eqn20Wyad+eTjv\n6PKhPu36fcCvm0iDHoZMpTY3Y41AOq06THHaoSR8y2KrZ/lKhlbhTR733nsv7r33XgDAyMgITp8+\n3ZYCtAtax+UwNXg5GvHOJL+NIt+v4dPxbDDNFJiIwkYenLxMLxWybaY3mJnqUQvnYbJsPvUiVYtJ\nbUiSku991fIymS0+8On8UVVH1Lp2DUSm+1qr1VAoFLC8vIzZ2Vlks1mUSiXfS7dix64w5fAd+fmv\n5iTViIOe2q1UKuGnEqQaMY2svr4RPhqYTBX+nxOHNA18zBZ+raaNx+Fl1+qS158Mi+pfkX4NThr0\nvhZ+nO6VJBt5r5tVGbyO5b4JLgKxnd+MMrHd23q9jnw+j/n5eVy8eBHr6+soFouR89BwTZAHgE0d\nxhbP1ph4pdM3VSqVSvjZSPpUpDQLCCbvv63h2s4xjcSaz0NTErTP45nOkeG8vqgMvuShkZYpTObF\n64B/yU4SB68jqT6kCpEE0An4qA6bGnGF+5bBRB6XLl3a1F5bwTVBHmtra5iamsLPf/5z7N+/H+Pj\n45iYmNj0eL4NsmPQiEbkUS6XG8hDe0WgJrP5y39ko+VlMpGDJA/a5788LRcRmOICuolB8UxKzZSn\nzUmrkZm8F0Qc6XQ6/PIe3+RnMbWZKTlAyHvQKRIh+CgMrb5lvGY23n5JMbfraVrCNUEeq6urOHv2\nLPL5PI4cOYLbbrsNu3fvRnd3NwC903D1ofk95MuG+Ffv6abwmyV9E/K7sNLLLRuNjTS0X4JGIDIf\n03/ZyWgEl41ZdjhXQ9cctCZiktfFl9oTUdA3fGmf1IjptYtauU115gsfc0WD7+Al4/jGt5EH/xph\nK2rGhGuGPPL5PC5cuIBKpYKRkRHcfPPNAPTOozUeSSKSuYk46NkAuin8fN7weTj/5WXiElIzb1y+\nEln+qOfweFKBaHG0/zbFYSIOaT5wwuQzKel0Gt3d3chkMuGWTqfVN8IDcJqHtvryPacVAvEJt5k4\nWh2ayENz9Lcb1wR5UEWRb4I+IG2S5zbIEZA3ZPriPVctXHn4Nkh+Pq1PML131Cc9HsclzW0Nkj8w\npdWZiXhl/gT5vlap/KR/R/o4OGnQPSDFIcnWZvZpdWqrR1db8VFfrUC7R/K/iUBo0OvUC4A4rgny\nkJAVy8N9QA2TGjB3jCYSCVQqFSQSidB0IVbXnm41NVjKg/b5gifeqei4zTxx+UO0utFkrlRe/Nps\nph4HEQYvp9ah6PrkNLTNx6HVkXbdLsLQ6siXcH3RCTNBI3ONQGq1GorFIrLZLBYXF8NPtLYb1yR5\nAHrF8n2b+SKnBrn0pjj0yz9IrdnftsZLcbjCMaVhukat08h8KC6/fm1aV5ZRfmw7ivJwdR5JtJqf\nQ3OKamrDVAYfAjHtt6I+OgGTGjENBPTO0pg8IkB2Dlpl6CMnpZSWn0DgiiSZTDbMvPCO5UMirpHT\nZMLYys3TkfsakSYSiQbSoOs1ka4pb4Lm6zHtc7OQE4NLbUjyMJXF12yxlZPXk7YfFS4fhwyX5omM\nr5EG38hhSu2z3bgmyUNblk3HbCTCO24QBA3PS5BC4JKapsC4R5vLetsoaQrj12Eb5bVrsElveY42\nOstnRDTbWiufRoS2MADGFxpJtaERh0kxav9NZXHVl63DtgrN/Ih6nk19aG2/E7jmyAPYTCAUJn+1\nDspHRvpPxFGv1xtGRprCJXbnaz9cjVUrs686kmn5jKbS5OLHJWnK8sipPhNxaKtgTcelqSbJhL97\nwmYC+tRB1PrrJExKznXfbYrDNmB2EtccedTr9fCdjZVKpeEBKZcEBzaTB4WZ/ALU8PlzMLKj2hqK\nrVGYyqaFmTpWs6McT5/qQlNV8r/W4bW4GmHIMBMJ+ZZb/m8ncbRLgbhIwRVHW4ynOUzL5XLL5ZW4\n5siDFnaVSiWUy+VwlaKpE9nUBx+NeePjqoU6Av84tU1Syrx5eUyNxjWqmkwil8x1PXciO20QBMYH\n9nyJQ5KHyXGqnReFPLR7KevuaigO0zGf46ZN3sdarYZ8Po+FhQVMT08jn8+37WE4jmuOPEh5FItF\nlMtlZDKZTZ2GQAQgCYSrD35TeCeieFJ5aA/nuR7Y42Xjz2hoxMbhaxbZiMNWLkmeVCfadLSv4pAE\nwjfbNLdGHpIgbXVk24+KTpkEpjZh2jeRSLVaRT6fx+LiIqanp8NBrd24ZsmjXC6jXC6jt7dXnXWR\nysNEIPw/nSMdqbxD8NV8pk5K+9xH4mPX83L5EocGTYVpox83WbivQptNsikFm/qwpSnrw6SwtGuz\nxWuXqWJTlzzcN77rPHmubFP0eYVsNou1tbXwOy2dwjVLHqVSKXyM3vexcMDtVwDQ8B5I2SgTiUQD\neWijA19wxqd5bfJca/w2AuGkSMdcpCFVFp1nUwg208J0zKQ8fNPT4EMa2n95vitcazO+aZmO2fI2\nEYdsT/Tejk4vDOO4psmjXC5vmkY1kYeNNDiogXPnqSbztZGFqxC+AIuv7jR1PFkel/LwIQ7bf14G\n6di0rfJ0XYdUI74KRqYvy+6jJlohDp99n3Ppv4+K0c4xqRcij5WVFSwsLCCXy8XkERXFYhFLS0u4\nePEiEokE0uk0hoaGwmXmJtMlyshF6chFVXTMpGoobzqf+0tkHj7S3bfDyM7FZ094mjQzJZWHXHNB\nm1ZHzZCHTaH4XC+F20Z8Da2QBv9vM1v4vq3d2dKzqVf+9Dd3kq6srHTEScpxzZFHoVDAzMwMKpUK\n6vU6+vv7MTk5ib6+vobKp47OCUCO1hxaB+EdSWsotC9BZaC1I/I5EsrD1oGaJQ4eFgRBw1Q2L680\nL7TFWqbOJ/MzEYTLVJHXrqVvMjmjmge2MFMHp1+bsvAxSWzk40MctJo0l8thbm4OU1NTWFtba9sb\nw0y45siDnEQLCwtIpVKYnJwMiYT7GvgNkSOXRhS0Tx2O4spVmUCjGWKT1NQYSHaa1pJov76wEQeV\ngasIiidNCU1tmCQ2j2NTHrbZmKiqg2Az1bR4tnBfAqF9mzKxlcNEGPy/9iySVB65XA6zs7OYmpoK\nZ/86iWuOPGi5OH1nJp/PI5/Po6+vDz09PWEj1RhdjqgmOU4d0JQWJxeZhkyHNq5CAHODs0l0rYO5\nyEamw1WV1qFtZaNjmsniOxtju+Z2IYrS4P991KXW+WW4TWXY4lI75S+pIt9eNptFLpdr6ztKXfAi\nj8OHD2NwcDBccPXCCy9geXkZjz76KC5cuIDDh698fmF4eLjT5Y2EarUaPl3Y29uLIAga3gdBHVh7\neM7WYGXnkAQinalafJ4OP8/UsCRMI75JqZjUFE9fOydKx+WkytPwXfuhkU67YSIG7RgP8/n1MVFM\nx0yKQzNZ+Ht119bWsLa2hqWlJayurnZ0albCizwSiQR++MMfYmRkJAw7ceIEjh07hscffxwnT57E\niRMntvxj1y5w8ujv70cqlUJvb2/43ITpZknJa5LOnDi09PiCLx7fNJqbGhDty3gynPJwSf9mTAEb\noXE1xssAwEoctnI2a6bZYOvAtjiu+6H9mvLR6lKLo+UbBEHDe3WLxSJWV1exvLyM+fn57UkewOZK\nefbZZ3HmzBkAwPHjx3HfffdtO/IoFotYXFzE+fPnw448MDDQMPOizcCY1AfvIHScEwjfl+fLkVR2\nGm1E1Bq1iVx4ulr62nEJ26hsCpPEoeWtqQ1TGWwKqRX4XIuJRFwqw6VGTKThozqkf4PMFiKQtbU1\nzM/PY2ZmBisrK9uPPBKJBN73vvchmUzi937v9/CZz3wGc3NzmJiYAABMTExgbm6uowVtBuvr67h8\n+QKclvUAAB6sSURBVHK4WKynpwfj4+MNq06l70FjfoKmPDTTRZIST0uaSjItmZePlNYQZfS2dQ5T\nB9CUmawTX4VhunZ5PbK8vvAhCa1Ofchbi2dSiTKOTx2bCITMl7W1tXB6dm1trePTsxxe5PHjH/8Y\ne/fuxcLCAo4dO4Zbb7214Xin7NNWQe9uXFhYQFdXFyYmJlAulzfNvAD67IEcUXkYH3E1EuFrJuT5\nct80KvvUqQ/B2eK7iNNHasvyRiUPraw2MtGUmgk280Du2wjERbBa+i6VqKWnkYaJQIg85ufnMT09\nHSqSrYIXeezduxcAsGfPHjz00EN44YUXMDExgdnZWUxOTmJmZgbj4+MdLWgzoJkXAMjlcigWi+GK\nU9uqU9sNN42KkgCkv4PA0+OmE9D4wmBXns0co7R9R7woaiwKYfD4spxRrt0GH9Lg/03XaFMV2i+P\nF1XJEUnIX22jYzTjUigUmqqnVuD8ZHahUMDa2hqAKyP59773Pdxxxx144IEHcOrUKQDAqVOn8OCD\nD3a2pC2CKtv29KvvaEHHJLQOo01DmiQpfyeIqcE0u5kaoWszdSpf88RFJjy9KPcyKlwd37dza+f5\nnGs6rt1b00Iwrd1eTTiVx9zcHB566CEAV0byj3/843j/+9+Pu+++G4888giefvppHP6/qdrtDpJ6\ntVqtYWWpaeOmDNDoh7D5P7j5wddtyFFfhnOTh6fJ4zTbyUwNXiMlGU+W2aQe2mWqmK7Rt7NoZGer\nDx4mO6XtHFcatnCuLkyEwslCI5AoddIJOMnjxhtvxMsvv7wpfGRkBKdPn+5IoTqBjY2N8KnD3t5e\n9Pf3N0ybugiEd3xTR7Z1FG7K2BodL4utk/rCNrryfdtxfn3atdoIRKsfU1qm8vter6kjmUjEVQ/y\nXBsZ83Af8tCIwzSzIj8+Rq+b4A9+Xg1ccytMTahUKshms5idnUUymcTo6Gj4en/e2DUCAXRb36RI\nTB1dm33h+5w8pDNXS8/VqVwjpen6TJ2wWfIwkYnvNUUZXV2qIwqBavn71qktXDNTTOTBF4XR95Jp\nKxQK4edPrwauG/KgJbwzMzPhd0HoaVutsWuNwNVZpSIh88U0MmgjFJ3n8yv3TenTPg/X9rXrseUb\nlTy0dKOQoQ1R1QIPs3V407m+hCz3XaaKyQdGi8JoK5VK4XNcMXl0GEQely9fRiaTQX9/P3bv3o10\nOg2gcbWovKly9SjBNJICjWTjIhC5bzMVTHnz/7ZOIPM2dVhT+iai4GHyPB9TpR3E4VIbMsyHODSi\ncYWb9n1MFe7bkCYLvSksl8shl8theXl5y1eVclxX5LG8vIxarYZ0Oo3BwUGMjY2F7zjVHKja6lNb\nI9eIQx7j4PFo39QobWjVwcjTsJlKNpVhO+4qb7sUh2+8qMRhIgOZnhbXtGmmiok4uNlSKBSwtLSE\n2dlZLCwsYGVlZcsehJO4bsijVCqhVqthbW0NmUwGY2Nj2LdvH/r6+pBMJtHd3R0+MMf9DaaGppko\n/JiEpgxkPN/RzwRTevK4LLN2LfTrQxyu+KY0tTJHgU+9+NZdM2YIPzcqebhMFf4tIHqKtlKpoFAo\nYHFxEZcuXcLly5fD8KuB64Y86CaUSiVks1ksLy9jcXERPT096OrqQm9vL9LpdEgcmurg6kPrdIC5\nM/BwmxlDMElw7ZgrXFM3Uc0Ql39Di2/7lftRYaoPF+GaOrJ2ro854hMvquIgtUGP3dMDcEtLS5if\nn8fi4mJoslxNXDfkwVGpVLC6uoqZmRlkMpnQedrd3R12LtdGkJ3BZNrwVxDy/1HyahYmX0MnCKPT\n/g3A3/nrSxo8rosEbHFt4XLlqFwIyFUGEQjNqtAbwi5fvoyZmRksLy9fNVOF47okDz7z0tPTg8HB\nwXDKi3cOW4e2KQzbcU4aUn3QuVHm7V1qQ9vvBIHI82S4LEez8CEOX1OFjvsSh0ttmOLYpmJtqqNc\nLmN9fR2rq6uYm5vDhQsXcOnSpfBBz6uN65I86JVtqVQKu3btCl9VKMmDYCISDl8FwgnC9DJm+nWN\nknJfy0vu2/wWJpKxEYeWpilPWQdREYUsfFSH6Tzfe2AjDxlmIw0iDHKM0rRsNptFNpvFwsJCaK5k\ns9nI9dYpXLfkkc/nUa/XsXv3buTz+QbyoFWnAEL/B+37qA+Ky/dl46LXDmoNzkZWNmnuUw76NRGH\n7dekTkz5aOlocaJcj098W+c3dXLTvg+5u/LiykMuM+eEQbMpxWIxfFp2fn4eCwsLWFpa2hamCsd1\nSx70dunR0dGQPKrVKhKJRMNrCk3EwRsOVxouQpHn8WcUfBs4h09na5ZA+Dk+ZorpXC3cdA1RVImt\nLjR1qJ0flTiiqg2T6pDkQStGc7kc1tbWsLKygkuXLmF6ehrz8/Phh9u3E65L8uCr9tbX15HP57G2\ntoaBgQH09vZuehKWmxq8cXOVYPOB8DQ4gUjfCqUZhTxMYVoZZHlsfg55vum4jTB91AavO0nGJriO\n+SqCdhGHPCZJQ1Md3MfBVQfNqiwsLGBubg4LCwtYXl42Xu/VxHVJHhxkwiwvL6Onpwf1ej18xymg\nEwfv/BpcjkFJQFH26b+EqUP5ODBdxCHjmNIz5auFa0TBj9kIRB6zqTKtg2tx5L4rjm3TXmvgWgRG\n7+UgR/7s7CxWV1e39M1gUXHdk0e1WsX6+jqWlpbQ29uLZDIZviSZzAquENpFIlKJAO7pQgkXofj6\nJEzqwUQ2pjxsYVocSRp0HVrd+MJEAPK4iWhsaTRDHDZzRSOPlZUVzM7OYnp6etvMqphw3ZMHn7ZN\npVJIpVIYGBgIn3mhx/YlibgaqdaB5MeVbKOn6VfCRiBRyMNWfpffwocstDI3Qw78fL6vqTObeaHF\nken4kIU0U4JAX8PB9/kCsFKphNXVVayurmJxcRFLS0vbYgGYD6578iiVSlhYWAhvLn3bNp1OIwiC\nTTMvcuOkIuHrTASiTT1q8bT/JsLg/30cmu0iDQmu2iShNKs+bIpChpnIwxbHRBqaeaLNrtBSc3o6\nlhaAzc3NhTMrV+OVgs0gJo9SCYuLi+GrFgcHB8Nv29JHrmj2Rfu4k3SASvh0YA4Xich907mm9G1+\nj62AJAYZ1myaJkWhhUVVJFHNFEke3FwhRz293nNpaQmXL1/GhQsXMDs7G76zYyfguicPko/5fB69\nvb3Ys2cPRkdHkUgkMDo6Gn4dPpFIbFpEJk0YE4EA9s4qz7EpClsH8yEPV1miolmzo13EYStLVHLg\naUQlDc0ZKjfyYdAb7VZWVrCwsIDZ2VnMzs5icXGx5TrYSlz35MGxvr6OS5cuIQgCrK2t4S1veQu6\nu7uRyWQAvLkug5MHfzuYC6aZC5ci8UnfFMfH5LCRhytv347PzRIeJh2nvmSikYIWHkVFuM6Xvg3b\ncym0ceKg7ybncjksLS2FPo6lpaWr9k6OVhCTBwORx/LyMgqFArq7uzE+Po6BgYGQKCRxNPPODxN5\n+CqAVkdpH/OJ8rEd84EkBr6vhfmmJ8PaaYrY4rtmUmjdBilaCqfl5vQ09/z8PObm5pDNZsP3ke40\nxOTBQMuEs9ks0uk0xsbGMDExga6uLuzatQu7du1qmHmxPbbP0Q5TptPQ1I7JoesLX/PEV2nwfR/l\n0erG03M93Mbfu0F+i3K5HL5vY319HYuLi+G2sLCAhYUF5HK5yPW6XeBFHtlsFr/zO7+D//mf/0Ei\nkcAzzzyDI0eO4NFHH8WFCxdw+PCVTy8MDw93urxbhnw+jwsXLgAAFhcXccMNN+Dw4cMNL0zmDYgT\ngCbRTdBMmSjnEZpVI74kxa9LIwXfsrQym2KK5+OfaIVEbO/gkKqDfBpkouTzeayvryOXy4V+jtXV\nVaytrW275eZRkQg87tzx48dx77334lOf+lS4qOrP/uzPMDY2hscffxwnT57EysrKpg9db/Xo2U50\nd3djYGAAAwMDeMtb3oKjR4/i6NGjmJycRDqdRiqVCn9TqVToWE0mk6F5wz/t4LsB/gpETnO2G9qo\nrv1q52lxTOf7mA1amIsobKQRhVBcsyl80Rd3hq6srGB5eRnLy8vIZrPhYxCFQqHBrNnuMN1nJ3ms\nrq7i6NGjOHv2bEP4rbfeijNnzoSfnbzvvvvw2muvNSa+g8mD4+abb8Z73vMevOc978HBgweRTqfD\njUhEkofcohCID3m0S3nY4NvxTedF+fUlCu2YiTBMBOEiDnncNKOikUc+nw/XbdDTsEtLS1hdXQ3X\nduw0xWFqW06z5dy5c9izZw8++clP4r/+67/wrne9C3/zN3+Dubk5TExMAAAmJiYwNzfX3hJvI1Dj\n4O+L5KSgfZxaTuNSWBRE8YG0k6h5eeV+K2aHlgevH37Mhzi0Tt4qicjzbP4NbXqWlphPT09jbm4u\nNF2INOgp6msBzm/VVqtVvPjii/jsZz+LF198Ef39/ap5cq2oDA1BEITTbeRJly+o5aOQrcE2A212\npBOblp9pVkgSZTP3XyobVx21gzjkA2tauLZGg0+/8o3MD2oP5XIZKysruHz5MqampjA/Px9+ZH2n\nmCm+cCqPAwcO4MCBA3j3u98NAPjIRz6Cp556CpOTk5idncXk5CRmZmYwPj7e8cJeLdD7P+iFyYOD\ng5H9FfzTDs04RF3h7YBp6tQ2pRpVeZhUhhbmu2mE7VIe2nHXQ23cPKF3cJRKJVQqlfB8PqOytLTU\n1H3YKXCSx+TkJA4ePIjXX38dt9xyC06fPo3bb78dt99+O06dOoUnnngCp06dwoMPPrgV5b0qKBQK\nuHTpErq6urCysoJDhw7h4MGDDS8N0qZdaaOGpX08aqcrNm5O2MJNpocprFniiEIk8pkUF3HQVGy1\nWm1409fa2lqY5traGmZmZnbM8ymtwGuq9qtf/So+/vGPo1Kp4KabbsIzzzyDWq2GRx55BE8//XQ4\nVXutghaPZbNZrK6uIpFIYHh4GP39/aHPQ5P+kkBkh+F+g50CjSxc+77E4crXhzB8yMOHMExmDJmt\nuVwOU1NT+N///d+GZeX03Mp2e2VgJ+A1Vdt04juoU/jiwIEDeOc734mjR4/i0KFD4eKxnp6ecNqW\nT+OaZmG0qVztDWb8V+63G76EYCIFnzgu8nApDBMBmMjDZZ7Ix+c14uD+DJoxuXz5Ml599VW89tpr\nmJ+f78Tt2DYwUUS8wjQiCoUCpqamNpkw/BkXSQR8I287/44Lzda4eLxdSiXKeKGZH/Tre6xd5opJ\nafiE29SGRiDcx0GzbGtra+HK0NnZWczNze2YJ2A7gZg8ImJ9fR1TU1PhQqAgCDA0NNRgwtjWdsjv\ntnDS0Tp1u6ZGNfiaCjK+S324yEOm70saJoKwkYevWaKRiFxuvrKygqmpKZw/fx7z8/NYX1+PySOG\nP+ghpsXFRVSrVYyNjeHAgQMYGBhAX18fAGwiC/4oPwf/7KR8yI6vHtWmaluBD/k0a5JE3Y9KGiZy\nsJGGzTTR1mqQ0qAXE9Osyvz8PC5fvoyLFy9e8zMpPojJowVUKhUsLy/j4sWLAIDR0dHwXSCA3/Mq\n0nyp1+sNKkM7j5tHLkRVKSalwcOiEIPrf6uKwxRuUhMyTJonNC1PK0PX19fDcHpV4E58ArYTiMmj\nBVQqlfD7GtThe3p6kMlkrOs/NMj3pErl0cxCrFaIg/9vhTyaJY4o5GEjDY1EtH1SG7TI6+LFizh/\n/jyy2WwYl2ZSYvK4gpg8WgA9vk9P2mYyGfT39yOdTjeYI74dn/tENMKQaiQqObigqQ5tv1WTxBbH\nRBi+vgzT8nGNNKR5QibK3NwcLl26hLNnz2JlZaWtdXwtISaPFlCtVpHP55FIXPnKXHd3N1KpFDY2\nNjAyMoKRkZGGN6bblnMHQaASh7bobKuma+X/dvgxtLicMEykIcnDpiR8yKNer4ezJ+T8lObJTnuA\nbasRk0cLoNcT0PLkdDrdMB3b09OD7u5uownDO4x8uM6XPExE0g5VYvN/NGuKuMjDhzg4SZicntoT\nsHJbW1vDpUuX8Mtf/rLBPKGvt8XkYUdMHi2AXi9XLBZRr9fDb72QCUOLx+TIStBGeTnFS+n5KA9N\nzbQDGnHQr4lA5DVH8XH4mCmmlwzLY/I/f6htaWkJ09PTOHv27Lb9pON2RkwebUK1WkUul0NXVxdS\nqRT6+vowMDAQfoGur68Pvb296O7uDjscPSxHvyazxdd06TR50L6LPDTi8CETE3lo6y/kg2ryl6fB\nF3rl83lks1lks1nMzs6GH5GOER0xebQJ9LAUSd2BgQEMDg4inU5jYGAA1Wo1bNC0iIyIA3iz82lL\n1G1kwrEdyUMSgg+BUFzNryFVhelReV4u+jIbfaPn0qVL4Yuur4XXAV4txOTRJlCjLRQKSCQSGBoa\nwuDgILq6ujA0NBS+DLderzeQB23ykX3bBmzN8y6aWUW/Pv4Ok//CR6WYfBvaezboSVc+a0LlSyQS\nDQ+rzc/P49KlS3jjjTfCD33FaA4xeXQA5XIZS0tLSKVSyOVy2LVrFwYGBjA6Oor9+/cjkUgglUqh\nXq8jlUqFHYa//9S0cccq/5X7hHaoD5fyaJY8XOs4bGqDZkb4trq6Gr4zlH8gmpst9G7R7fwB6Z2C\nmDw6gEqlgsXFxXCkGxgYQH9/PyYmJpBIJLBr1y709fWFHQZ4c6Upf+JWIw8+omq/7YQkDfnbLHlo\nJBJlzQZfn8G3xcVFXLx4EVNTUw2PxPP0aCalWq22vb6uN8Tk0QHQKLi6uho6T3t7e1EoFEIF0tfX\nh56eHvT29gJ4c4Up/y4uVxu0X69v/rB2J9d+mAgkKnlo+zyeadqVzEFOKqVSCcViMfw2SrlcRqVS\nwfz8fPiOjfX19Y7UR4w3EZNHh0EOu0QigeXlZZw7dw7VahXz8/PYt28f9u7di927d4fvASGfiEl9\nUBjg//nKZstt2reZLr6qwmSmcB8GJwZaOwMg/Fzj0tISSqVSSDDLy8tYWVmJVcUWISaPDqNer4eO\n0pWVFdRqNSwuLmJubg7FYhE9PT2hCUM+EPnCoCgOVNcMDODvB3GpDh5uM0l8XrhDv9wMKRQK4QZc\nUWfJZDJUGFNTUyiVSg2KZH19PSaPLUJMHh1GEAThyFgul8PPCy4vL6O3txdjY2PhYjL6qLb2xjEX\ngTQzC+NDIibV4UsePg+ocb8GLbqTX10jJ3MqlcLs7CwuXryIN95447p43d92RUweVwmlUgnT09Po\n7e1FLpfDxMQEJiYmMDQ0FM668FcXchIxkQngNwvTDGnwfY1ETH4N6fDUlAifYs1ms6FJQn4NeuEO\nvc6RPtl4LX3GYCciJo+rhFKphMuXL6NQKGBhYQG33HILksnkpq/PSSIh8tAIBIju/7ARSRRnaZSp\nVk4eQRA0mCczMzPhIq5SqRT6Qehaurq6QvMkJo+ri5g8rhLK5XL4WcKlpSWk02kMDw+jt7cXyWSy\n4WXK/EXKRBycVAD9Q0z814RWyEOu05ArQ13PnfBPNNJ3XC9fvozz58/j7Nmz8crPbQ4nefziF7/A\nRz/60fD/2bNn8cUvfhG//du/jUcffRQXLlzA4f/79MLw8HBHC3utolwuY3Z2Fq+++ioWFxdDYqCl\n7QMDA+jp6QkJJJVKobe3N3xWxqZEADuBuEwYn+lZOYPis6ycfwy6UCg0LB/P5XINsysxticifXqh\nXq9j//79eOGFF/DVr34VY2NjePzxx3Hy5EmsrKyon6GM4UYmk8HQ0BCGhobQ19cXdv6enp7w1YaD\ng4MheXR3d2N4eBhDQ0Phw3dydSpg/lSkdHa64DJVosyq0Hbp0iVcuHABFy5cQLlcDp3KxWIR6+vr\nKBQKMYFsE5jaSSTy+N73vocvfvGLeP7553HrrbfizJkzmJiYwOzsLO677z689tprjYnH5NESent7\nsXfvXuzduxcjIyOh6ujp6cHY2Bj27NmD4eHhMFx+GwbQ14JI8nDdJ04SXEnY1nJo4fzc119/Ha++\n+ipeeeWVeKn4NoeJIiL5PL7xjW/gYx/7GABgbm4OExMTAICJiQnMzc21WMQYEuQPWFxcRKlUCkkh\nnU5jeXkZMzMz6OvrazBzBgcHsWvXrvBTEKZZGYJGLvKXKwt6nD2bzToXiNmcqbOzs2EaMXYmvJVH\npVLB/v378corr2DPnj3YvXt3w/sdR0ZGNr1QJVYerSGZTKKnpwc9PT3hW8oSiSuvPMxkMuju7m4I\n7+7uxt69ezE5OYmxsTGv6V1tCbzcqMNXq1VcvHgxfH4EMD9pazsWBEHoIF1bW4vNk22OlpXHd77z\nHbzrXe/Cnj17ACA0VyYnJzEzM4Px8fH2lDRGiFqthvX1de/nNHp6erC2tha+z4JP62rTvKY1JDKM\nP816+fJl/PKXv8Srr77a4auPsd3hTR5f//rXQ5MFAB544AGcOnUKTzzxBE6dOoUHH3ywIwWM4Y96\nvY7V1VVMT0+jWCxGWp1qi8t9FtPT0+Eq2RjXN7zMlvX1ddxwww04d+4cdu3aBeDK8upHHnkEFy9e\nNE7VxmbL1iKZTKK/vx/9/f3o6emx+jGi/HL/RS6XC82NGNcH2jLbEhUxecSIsfNhooguNTRGjBgx\nHIjJI0aMGE0hJo8YMWI0hZg8YsSI0RRi8ogRI0ZTiMkjRowYTSEmjxgxYjSFjpLHvffe28nkY8SI\n0WHY+nBHF4nFiBHj2kVstsSIEaMpxOQRI0aMptBR8vjud7+LW2+9FUeOHMHJkyc7ls+nPvUpTExM\n4I477gjDlpeXcezYMdxyyy14//vfj2w22/Z8p6am8P/+3//D7bffjre//e34yle+siV5l0ol3HPP\nPbjrrrtw22234Y//+I+3JF9CrVbD0aNH8aEPfWjL8j18+DDe8Y534OjRo/iVX/mVLcsXALLZLD7y\nkY/gbW97G2677Tb853/+Z8fz/sUvfoGjR4+G29DQEL7yla9s2TV7IegQqtVqcNNNNwXnzp0LKpVK\ncOeddwavvPJKR/L60Y9+FLz44ovB29/+9jDsj/7oj4KTJ08GQRAEJ06cCJ544om25zszMxO89NJL\nQRAEwdraWnDLLbcEr7zyypbkvb6+HgRBEGxsbAT33HNP8Pzzz29JvkEQBH/5l38Z/NZv/VbwoQ99\nKAiCranrw4cPB0tLSw1hW3W9n/jEJ4Knn346CIIr9Z3NZrcs7yAIglqtFkxOTgYXL17c0nxd6Bh5\n/OQnPwk+8IEPhP+feuqp4KmnnupUdsG5c+cayOOtb31rMDs7GwTBlU7+1re+tWN5Ez784Q8H3//+\n97c07/X19eDuu+8O/vu//3tL8p2amgruv//+4Ac/+EHwG7/xG0EQbE1dHz58OFhcXGwI24p8s9ls\ncOONN24K38p7/O///u/Be9/73i3P14WOmS3T09M4ePBg+P/AgQOYnp7uVHabsNXvWD1//jxeeukl\n3HPPPVuSd71ex1133YWJiYnQdNqKfD//+c/jS1/6UviCZWBr6jqRSOB973sf7r77bvz93//9luV7\n7tw57NmzB5/85Cfxzne+E5/5zGewvr6+pe1ru747uGPksZ3e5aG9+LedyOfzePjhh/HlL385fFlS\np/Pu6urCyy+/jEuXLuFHP/oRnnvuuY7n+61vfQvj4+M4evSo+QUxHbreH//4x3jppZfwne98B3/3\nd3+H559/fkvyrVarePHFF/HZz34WL774Ivr7+9VPjHSqfVUqFXzzm9/Eb/7mb2461ul27ULHyGP/\n/v3hS3KBK87FAwcOdCq7TaB3rALo6DtWNzY28PDDD+Oxxx4LX8W4VXkDwNDQED74wQ/ipz/9acfz\n/clPfoJnn30WN954Iz72sY/hBz/4AR577LEtud69e/cCAPbs2YOHHnoIL7zwwpbke+DAARw4cADv\nfve7AQAf+chH8OKLL2JycnJL7rHp3cGdztcHHSOPu+++G7/85S9x/vx5VCoV/NM//RMeeOCBTmW3\nCfSOVQAde8dqEAT49Kc/jdtuuw2f+9zntizvxcXF0MteLBbx/e9/H0ePHu14vk8++SSmpqZw7tw5\nfOMb38Cv//qv42tf+1rH8y0UCuFrD9fX1/G9730Pd9xxx5bc48nJSRw8eBCvv/46AOD06dO4/fbb\n8aEPfajjeQPmdwd3Ol8vdNKh8u1vfzu45ZZbgptuuil48sknO5bPRz/60WDv3r1BOp0ODhw4EPzD\nP/xDsLS0FNx///3BkSNHgmPHjgUrKyttz/f5558PEolEcOeddwZ33XVXcNdddwXf+c53Op73z372\ns+Do0aPBnXfeGdxxxx3Bn//5nwdBEGzJNRN++MMfhrMtnc737NmzwZ133hnceeedwe233x62pa26\n3pdffjm4++67g3e84x3BQw89FGSz2S3JO5/PB6Ojo0EulwvDtvIeuxAvT48RI0ZTiFeYxogRoynE\n5BEjRoymEJNHjBgxmkJMHjFixGgKMXnEiBGjKcTkESNGjKYQk0eMGDGaQkweMWLEaAr/H6S8w9fj\nVdIPAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] }, { @@ -26363,7 +32836,7 @@ "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAQAAAAD/CAYAAAAewQgeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrGDJCCCTTFawZASQSSYrWP4PJzco24oJ+dUAAAAASUVORK5CYII=\n", "text": [ - "" + "" ] }, { @@ -26371,7 +32844,7 @@ "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAQ8AAAD/CAYAAADvylOTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhIQ8EiRIUBP+P4kqi2EcUtVnAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] } ], @@ -26416,9 +32889,9 @@ { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAD7CAYAAACc26SuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVsB4iDPGWAHjIc4YYwWMhzhjjBWwX2AsqgXHpzWaAAAAAElFTkSuQmCC\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAD7CAYAAABzGc+QAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJUoGuBBClCgZ4EIIUaJkgAshRIn6CfH1fED1DyI7AAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] } ], @@ -26561,8 +33034,8 @@ "stream": "stdout", "text": [ "Image: 0\n", - "Initial error: 0.1200\n", - "Final error: 0.0948\n", + "Initial error: 0.1265\n", + "Final error: 0.0257\n", "Image: " ] }, @@ -26571,8 +33044,8 @@ "stream": "stdout", "text": [ " 1\n", - "Initial error: 0.0724\n", - "Final error: 0.0722\n", + "Initial error: 0.0806\n", + "Final error: 0.0725\n", "Image: " ] }, @@ -26581,8 +33054,8 @@ "stream": "stdout", "text": [ " 2\n", - "Initial error: 0.0495\n", - "Final error: 0.0458\n", + "Initial error: 0.0624\n", + "Final error: 0.0390\n", "Image: " ] }, @@ -26591,8 +33064,8 @@ "stream": "stdout", "text": [ " 3\n", - "Initial error: 0.0890\n", - "Final error: 0.0943\n", + "Initial error: 0.0881\n", + "Final error: 0.0590\n", "Image: " ] }, @@ -26601,8 +33074,8 @@ "stream": "stdout", "text": [ " 4\n", - "Initial error: 0.0332\n", - "Final error: 0.0207\n" + "Initial error: 0.0793\n", + "Final error: 0.0210\n" ] } ], @@ -26623,7 +33096,7 @@ "cell_type": "code", "collapsed": false, "input": [ - "fr = fitting_results[0]" + "fr = fitting_results[3]" ], "language": "python", "metadata": {}, @@ -26650,94 +33123,27 @@ "output_type": "pyout", "prompt_number": 16, "text": [ - "" + "" ] }, { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAAD7CAYAAACYLnSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWwAAAD7CAYAAABOi672AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nbMYYKxPcsBljrExww2aMsTLxB5mdjBmxSjomAAAAAElFTkSuQmCC\n", "text": [ - "" + "" ] }, { "metadata": {}, "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAAD7CAYAAACYLnSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYCaYm2aaaaadB2aCuWmmmWbaeWD/P5AU0Mtvld8dAAAAAElFTkSuQmCC\n", + "png": "iVBORw0KGgoAAAANSUhEUgAAAWwAAAD7CAYAAABOi672AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsfXmYVNW1/ap5nru7egAaRAaNE0Z9KhoxAsoQDDGKCjJI\nHJ7iL3Ek0RgQjGgciFMUE+OscXxqVAYR0RiJiIoaFRRoBoGmu2ue598f/dbmVNEIIpr2Ufv7+uvu\nqrp1b926d5111l57H02pVCqhGtWoRjWq0e1D+58+gGpUoxrVqMbuRRWwq1GNalTjexJVwK5GNapR\nje9JVAG7GtWoRjW+J1EF7GpUoxrV+J5EFbCrUY1qVON7Evr/xE6HDBmCN9544z+x62pUY5+KE044\nAUuXLt2t13q9XoRCoW/3gKqxy/B4PAgGg10+9x9h2G+88QZKpdIuf2bMmLFbr9vbP9X9Vvf7f2W/\nX4cYhUKh/8h5qf6U/3zVoFmVRKpRjWpU43sSVcCuRjWqUY3vSXRrwB4yZEh1v9X9VvdbjWr8b2hK\npdJ33ktEo9HgP7DbalRjn4uvc6915/ty9erVGDduHNatW4dEIoFZs2bhmmuu2e3tR44cibPOOgvn\nnHPOt3iUO4/JkyejZ8+emD17NpYuXYpzzjkHmzZt6vK1X/U9fCsMe8GCBRg4cCD69euHm2666dvY\nRTWqUY19KP7whz/gpJNOQjQaRaFQELBeunQpevbsWfbamTNn7gDMr7zyyn8MrIFOENZoNN/4ffa6\nra9QKGDatGlYvHgxmpqacOSRR2LMmDE44IAD9vauqlGNanSTeO+99/DSSy/Bbrdj8uTJ8Pl8e/X9\nN2zYgGOPPXavvud3HXtj9rLXGfby5cux//77o3fv3jAYDDjzzDPxwgsv7O3dVKMa1fiOolQq4bnn\nnsPNN9+MRYsW7fD8/PnzMWTISfjzX17Drbc9jkMOGYSOjo69tv8f//jHWLp0KaZNmwaHw4Hx48fj\n2muvRTKZxIgRI7BlyxY4HA44nU488cQTmDNnDp588kk4HA4MGjQIQGf+4P777wcAPPjggzjuuONw\n5ZVXwuv1Yr/99sOCBQtkfy0tLfjRj34Ep9OJYcOG4eKLL94tdn766aejoaEBbrcbJ5xwAj799NO9\ndg4Ye51hb968uWyK0qNHD7zzzjt79F4TJkyQv0ulErRaLYrFIgCUTS90Oh0AQKvVytRDq9VCp9PJ\nY1qtFnq9Hnq9HgaDAQaDASaTSbZjGAwG+P1+LFiwAO3t7aivr0c6nUYqlUI4HIZOp0Mul5P3yuVy\nyGazZe9lMBiQTqeRz+dhNBqh0+ng9XoRj8dhNBoRjUZRLBZlu2QyCbPZjGKxCJ1OB7PZDLPZjFAo\nBLPZjFgsBgCw2WywWCwyLdRoNCgUCvKZNBoNzGYzLBYLQqEQ7HY7ksmknJNgMAifzweLxQKz2Yxo\nNAqv1wutVgutVot4PI5MJoN4PI58Pg8AsFqtsFqtMBqNyOVySCQSKBaLsFgsco5NJhOy2Sw8Hg9S\nqRTMZjO2bduGUqmEZDIJg8GAbDYLrVaLTCYjflN+n4VCQb4nnl+j0YhSqYRCoQCLxYJ0Og2tVot8\nPg+9Xg+z2Qyv1yufmee+VCqVfTe8NkqlEnQ6neiD6vVTLBaRy+VQKBSQzWblc/M643ZGo1GuG6PR\nCJPJhHw+L9sXi0Xk83k5h+FwGLFYDOl0GplMBsViEcVicacaJY+pq+fUx/i6Pb2vvk6USiVMmDAR\nCxe9CYulJ+KxW3Hxxefj+utnyWsuvfRKNDaNgtvTHwCwaeNLmDdvXpnG/Pzzz2PatF8iEglj2LDh\neOihv8LhcOzWMSxZsgQnnngizjnnHJx77rmYMmUKNBoNrFYrFixYgAkTJpTpwZ9//jnWrl2Lhx9+\nWB6rlCSWL1+OKVOmIBAIYN68eZg6dSo2b94MADj77LNx/PHHY8mSJXjnnXcwcuRInHrqqbs8zlGj\nRuHBBx+E0WjEVVddhfHjx+ODDz7Yrc+4u7HXAXt3dZqZM2fK30OGDOkyg75mzRr5mzdcoVDYYT8E\nHBWcCSa82XQ6HfR6fdlNZzKZBNQBwGg0olevXnj33XexaNEiAYZAIIDNmzcjHA7DZrPB7XZj69at\nyOVysNlsAiyZTEZuRqPRKMdps9mQTqdhNpuRyWQEFAAIAAGdchI/HwCYzWZ4PB4Ui0Ukk0nkcjlY\nLBZoNBrk83nYbDZotVrkcjkAkIHCZrMhEokIMLlcLphMJgQCAWzduhWlUgkGgwFmsxkbN25EOp2W\nAaejowNerxfpdFoGJpPJBL1eD4fDgVgsBp1Oh0wmIwOLzWZDKpXChg0bYDAYoNfrUSwWEQwGodFo\nkEgkkMvlkM/nBZzT6bSAayaTgcFggMViEcAjQBUKBfmcxWIRRqNRBl+tVguXywWv1yvnQH0NB8BC\noSDXgnq9lEolAVkCdiaTgVarhcPh2GHgV4HaYrHAaDTKd5bL5eQnnU4jGo0iGAwiGAwiEomUAfbX\nuV84uO1uLF26dLcrG3cnPvzwQ7z88kLs3/886HRG5HLH4NZbb8Wll/5SZI9YLAZfrUe20emcCIXC\n8v/777+Pc86Zgh69foo6fw3+9c4SnHPOZDz//LN7fFw8Jzsb3HZ1zpqbmzF16lQAwMSJE3HRRReh\nra0N6XQaK1aswOuvvw69Xo/BgwdjzJgxu/UdTJ48Wf6eMWMGbr/9dsRisd0emHYn9jpgNzU1lY12\nmzZtQo8ePXZ4nQrYuxO88XijqUHWAuxc3FcridT/+X46nQ5utxubNm3CokWLoNPpcOyxx8LpdOKL\nL75AqVRCc3MzEokENm7cCKPRiLq6OmSzWWSzWeTzeZRKJWHVZImFQgHhcBgGgwHxeFxYH290smQO\nLGTKZG3BYBAOh0OA02AwQKfTwel0Ih6PIxaLwWw2w2QyIZPJwGKxIJfLwel0IpvNwuVywWAwIBaL\nQa/Xo1AooKamRgAklUoJSOr1ejQ2NqK9vR0WiwUABBjJxE0mE6LRKGpqaqDT6ZDP5+F0OlFfX49U\nKgWj0SjnggzU7XYjl8shFAoJQPJY8vm8DBbpdBrFYlGey2az0Gg00Ov1SCaT0Gq1cg1wwC0Wi4jH\n47BarQLAHPR4XfA4+T3v7Npg8PrhwMBtOJPh98BZgDoAc58Gg0GIAIlEV9HVfnf2/O5EJfm57rrr\nvtb2lREIBGC1eqHTdRIQg8EOk8mGUCgkgH3qqWPw7HOL0dBwMrLZKCLhlfjJT34n77F48WK43AfC\n6ewNAKhvOAmvvnrPNzqubxr19fXyN2dT8XgcbW1t8Hq9MmsDgJ49e+7U0cEoFou4+uqr8cwzz6C9\nvV2++46Oju4N2EcccQS++OILrF+/Ho2NjXjyySfxxBNPfOP35Y3QlSSigjRvvsqLn+yGNzRv7lKp\nBJvNhnw+j5aWFnR0dMDlcmH48OH44osvsGzZMmGnlCh8Ph8cDgfWrVuHYrEobMxkMqFUKiGVSgGA\nADKn8rlcDiaTCblcDg6HQ54nUJFput1uAEA0GoXJZEI6nUZTUxNcLhfWr1+PQqGAbdu2CaskYw2F\nQiIfOJ1OAJ0XjFarRU1NDZqbm5FKpbBx40Y4nU7odDrY7XakUik5v8FgEE6nE5FIBCaTCRqNRmYU\nPp8P/fv3R3t7u8g8gUAANpsNLper7Dzk83k4HA5ks1mEQiEB9mAwCJ1OJ+Dd0dEhMogK1pQ0eH6S\nyWTZgEU23N7ejqamJjnnAER+0ev1ci3wbz6n0+l2kCcqgZuDlfqb8hB/uA2vLXVmx2PltcjrrfL6\nZXRHS92gQYOQTgcQ6PgYbnc/BAIr4XTa0NzcLK+ZO/cW5PO/wnPPPQGr1YZ7770TJ5xwgjzv8XhQ\nyIflu0ing3A4nN/ouFSCVhmqxPl1o6GhAcFgEKlUSkjLxo0bdzkTeuyxx/Diiy/itddeQ3NzM8Lh\nMLxe7y4H5K8bex2w9Xo97rrrLpx88skoFAqYOnXqHjtEdjbd6Qq4efPt7KTwRiKA8kYtlUqijxqN\nRrS0tCAajWLFihXw+/2oq6tDW1sbrFYrdDodstkswuEwWltbhXHZbDYkEgnRrfl4Pp+HwWCQ/ZN5\nUUKhRECAzuVy0Gq1iMViMJlMMJvNIq20t7cjEAjIewGdN4JWqxUtvLa2FoVCAXV1dfB6vcLKE4mE\n7LOhoQF2u12Yaj6fh8/nQ2trKwqFAnr06IG2tjZ4PB45v5lMBr169YLdbkdbWxucTqcAc79+/eQz\nk3FFo1HE43Ho9Xpks1nU1tYiHo9Dp9PBarXK4+FwGH6/H6VSSWYAsVgMqVQKJpNJGHU+n4fVapXB\nlqBrs9mEHQGd8pJOpxMATafTwoiz2awMCHye1xOBVJVs+Nkp8QDoUsPmtnw/Hi+ZuQrYeyO6IiPf\nZni9XixaNB9nnTUB//74ZQwc+AM888yrcl0DgMlkwn333YP77uuaNY8fPx5//OOd2LThGej1HoTD\n/8Zf/nLvHh+TOrD6/X4EAgFEo1EhKX6/H6+++uoenavm5mYcccQRmDlzJq6//nqsWLECL730EsaM\nGfOV28XjcZhMJni9XiQSCVx99dU7PeZvEt9Kt74RI0ZgxIgR3/h9mPhSgzcTv4ydsaPdDa1Wi1Qq\nhWw2i02bNiEQCKBUKqGmpgaff/45gsGg6MaJRAIARI/1+XzQ6XQC2LyxKXsYDAaRNoxGIzQaTdnI\nrdfrRQNnctBqtaKmpkbYN296p9MJh8MhDXqSySRSqZRo6jabDblcDgaDQY7P7XajVCqhrq5OwCaR\nSKBnz55yvAaDAclkUkA7mUyiT58+2Lp1KzweD0wmkyT+fD6fMF+r1QqtVgun0wmTyQS73S5ASjZK\n2YKSUTabRTQaRSwWQ319PWpraxEIBJBKpWTw4YAajUbh9/uRTqcBQGQjgiGPg1IJj5XbU3/X6XRy\n7vP5fFmOQw1+Rxw0KTORXZOlUwoh269kzwaDQeSlbwLWlddypZz3XUbnrHnVHm9vtVqxfPkyPPLI\nIwgGgxg69FYcddRRe/x+KjEbOHAgzjrrLOy3334oFov49NNPcfrpp+PRRx+Fz+fDfvvthxUrVux0\ne/UxxmOPPSbWxKOOOgrjxo0ryy11FRMnTsTChQvR1NQEn8+HWbNmYd68eTvd555eF9260pGWHDVU\nvVfVI5lUZIKoMukIoCzpaDab5Tmr1Yq33noL27Ztg8ViEWCsra0FAGQyGaTTaWzZskW054aGBkmS\nBYNB0cMTiYQkGsnIuX+CDxmjy+VCJpOB0WhE7969Rb5IJBKIx+NiVYpGo3C73UgkEvB4PJLccrvd\nsFgscDqdMBqNsNvtwjjJ9AhQ6XQaffr0QSaTQSwWk+l7NBoVnVuv1wuTz2aziEQi8Pv9ojGXSiU0\nNjbC5XJhy5Yt4iCx2+1oaGiQ2QFBi8lDMuOOjg5Eo1Fhwu3t7bDZbOKosNvt2LJlC9avX49wOAy9\nXi/nyGAwlH0mVUP2er3wer1oaGjYwWnBa0B1aPAaJGjz+OjcofOF1xSvJ35Wq9UKs9ksgM3Bk26i\nRCKBRCKB9vZ2tLa2IhgMStJ4V9d9ZVJSPcbKyGQyX/le/Jz/Fyod/5Mxbtw4HHjggZgxY8Z3sr+v\n+h7+I/2wdze6aj2o0WiESebzeWE/BHJg+82o3pyqS0A9IWazGeFwWECpWCzKlLe9vV3R3dIyCNTU\n1ADonPpns1lh1nROUK8GIElAAgtdEQQRh8MBo9GIYDAoCdD6+nqRMVwuFxoaGgAA4XAYxWIRHo9H\nGDfZP5kkwddisUiykeeGSbfm5mZxadDBYjAYRJ/1eDyIxWJobGxEJBIRC5/b7RaQ6tevn4AoE6pm\ns1kSjHTYpNNpYdhGoxF+vx+5XA7RaBQ9e/YUMHa5XMJiTCYT1q5di2g0ilQqBb1eL7Mto9GIVCol\njMXn86Gurg719fVioaQ7RE0yqtIHt61kx9lsVmZFZOW8bsjq+V7qNaSyJfVaVTVrvo7A25XOqg4o\nlVG5j+9SFtnXYsWKFfB4POjTpw8WLlyIF198cQeJ4z8V3RqwySDUqaCqPfOm5I1FlqvekPyp9ORq\nNBp4vV5s2bIFH374obBf6roEaOqo6XQa6XQadXV1iEajMJvN8t50PjB5BmyfAvG1lFN8Ph9qamqQ\nTCbLfL9msxlWqxXxeBzBYBB9+/aF2WwW1ppIJOB2u+HxeGCz2WR6Tv+23W6XGYPL5YLdbkexWITV\nakWhUEAymRTW++WXX4r27na7ZQAhiHBgsVqtiEajiEQiYq2jbzyfz6OpqQlmsxmFQkHkiGKxKJ+3\nWCyKW8Jms8FsNiOZTMo+6DFn4jMej8usIZvN4osvvkAymRSWS+A0m81iwysUCpIMdjgc8Hg8Yhdk\nDkG1CPIa4XdNbZ+JTtU2qs7WCJD5fF6uD9UlwlkP34v+7K4cIqrmrcbOEpGVA8zOXluNvROtra34\n2c9+hkAggJ49e+Lee+/FoYceisceewwXXnjhDq/v3bs3Pv744+/k2Lq1JLLffvsBQNlNo2biCQbq\nDc1kFZmgOvUla6J2bLfb8dlnnyEYDCIQCCCTycDtdiOfzyMej8t01+/3Y9u2bXA6neKFjkQi0Gg6\nizbILp1OJ8LhsDBqq9WKdDot7NHv94uOm8lkUFdXBwACegSbVColU3S73Y6amhr4fD706NFDAIaJ\nO5PJBIfDAZvNJm4X6rqUeyhTANtZHAchJio1Gg0ikQja29uRSCTg9/sFODs6OlAsFlFTUyPnoFQq\nwWKxiERA6YcDFgDxX3NWUSgUYDabyxwd0WhUXkvGHolEsG3bNnz22WfYuHEj4vF4WVEMgZh+aCaE\n999/f7hcLpEsOBNTB/mu2CmTjeoASmatgjYlN87A1JwFfevJZBLJZBKJRALBYBDt7e0IhUJIJBKy\nD3XQUKOrx1QWX3ncLKj6qqhKIt+/+N5KIh6PRwCXN46afWdxBDVIgpx64avyCD2/Op1OGF0gEMC2\nbdskwUSLG5N3drsdgUBA9GqCChNPyWQSVqsVGo0Gra2tACDJJwIrLWkstqmtrRWHg8FggN1uh91u\nlwElm81Kxttms6GmpkYsYiwK4cBB4IjFYsjlclLMQp2XhTQECiYBmVjjwGQwGODxeEQzJusm402n\n07Db7dDr9fK/2+0WEKF2rtfrJaHpcrkkAWoymRCLxUTXps/V4XCUWR5ZRWk2m2UW8cUXXwjI5/N5\nOY5kMikA2tzcjLq6OvkuKqtcGarsoIKhOjvqSspQQZ+JT76elkSyc9UFxJkgZ4Dqe1bGzixqKsP+\nKk93Nf7vR7cG7IEDB+5QxUjAAlBWTkyQyWazwhjVUG9cMs9IJCKgQGYVCoVgMpngcrmE2dXU1CAa\njcLhcCAcDkOr1QqLNRqN4qMmyPB/uig4kNDVQR82wdrlcknSkINCOBxGr169pGCFTDEej8PlcqGm\npkYqIPV6vYCnKhep1XwE/FKpJH5pFrlwik9Gz4pMAPK5rFarzF6A7ZWnlBwIWmS11JF5PqjHMynL\nBF8qlYJWq4XP50MulxMm7nQ6ZWCKRCLYtGmTACF1b/qxk8kk1qxZA5PJhIaGBrhcLpG2VJcHPw+j\n0nlBYsD/eT5VdsvzqcpIJAuqFMKBQWXnKnPqikF1BcSVCXY1F1ONfS+6NWD36NFjB0ZNXzJ1Q4IN\nnRX0Q6sJJ2C7XslCFK1WKwlBsjVau8j41IGCSU5O/d1uNwqFAhKJhCTUyGjJ+hobG0UaWbNmDQ4+\n+GAEAgFoNBpYLBbU1dWJ3JHJZLBhwwa43W706NFDpBm73S7gYDAY4HA4xHtdKBTgcDhgMpmkypDT\ndDJ1m81WVnVHICUY8riphxPkPB4PMpmMJPiy2axUVTJZSsAjs+Q5oxuH2j7ZNEvgOfiQwbNalAOT\n+l00NDTgoIMOgkajwdatW6UXSywWk/cmkw8EAmhoaJAZkOrwUP37KlATXCkZETRVG5cK/GqxjaqN\n85pRf9RWA9yesbOEZaWMx2tXLd5Rqy+rsW9Ftwbsnj17iubMi5TsjUnAbDaLRCIhzJs3k2qnAyCM\nN5lMoqamRmxryWQS0WhUbhbauuLxuDgwWltbBUDJUgmQlD2ozbLAg5oy/cnHHXccMpkMfvjDH4p1\nUC3B1mq16NevH0wmk1gCqUd7PB75PEzcEfQLhYKUlwPlwNDW1ga/3y8WNE7n+TmY1AQg1YmUU9Lp\nNDQajbB+2gfVxlbcv9FoLJtx0NYGbAc7gjjPX6lUQiaTEbmEBStsFkUGreYuUqkUNm/eDIvFIswz\nn88jFArB7/fL/ugR31myjixbdWzQLqgyYLU4iwOd6kLhOec5zWQyAtbqTI9AW+nl7SoZqZIEVdpR\nKye78pFXY9+Ibg3YdXV1ZZYqXrgEsmQyKYyWN5J64zBUNuT1ehGNRtHR0YH169cDgIAMg5Y4VsYB\nnb0H2trahLlzG1reIpEI6uvrEY/HYbfbUVtbK4mvXr16oVgsorGxUTRmvV6PSCQCo9Eo1j715i4W\ni1JRWCqV5PlEIiHsSrU1sixeHdD8fr+ADpOUarKW03dqx2qVII+Bz/M4qH3zeYKH0+kUIOdshOeI\nwKNWgHIb+rL5WpUVA9sTcU1NTUgmk4jFYuK84evS6TQikQgMBgOCwSB69OhR5sHncaoOEDJtylWq\n/KFa8iqlC7VaVmXpnH2lUikpxCKg87VdgawK2vwu1X1wNkKfvCrbVGPfi249TNfU1Ihk4PV6xX/s\ndDrh8Xjg9XrhdrvhdDolcVeptaoJI6PRiHg8LgUxfr9fHCG0aNE7HIlEpIjl4IMPRjablew/HyfL\nZaUg7W8Wi0U04IaGBpm2s9w8l8shHA7L4wQysie1uo+gxONkeTdvZg4uZKrqAFYqlaSCkEDKm59O\nB7PZLMwb2M46ycipS6uAREmGbhECIl0j1LRjsRicTqe4ZVS3BJtB8bPTRkj2TLbPz+j3+9GrVy8c\ndNBB4krJ5/NwuVwyu9mwYQM++eQTfPnll2XSggpwKoNWtWc1H0KJI5vNSjEMv/t4PI5kMim/E4mE\nFM6QRKRSKSENHARUW6JKQjib4Dmo/K1eG5yl0B2zL8Xq1atx2GGHSQ+c3//+919r+5EjR+KRRx75\nlo5u1zF58mRce+21ALpeJWd3o1szbHp/1aQNs/FkimSLTASpOi6DYJ3JZOBwOKTVKV0baukyE1lW\nq1WmusFgEIlEArFYDA0NDYjFYiKXFAoF+Hw+xGIxcX3Q+0zPNHXifD6PVCqFUqkk/UPILpkEZKc9\nasx0VVgsFrhcLulORzADOv3qZMEcrGjJo26sJsEoR2g0GpEl+LlVfZvnm6yd1YWq57xSOigUCrDb\n7WXfFQtzeLwciHgOWQaugjnZLd0n2WwWXq8XvXr1wsaNG7F161bxYFOCYkJy06ZNqK+vlzwDv1se\nK1k1dWc+pv5Pqx9/k3Hz/JEF8zNz3zyfHOTU16qJYJ4vNdTXqbOtSnfUvph45BJhK1euLHu8q/UR\nZ86cibVr15YB9CuvvPKdHWtX0ZUtc0+iWwM2b3xV0+PNRPcBn1cZYDQaLbsxOH0n6G/duhVffvml\ndIpLpVJyk6ie4UQigZqaGqTTabS1tcFgMKCjo0M0ZgBlyT+drrOvSCaTQd++feF0Ost0Znqmmehk\nlSDZPYGQWrDKlAmoLIYhIAMo68uczWbF191VNzkCOiUCdSZCFsi/VWmE76W6IywWSxlgE+TZa4RF\nMgRd1XLJfah6ONk+pR+CLQecfD6PhoYGHHbYYZJoJogmk0npA75u3Tr4/X5pN6vaPwEIkGYyGSkC\n4vOqvKG6XypL2/kZAJTlBuhUUoFfTXh2lWRUz4d6ftTKXJWV8+/uFNUlwnYde8Pj3q0lEXW6yCki\n21pSXmCDIfqa2SOEod5UZOxGo1FkFQJpsViE1+uV8mRKDIlEQrrkUTdVnSTA9j7OlGPoiiDrY2Ui\nGyU5nc6y6sRKaUH1lDO5SkBg+XgoFJLnAJRNufnelGzUIpdsNot4PC6aNaULdepNkFF7s6jtT1Xv\nO88x98HimGw2C6PRWAaYnIGQRYfDYeltwspIDmJcOQeAsHtWM9bX16O5ubls9RrOFux2OyKRCFav\nXl3Wf1vtFVLp6KC0of6oORK1kpGOFlpJVRlE1a53poGr16UK1pW/K5/n4NVVheS3HaXSrpcI+9Ep\nQ3Fb6A3MXvEUDj7y8OoSYd/SEmHdGrArGYXqFFE7pxmNRmlERNCp9NtyymqxWJBKpaS6kWDCnhp8\nPUvZ1cQRfyqnrrTWcdDggBKNRqWVKduKkr0BkK5uKnMGIAlEgmapVBIXBl0aFosFNptNtGgCGguA\nCCbstEdgIpOjs8RsNqOpqQkABJAqvciUa9SkmDot5zlk4jaZTIo0RcmKgyKZOfuKcxBMp9MyAPA7\nBsqZJ/3g9fX16NevH/r37y8FQZw9sUshe8NwUK2sGFStcyqr5sCkyiccYDhQqbMW9Rrje6n72pWb\ng6Bc+TqVaHCG1dX+vu0olUo4+9yJOPe6y/H7lpfx8/+ehGtm/q7sNb+65iqY7hoL2+9OgfXu05Ac\n3FjWqQ7oXCKsaf/esPvc+OlZp+9WlSZjyZIlOP7443H33XcjFouJhMglwhobGyUZfdZZZ+Hqq6/G\nmWeeiVgsJkt0VUoSy5cvx8CBAxEIBHDVVVfJ6jNA5xJhRx99NILBIGbOnIlHH310t+SMUaNGYc2a\nNWhvb8fhhx+O8ePH7/Zn3N3o1oCtAqQKmCqbVBl4ZTUZsP3CVqeQXJ3EYrGIL5ieY4IQBwKdTicL\nArB/BBOXanKT9jdq2alUCi6XS/RzgjsTfgQ8MnkubACgTAvlTe/xeOB2u6WUWwVVDjRut1tAnUU5\nlX0vCJhMQFYyemC7dEFwplTB86tO14Ht7WRZBWm326UKk4swUC7RarUiq1DScDgc8Hq98n1wNRx1\nsGYykkyqsbERjY2NsNvtcgxkoS6XS3IDPM8c+FRPP/VhlRHz86vng1JZpTzHgYqvqayi/CqGXXl9\nqvtXXSqnmLJ5AAAgAElEQVTqOe5Kjvm248MPP8RLSxbB8vJUWK8fCcsr5+HWubfJrBMAYtEodL22\nLxFW7OVCMFK+RNiE86cg/cdTYPvnJVha2oAJ5035Rsf1VQVIu3PeuUSYRqPBxIkTsXXrVrS1tWHj\nxo1YsWIFZs2aBb3+6y8RxrqHGTNm4MMPP/xaA9PuxPcCsCuBWvWmqtN2FcT4W72wyXLVwgZqjrSa\ncTtq29SE1aQnC1hyuRzq6uoE9IxGo/i16Y7g8ZL58j3Uzm8qo+Z0W2VVFosFer0eoVBIwFutRrTZ\nbGJ7o+VQ7Y9BbZsDHO1/ZN3chq4RnU5XVunI5v8ELoIWAZKyB4tl6Cxh+TwZMItu2L9E9YZTS9Zq\nO9dp5OyBMxeCPJ0y7KbG/ioE0Gw2i0AgINIMfeUAhHVXShBqglAtKVf/52vU88oBlY+rbJnnaGeh\ngor6e2fAQCkK2HHtz28zAoEATD290Fg7C9Z0tXYY3Z1LhDFOHT0GuWsXIr8hiOy/WlB8YAXGjBot\nzy9evBj60w6B6dj9oKtzwDx7BF5dsPA7Of6dxc6WCNuyZUuXS4TtKorFIn79619LP5s+ffoAwF6V\nhoDvCWDvTOOrfF6dMnaVrCQgAigrGef0myDKhCW1WZvNJtvlcjn4fD60tLTAZrOhvb1d3Bvcf21t\nLdxut4CcysJUxq/X66VgRf3M6mom6hSc5exsHkWWaDQasW3bNgDbE2AczNgMibMK7pvgS72e2xGY\n1JVcGJwBELTJ0lUXBY9BfR11fCYvE4mEyBu0a7pcLmHRlHzIuOm4ofTF5K7f70fv3r0lN8BZTHt7\nO3K5HFauXFnWFpeDIM8zQ00WplKpMn1blUUI4JSOKkGcTF1NYgIomyGqMlPldc1rWB301POpyjDf\nlSQyaNAgFNZ2IPXcShSjaSTvfQsuo7VsibA/3nQLTh94PAo/eQCWSxfivlvu2GGJMM26kBxzfl0H\n7K7uv0QYY+PGjbvcTl0iLBKJoKWlBcCu1+z8utGtARvY/VWl1WkkwUed2gMQpsi2ngQ92tnIJsma\nAOxQoca+Iy6XC9FoVNgsmaR6UzKpR42bOi1dLvx8qiZOzZeAygIaggIlB5fLJYNBIpGQ2QMtgbxo\nySpVLZvuGp4z1Z1BlkuGrXq4VV2XrJmDhurkUJOB6qozDB4btUjVGkfAZPKXrJ95AM4E2D/F5/Oh\nqampLDGt0WiwceNGJBIJrFq1SrofqtcLgwDMHwJw5QxFBdLK64zfKX+6mq5X6uZ8nt8Df3e1bVd6\n+XcF2F6vF6/+fT68t3+A0A/moPnvW/D6/B2XCPvzXfcg8OU2bFq9DmeffXbZe4wfPx717UB6wuNI\nzpyP9MQncOcfbtvjY1I/v7pEGMPv92P9+vV7dI7UJcJyuRyWLVuGl156aZc49F0tEdbtAXtXoZ5I\nAp2qC/I1BIVsNostW7aIrluZFCPoApCkHG9EALLqCPVXr9crUgDtdY2NjVJIQfsd9W7KI5QlKuUH\n1dOr0XT27M7n8zJNo9+a8gj7d1Aro4ZutVplXUb6na1Wq9gP+T+dGPwMlHDU/iPUv9VkIM+tqgHr\n9XopHCJzJ0tkclT1Iqt+evWzcfbBAZUgrdVqy5K3BoMBPXr0QF1dnbSmZeLXYrHITEeVTBjcP5tH\n0eWhNhCr/FG17Uogr/y/Uubo6nEVrLtKKHJblY1XynzfRRxxxBFY+/FnyCRS+HDZCuy///5fa3ur\n1YoV/1iGOaf+N66qH4Ylf1+AcePG7fHxqOdDXSLM6/WitbUVp59+OoDO3vNHHHHEV26vPsZ47LHH\nsGzZMvh8Plx77bUYN26c9DDaWUycOBHNzc1oamrCQQcdhGOOOWaHnMPeyEF0637Ymzdv3kEG4UWv\nZu9TqRRisRi2bduG9evXY926dVJ2rjYaAjovntWrV6O1tVV6kFDfZU9mYLuVjA6JdDotjFdtgESr\nYKlUgs/ng9PpFCCnk4N6M7djUsxqtUqxD3VrMjaTySTAw+pLNjnizU12T6kkEolIZSM7A9psnXqj\nx+MR+yHZvTpQZDKZsvdX7Xy8WAmmqmuCkgwTj/zNz8JEK5NmTLQyl6Am7vidajQaAWsOBqpmHI/H\ny3pQr1+/HsuWLcPmzZvlHKfTaTgcDhx99NHo3bu3gDylBurmoVAI69atk8GD3nR1VqWCJX+r1y8B\nXp3tqYy5UoZRZ2Hq+3elgXOgUm2X/Hn55Zf32r32dV+7L0V1ibDdjN2RQ/i78gZQs/hk13q9XvQp\njUYjcgEteOwFrSb9OJ0n62NyUS3CoPOCU3n2BmGrUQIZwZx9q9V+J6rLQC2eIQOsr68XJshOeVwP\nke4U6tatra1oaGhAOp1GPB6H3+9HIpGA1+uV0nI6YtLpNHw+H0KhkAA498/EncqmCWTUk1m5CUBm\nGfSVd8XGORioIKy6TzhIUppas2YNrrnmGplxDBo0CJdddhl+//vfY82aNeL+GDBggBwr/drpdBrv\nvPMOamtr4XA4yq4bVdao1Ia7kjIqJQr1euPAon6PO7vh1GtUldAq8yaVDFxNiFfj243uvETYN5JE\nevfujUMOOQSDBg2SVZCDwSCGDRuG/v37Y/jw4QiHw7t4l52HmuxRbzL1t6o3quyTbIlgzYVuqfdy\nqqxqyaxw5GNsu0qnBplPLBaTZBjtd+oKNdQx6W4g46aFkADF/XPGQFYKQJJrBDha3bhyudPphM1m\nk/PE0nt2riuVtpezZzIZKRICOn3SdrsdWq0WtbW1ohezayCwvRBHPaccUNTmUcCOvaQpc2g0GpGU\n1O+Tf3Pw+uSTTzBq1CgMGzYMQ4cOxW9/+1vZngv85vN5zJ49G++//z5WrlwpgE4A4wILhUIBGzdu\nxMcff4w1a9aULZysJhJ53JII+1/5Rp29qYOKmoBUk46Vdkh+rkqbYFcaZqV+rSbK1d98X27D463G\ntxOtra048cQT4XA4cOmll5YtEeZwOHb4Ofjgg7+zY/tGgK3RaLB06VJ88MEHWL58OQDgxhtvxLBh\nw/D555/jpJNOwo033rjH768C9c40RAI2rXnqDVN5o6xdu1YqHAEIQ6WLQU0UMsmmsh+CJvtPk9Fm\nMhk0NjaKnY/sjpILsH0ZMLXcmKydf+t0OkkokuXa7XZxkhAoWWjy5Zdfwm63yyDQu3dvOBwOKQln\ncHDhdJ9MtFQqSZKP0gbBQ+3nrHbzI2ABkAGRIK6CFL+HWCwm4KPqvZy9MIF41VVXYfHixXjyySfx\n9ttv41//+he02s4mW21tbdBqtfB6vbDb7di8eTO0Wi169OiBP//5z5gzZw5aWlpEukqn0+jRowdO\nPvlkDB48WGQQ9bpRfzirUisYK5OOfB3llK707a606q8TO3ONqLmZrpKS1di7MXr06LKk9aRJkwB0\nJk9jsdgOP9/Veo7AXkg6Vl44L774onzASZMm4fnnn9/j997dzLx6o/HGpP6nWsuoGfM1XOiAGjK7\n4BGwAQgrVhOPpdL2Yg+NRoPa2lpZeZ0LyhYKnU2h2A6VLglKBQRodSrN/ys9vblcrmzNQ1rYLBYL\nisXOKk2XyyUaNQcSgj0HHdXLTo1bLdOm9Y52OjI8lrJz9qHRaMoGNQAiI3Hw4SCnuktoBeQMhvs+\n4IAD8KMf/QgAJA+wYcMGlEolzJ49G9OmTQMAWUl9+PDhsFqt+PLLL3H++efj5ptvlj7koVAINTU1\n0ryLK8RXNnP6qr9VC1/l/5UJxko5RbXz7QlwV8p8ZNhqUvK78mBXo/vFN9KwNRoNhg4dCp1Ohwsu\nuADnnXcetm3bJs3kuXjtnoYKZmRovFF4sxOs1ZaWZH6qJqyyWAKUWhrO9qlsXMT9sNteJBIR6x7B\nPBaLweFwIBaLwefzCfBzKk/dlYUpFotFtGY1IcVKRRaXqG4MyjJ6vV6qBplo5KLBqVRKXscBxmg0\nIhwOixWODD2Xy0kFJDVqluVzP5RxgO2dDgnAfB8231KlJ55zVY+lRq3RaPDRRx/h8ssvF6188ODB\nuO6663DRRRdh9erVACDFL6NHj8b9998Pp9OJI488EqVSCXPnzsXYsWNht9tx/vnnS9XjL3/5S8Tj\ncfzwhz/EBx98gHg8jvb2dqxZswbRaBTHHHOMJDorAVddbEAlBqrDSJ01qFJQJTCroKqeh90N1RHC\nAbtQKMgMiu/7XbtEqtF94hsB9j//+U80NDSgvb0dw4YNw8CBA8ue78o+w5g5c6b8PWTIEAwZMmSH\n11TqdsD2whC1IQ+nwWqjHk67ecNQe1ZXSeHftPhls1mx4XE7ulDUZCD1bp/Ph0AggLq6OgFOoHNh\nWU6h3W63+JxVpwjdF6wGZLMkVQe+9NJL0dbWBr1ej7/97W8wmUxYsmQJ7r77bmFfFosF4XAYer0e\nixYtgsViwZtvvokZM2agUOjsIvjUU0/B7XaLLs5+DASUVColbhQOMkyMEti5AAK1bpU985hVrVqd\n5XB2YbVacdlll+Hkk09GMBjE2LFjsWzZMlx33XWoq6tDa2srzjjjDFn38vnnn8fDDz8sgHjggQdK\nz4f99tsPmUwGwWBQJJO+ffvKoHHwwQejvb0d7777Lg477DDpoa3OzCp1atVNxPPL60/Vo/nZvip5\nqerSXUVXz1XeL2qxDWdOqq7dVSxduhRLly7t8rlqfP/jGwF2Q0MDgM7KvrFjx2L58uXw+/1obW1F\nfX09tm7dirq6ui63VQF7Z8EbXWUdlW0saemLxWLSXU1l2SrzY+P3cDiMVCol4ANAwEpNvKksmP1G\n6DZwuVwIh8NwuVxIpVKiV7e1tYl5nrpuKBSC2+3eoZ8FQZMODiYsuQDC6NGj4XQ6ceeddyKVSsFs\nNmPevHkYP348Ro0ahfnz5+Phhx/GzJkzcf3118vn+d3vfoeLL74Yp59+OubMmYPLL78cDz30EIrF\nopTaRyIReL1eOVdMWtKhYbPZxDnDgVDt5Kf2Iae9jyDFAZDnmOe/d+/e6Nmzp2j9TqcT69evx9FH\nH41UKoVzzz0XTqcTDQ0N+Pe//41MJoNx48YJWH700Ud4/PHHUSwW0aNHDxx11FG4/PLLpd2ty+WC\nwWCAz+dDKpVCr1690NrailAoJHJSZaJarUpUAVN1GKnXQiXQdpVIrIyuwJkMXN2uMtmoVup2ta+u\nopL8XHfddbvchuHxeKrsvRsEc2xdxR4DNjvBORwOJBIJLFq0CDNmzMCYMWPw0EMPYfr06XjooYfw\n05/+dE93IYxVTcbwhuNKIPF4XBZlTSQSoh/THcILX50C09qmMnFO07kNmx6lUik4nU5hl1xjkc/R\n6UF22adPHwQCAbjdbpFfWO3HMmk1SccpLx0qLN2uq6uTjmEApDWqxWJBIBCA2WxGMBiEx+NBc3Nz\nmf0snU7jzDPPRKFQwKBBg/DCCy9IAcFxxx2HOXPmoLW1FaNGjUIymYTVasXTTz8tC/yyaRNZJs8R\nveicYagLEqhMnLZBFazpJeb38sknnyAcDuPkk09GPp/HyJEjJfk5ffp0+P1+LFq0CC+++CLuvPNO\nAJ0g9+ijj0Lb4EJxa0SuE7fbjWuuuQZ6vR77778/1q1bh7q6OkQiEXledWNUhgrGwI4+aQYfV4Fb\nZdKVljw1KgH6m5RPA99O8ydea9XovrHHgL1t2zaMHTsWQOdUePz48Rg+fDiOOOIInHHGGbj//vvR\nu3dvPPXUU3t8cJQi1KAMwp7FBOxoNCqL6qp9AJgsAiCsUAV0erGpAfN19EC73W5J5jkcDrkxQ6FQ\nWaKPHeXa2tpQU1ODRCIhCT8yb+rh3Dc79ZHl0ctts9nEThiLxcqkhWnTpmHWrFn4+9//DgC47bbb\nJEHHabPVasU999yD8847Dy+99BIA4O2330Y4HMaIESOwfPlyzJs3D4cccghuv/12XHLJJbj88svx\n8MMPS4KNbJ0VnQDEZkjpQNXoeYwABLhVGUGj6Sx4MRgMaG9vx6WXXopx48bB5/PhueeeK5OIJk+e\n3Pnl6bU46OBDsGDBAowYMQJocML/zhXQWI0IX/E/SD3wLxgMBsTjcVx22WWAUQero9Pax5VJ+vbt\nK3IU/fOVtjuVxfK3yq4rpYrKv9WBoPLvSk2a12Tl9l83qkx434w9Buw+ffrssFwP0Nl7YPHixd/o\noBhqfwBVU2ZBiLrWHiUR2vtUOQPY7sLo1asXAoEA2tvb5b1pe2MwscSeGnQ1kH0zeRgOhyXxRQbu\ndDoFrJkAjEajZc37DQYDrr32Wlnx5q677oJGo8GVV16JeDwu+9LpdDKlLRaLiEQiuOWWW3D66afj\nggsuwF133YVrrrkGl156KQAIgM6ePRuzZs3C448/joEDBwqjp2Vw/fr1WL16NR599FE4HA5cfvnl\nGDdunOi4TCZS41c72VELJtCobWsJIqtXr8avfvUrmbUce+yxmDNnDi655BJ8/vnncg5OPfVUZLNZ\nDB8+HKNGjUI2m8Wk885FR2sb6jfNRjGUwmcj/oR58+Zh8ODBeL9XRrrGuW74CVIPvoO7774bF/7q\nEjiuGQ7zKQcg+fBy5B9ejh/0/4FUmzIpzF4yu5I1+NjOdOadAT3/VnMnu9Kyq1GNrxPdupcImbP6\nEwqFZPGBYDCIcDgskgjZLmUHtYKOj7HXBgCxx7HsF0BZ72o2NeJjlC5YeMJuc0ajEX6/X4Cevu5S\nqSQrfLMfBzXiH//4x5gypbMnMF0X119/Pe69917cd9996NOnDwYMGCDHlc1mZVV2bnf++eeL/g1A\nXDBHHXUUXn75ZSxevBi/+MUvZED6+OOPEQqFMHToUOTzefTp0wfvvPMOJk2ahHw+j8GDB+OKK66A\nVqvFH//4Rxx//PEYPHgwXn/9demHApSvbsN8AnXhYrGzpP/KK6/E4sWL8dRTT+Gf//wn3n77bRx3\n3HGora1Fv3790K9fP8yaNQuJREIKYfL5PDra2qH1O6AxG6BrcML238dhxUcrcfjhhyO98FMUNncW\nYiUfeAcGpxXLly+HrqcH9v93AvT96+CYPQow6WQtS4/HI7ZMzhAqnSLqoA6UJxxVW6nKllVvOaOS\nUROs1QZk6n4qE4yVz6vyi3od87lq7HvRrUvTyTbVi5P2O3bbo8tDbRGq3ihqll2r7ey1/NFHH8Fo\nNCKZTEq/ZPaFpldYXZ/Q4/EgmUwKY2fxCRspcTUYJhrZwJ/uC0oEBAaj0YgTTzwRa9asAYAyyYba\neUtLC2bNmiXaOFeaMZlMePnll3HGGWfgySefLOv5nM/n8dFHH2Hz5s34yU9+gkwmgxtuuAEnn3wy\nNm/ejEsuuQTjx4+XxCk/669//Wv89re/xTPPPIPTTjsN//jHP3DsscfiqKOOwsyZM8u69QEQbZ6f\npdIj3NDQgP79+8siDk6nE2vXroXdbkdrayuCwaCA+6mnnirHotfrgUIJlnOOku89+84GuB1OjBw5\nEsvefRfvHvEHaCxGaPNFXHP59M5lwMJJlHIFaAw6lOJZlFKdx0brJxPKapK0MuFYmXTkMe2KIe/M\nZre7jLorOWZ3t6vGvhfdGrDVZA6DNxABmqyDHlvVyaC+BzvCsUounU6XWdjUZkxMnAHYQSrhe7EH\nRzKZhN/vx6ZNm6T1KWUbsmOV4XF/7GjH59XPsnDhQhgMBtx+++3o6OhAqVTCmDFjAIMOpUIBd955\nJ+655x5pKXrxxRejVCph6NChgLFzULj11luh0+lwwAEH4KKLLsLpp5+OY445BhdffLGcr88//xwH\nHnigDChcb/LLL7/EaaedtsOqNADKfOOUeCoTvBystFotnnnmGYTDYYwZMwZ2ux1nnHEGMpkMhgwZ\nAsORzfC9ciFy721C8Gd/wYxrZiCVSuH3t96EwkdbUGxPoPR5O66+734YDAbcMGuWrArSv39/YZ4P\nPvkYgqf+GaZRByL9t/dRV+uHx+MpG3SZv1AHfzXRqIJypVuD3/1XXaPc7quuXTW60sF39lO5XZVd\n77vRrSUReoPZzJ6AaLPZ4HA4BPS4HJVa6s3g30woMilZKBSE/VKvpaODibd8Pi9FM5RETCaTJAR5\nbKFQCGazWYplVAcJfeGlUkl+c7+qK4Fsz+VyYcGCBTj00EPxl7/8BfPnz8djjz0GjcUA5w0/gX/1\n7+D8w09RNGrxxBNP4IUXXsBrr72GQw4/DKZhB6B+02zUb74eljN+iKb9mjF37lxMmTIF9fX1+O1v\nf4tf/+Y3GH3GaTAYDbjtttsQCoVw++23Y+DAgWhtbUU4HMbQoUNlAOTsRD2/qlecQKayfP4dDAbx\n5z//GePHj5dy+0KhIJWLNQsugkarhfHIZhiP7oN//etfOOmkk/Cn2+7AUP1+GNPnSDzxwMPw+/2S\nn3C73RgwYIAAai6Xw323340j9Y3wPvwZhvUehL899IgcIwcdnn9gx5anKkDTclkJ2upz/KmUOr5u\ndEVG1MdUH/jO9PJq7FvRrRk2bzagvNqR5d5q2bN6A6lAot6Q4XBYkpPsuUFfMisA1eIQVgiqq9No\nNJ0Njerr68se8/l80Gq10gOb4ETtmoU0rIy02+0iJdD54nA4EI1G0draissuu0wY4cqVK6GtdcA6\n5WgAgG3qMUjc+SY++OADDBkyBOl0Ghu2bYXlv38Mjb4TqCzjBqF96TNYsGABtmzZAqPRiKHDhgEo\nwTTiByjtb8V7i9+TMu+5c+fiwgsvxBlnnAG32y2sG9je5J/aNZ0vagKPVZKslCwWi5g8eTL+67/+\nC9OmTZMB6oYbbsDatWsBnQa51dtgGOBHKZ1DflUreo0dCqCzx/GAAQNEc6acwe9abRXAgWTGjBky\nGPbs2VMej0aj8Hg8MgNQe83wulABmGDNaw7Ysc/6zqIyUbk7THhnLHpnz6v3QTX2vejWgK0yHQZv\nWNruWFpOsCADVG9KJhDD4TDC4TBsNpus16iuFEPZwul0IhqNlrEqAFJUw6b/gUAAXq8XmUxGVrnw\n+XwiG7BpEgCRCehfVlcJLxQKuOfP92H1xrUopjun783NzeI2sVgsKATiKEbT0DrNKEbTKIYS0gdb\no9Gg0VuLlv/5COZTDwG0GqT/5yN4HW78/Oc/x5gxYxCLxTB67KnwfzEDWken3bBj8Fyc9+OfYeLE\niTjllFNw5JFH4sILL0ShUJBeI5SAKN/Qd04HTeXyamazGclkEueccw78fj9uueUWvPbaa3jzzTex\ndetWfPLJJ3jggQfwxJNP4pWT74b5xIHIrtyEGoOjU/b531BnHWy2xWNJJBJly6vRl88qUq6BqdF0\nLsirWgw5yBOEaedUG1qpnm3V/tdVbxBVZulK/+Y5U5/nOVTZu3q9VyY3KWF1lZisxr4V3RqwCRjq\nhap2XaMXmADNzD/ZIJOEvEHr6upQX18vDev53izY4E0SCASEQfK9uDYik49kzhwkgsGgVPcxKVko\nFAQwIpGIrPDNVqGhUOc6dxdccAE0bgu8j09GaNIjyAYTeOONNzBkyBBotVocdthhaPI3ovXEO2Aa\ncSDS8z9Fc1MvHHvsscJmZ8+YiYkXTEXbQTdAo9dBl8jhjr8+LOcgHo8DWg005u3tZLW2zl7fp512\nmoArGS0bS/G1BDE1kcpzpDLRfD6PF198UVj9Mccc0zmgDvAjv7qzrwzLy2ucThyeqUevk4/C+PHj\n5fyrbU7VxKCaDCYIcpBlGb3VakU6nUbPnj2xbt06sVPyc6g9Q+hyqampEQmM75lKpaRIi8ehsnyg\nHIh3xqZVQO/Kn834Kk27Mqpgve9Gt15x5vXXX9/hwi2VSkgmk4hGo1KKnk6npTw9Go0iHo9L21Qy\nFLPZDK1Wi9bWVmQyGfFus3gmHo+Ljs2S7Ww2C6fTKcUs2WwW7e3t6NevH6xWqwC9z+eDRqORpkn8\nu0+fPrDb7VKGTqZns9kEfIxGI86/dBq8r1wIw4Gdpf6x3y9E/ctf4vrrZolEY7Va8dBDD2H9+vXo\n378/pk6dKgMZQapUKuHtt99GOp3GiSeeKPukq+OUsWOQ+68m2C4ajOwba5G4YynOO2cK5s2bJ0U+\nsvaiBkBp+/fldDqxYMECSeAR9FT5Cdjuk2fJ/gnDfoyahRfDcEgTStk8Oo6di8kn/RSTJk0SgKf0\nBGz3n7M5l5oY5Co1ZNXsglgoFNDU1IRQKASj0YimpibMmzcPq1atwkEHHVQmdaiSCIFY7WFOQGee\nQ12Yl64k9bU7s9mp163K6NXENV+nlqCrf6sMmzZKVbKZP3/+XrvXqvH9iG7NsNnisxKwAQhYqNWL\nvJnY90ItM+eUl1a8WCyGfD4Pj8eDjo4O8Riz3wZ1Uq7wzTL2UqkEq9UqDZSYeGSRj8fjQVtbG6xW\nqyzRlUwmy6bilHS2L0KrRSmSls9dDKVQKmxf0YYWxPPPPx+pVEqaOPHz0hljMBhw/PHHl8lFBDmL\nxYIn/voQLrrsl2gd/yhsFiv+eOMtGDRoECZPnoxisYhxkyagY4AN7nlnohhMIDDiHpzxoxG49NJL\nywqR1P7ZKgNle9ba2lqxWiJfhP6gzoFIY9TD8INGbN26VeyQXNGHgwuTw2TM/J4JopzZVFr02AJW\nr9cjlUqhrq4O69evlx7j3Eb1NZNB0+1CIGbyuVTqrJDkMcbjcZHFOAtgqMCozgq7cn1UgnJXj6vb\nV/6ugvC+G90asAlolRo2k0vA9guZbIheZm6n2voymQxqamqwZcsWsfR1dHSII4LgxwQgk4hqIym3\n2y29MpxOpwA7gTyTyZQV1LBFK/3harc7rbZzUdnjDj8K/5j4COxXDUXhyxBSf1uB8Vf+pgysCBL8\nvPF4XJg6y67V5BiTf3wcABobG/H0I4+XgTnPAwBsbd8Gz4MXQGMxQNfkhvXCwVj2yLv4f4Xtq6Tz\nnKvAZ7VaEY/HhRHTl261WmF02hC/9XXYLz8R+Y+3Iv36Kvzod+NRKpXEAkntWbVjcqDid0jgrFyk\nQimtxyQAACAASURBVJV8jEYj4vG4rMjDalOuFsRBTpUoOMvh4ED2TumNCzWzapOFU5xF8ZpkdCVz\nfJUE0pX8sbu/q7HvRbcG7J1dxEwWcWrOXsesGFT9wwxOudvb2xEOh4XpUqtUHSnUaGnJc7lcAFCW\niOMUlVN0rnbidrulE51axs2ZgNlsBrC9mi4cDuOcCRNQu6AGb/7pXzDp9bho2q+w//77y7bUiwFI\n7wyyWPW4mYAla6QFUaPpdLZwoODUmoMLX280GJD7cDMMB9R3gtm7m1Dj6uwcxoEDgDB4tRUp7ZCq\ne6RUKuHOm27F/5t+OVr/8Co0Bh3O/NnpOPHEE0UO4SBAdqzOmCghEZT5v9VqRSgUktXg1ePjgOF0\nOmUVd/ZwUYFeXSxC7ZPNmRQHBnXhWwCyOj2ToJSigPI1K1VdXx1I+ZwqJfFa4D4YlV7uyiRlNfa9\n6PaArf4GyrXCrrywaqZd3ZaaIbVJViZyysypLhNRnCazdSfZFNkWWV1dXR1MJhPC4TC8Xi8cDgc8\nHo84F7RarUyvycbpuiBL1ul0mDJlCsaOHSs2NC4+wJL0RCIBAJJkpP5OEFAXFqCOzBV0LBYLIpGI\ngCMZJeUah8OBbDaLyy6Yhhuu+AMyr3yKYlsMpdXt+PVfH97BIUKbHcHKbrfL+0QiESn5LxQKOOqo\no/D2a28Ik6+05PFvSkaUf2g3XLhwobDgq666CsuWLcP9998Pv98vMpTB0LlifGNjo+QnjEYjfD6f\nrN/JXAX7iQDb12Dkd03AVmWeShBVBwh+JiaiCfx8nlHpBNnZdd7V41VwroYa3RqwaXtT7Xld9W7o\nKltfycjJVv1+P0wmE7Zs2QKNRoNIJCI3Hqfg1E8dDoe0MmVr0ZqaGkQiEWGtpVJJHCAs6OE+Ka9w\n6k1GTFZLRpnL5RAMBgWM2dVObadK9qweJ7B9wVuuMcmkIf8m86fFkAMSgZe9t7VaLcaPH48BAwbg\n6aefhrm3GVNnT5XWpCqokQGzux4HA74vwZE6NsGZDJgyx+DBg2G1WrFkyRJMnjwZn332GTSazuIb\n7pda/4oVK/Dpp59Cp9PJUmyUtIxGI9xuNxKJhGjdTqcTyWQSLpdLVvGh557nkbMzSk7qOSWYq/KP\n2mGRhVd01VSuOK/O8Crteqq8VHmtdvXYV8km1di34nsB2OrFykQTsJ0hkRHxh6DAbQHsIHm43W5s\n27ZNprButxvBYLCsIi+fz8sajblcDj6fT25WLiVmMBikax/9y2TV6jRXq9UK+ESjUdTU1KCjo6OM\n4bGFazweF6taKBSSrn+hUAg2m016Y1AiyGQysNlsZSBSLBaF4RNImVglyyXz54CYTqdxwAEHYObM\nmQJmBJhcLiefpdLKZzKZxFVjt9uFeWu1nct9EczVZlzTp08XD7tOp8PNN98Ml8uFVatWYerUqbIP\nDhZXX301pk+fjmuvvVYSvZSL1O6I6XQaNptNNHS18pKDEwcOtX83i5cI1pxxVbZjJbCTrXOAUpOg\n/N7VQq6upD2eCzVPoUZXIF1l3ft2dGvAJmBUXqS8MZgcqgTrSu0PgBRW0FfNakPawpLJJHr06IFE\nIiGsi1WJhUJB1qkkm+rbt690mONiBV6vVxJolAyATrcLpQrKAtSAbTabJD75Gia8yEzVFdcpGQCd\njpREIiHtXXluVIbHz0HLHuUNq9Uq23IbDoScjRCo2feb55ZsnW4RauOqX5rFLQRIhslkwsqVK7Fy\n5Uqcd955eOCBB6DRaOD1elEsFnHllVeiT58+SCQS0uZ17ty5cDqduO666+Q7Pv/88/Hxxx8LU/35\nz3+OcePGyWzKbrejrq5O5CL2NVdlCxIADiTqtUPdmp+LuQfmPuhw4eOcqanOJA4GldZHylgquJPN\ncx/qa9XH1GR6Nfa96NaATSuemmxR7VhcgFddx7HyxiMjYtKOQON0OqV7HNdEJDg7nU5h1cViEfX1\n9bDZbGI7Y3UkpRP2XaYOy99kgbTVARBmS4Ycj8eF3apgT7anSgq0I3K7SZMmyfno168f5s6di7PO\nOguRSEQ+J9DJqAcOHIi//e1vePbZZzFnzhxhsL/5zW8wevRomaWQoROMAYhNEkAZk1QTaVwWjEyb\nobJMetenT5+O6dOnywonPM+jR49GW1sbgsEgzjrrLPz973/HqlWr8Oijj2LAgAHSq+Wzzz5DKpXC\noYceiiuvvFLkGZfLhXg8Lp57u90uCeBKWx+T0GpSkMdJyYLnjwNlJRFQzxG1bA5sKuhzdrczSY9J\ndHXmqJ5bMnTVh10F7H0zujVgU15Qy3IJFuqK6WoxBVlvpZxCwOHfhUJB+mir4ObxeMr0S7vdLt5e\nl8sliTqr1Sr6KXVp3uS86VUvOI9Jo9GUeanT6XSZnsrXUx9nhR1vfL5HTU0N7r//fpFCJkyYgJdf\nfhnPPfccgE4gmjhxIjweD2655RaccsopePzxx3HHHXdg6tSp+MUvfoF7770Xt9xyC37605/KzIOA\nRxcEPxNXVq8EFUo5lB8qz7HaLCqVSmHevHlwOByylBywfaFjr9eLjo4O5PN5PPLIIwCAX/ziF8hk\nMvjoo4/kupgxYwb8fj9KpRK++OILsS9yYCwUCqivr4fH44HVasXkyZOxZcsW6PV6PPvssyJv3Hzz\nzXjvvfcAAD179sTVV19dVgmpgmIlAeDfzEOoNlN1ZsjnybL5/vxe1eB1wNepzJ/HoMp91dj3olsD\nNj21ld3TqC9TnmC1I1egYRJRvblU3RUobxNKFlxTU4NMJlPW1Y3SAZ0WAODz+eR5n89XVkBClkw5\nQT1uHgMTY7yhydori0bU5kalUknYG3V0Dia8oXv16iXAYTAYsG7dOsybN09mHrW1tSLBZDIZ0d7J\nFIPBoAAvvePUnilt/Pvf/8Yvf/lLSbINHjwYN910E0aOHIlQKCSApdPp8Oqrr8rMhnLEe++9h5aW\nFhx22GFynsaMGYPzzjsPkyZNQjKZxKpVq/DMM8/AaDTi6KOPxptvvoljjjkGGo0GS5YswYQJE7B0\n6VKsWbMGs2fPhtvtxpQpU7B69WocccQRyGazCAQCiEajaG5uxs9+9jPY7Xbccsst8pmef/55/Pvf\n/8bdd98NrVaLTZs2SZK0spNipWShBgFUncGp8gUZMiUv5j/UUAcI1Rq4M12b+63GvhfdGrA5ZVZX\nhAG2JxtZxJBKpaRUPZVKlVXIAdvZkep3ZTmy0+lER0cHNBoNwuGwlJkzkZVMJiVZqNfrEQgEyqoX\nk8mkFLCokg1vLNVpUDmAUP+1WCyicwOQhRDIsJnUMxgM4gmnG4VLax1wwAE46aSTAHSC9YMPPgiD\nwYBp06Yhk8ng4IMPxpAhQ2C323H++efLWpsPPPCAnFNWKmo0mjLtmZ+N0sD06dMxfPhwtLW1YezY\nsXj99dfxzDPPiDtk0qRJsNlsACDnedSoUbBarXjqqadw0UUXYd26dXJe2tracMMNN2DIkCFSWg90\n5gsWLVoEaICOjg5s3LgRAPDYY4/B4/HgiiuuQC6Xw9NPP437778fF1xwAVpaWlBfXy/VjYVCASNH\njpTl7Ch1zZ8/HyeffLLkDOgqYV4EQJmOzeuokvHyHKlsuzKhqOrZlMzU9+P2qlxSCciVyceu7IHV\n+L8f3RqwW1tbhWGToQAo07C5EAFXoFFLhtUiBsoMvFmKxSKam5uxdu3asuQPW6Cy0ILTaurJTGoV\ni51d5NxuN9xut7wvWbU6peUxqY4KMjJKH7xZ6T5hebtGo8FFF10kN/f++++P2267DVarFb/5zW8E\n+FetWoVHHnkEo0ePhk6nw7PPPovDDz8cN954I9rb2zFhwgTcfvvteOCBB2TgcDgcmDZtGq644grc\neOONwtoffvhheL1eOS5q6sViEb1790bfvn3FQeN0OrF+/Xocd9xxkmhds2YNbr75ZtHlr732Wrjd\nbqRSKbS0tKBv374488wzcc+996KjvR0llFAqlrBkyZLtjBalzm7t+SKg0eDjjz+W68LpdOLss88W\nt8jxxx+Pp59+WpLJAwcOlCpV+sJZRckujfF4HCtXrsRLL70ErVaLUaNG4ZBDDikrnlELeVQWzB9V\nNlFlK15fPM98D5Utk21XWgdVqanSDqhGlWHvm9GtAbutrU2KTCqdD5RFqH9Sx1Y1VnbgMxgM6N+/\nP7xeL8LhsPQI2bp1K8xms8gE9PdaLBZpYMTyaQ4WZMN0eFA7JcOqnMaqRROUEQjcHGA0Go3YxOjm\nILO22Wy4/fbbxbY2depUzJ8/H5lMBu+//z4ee+wxdHR0YO7cuVi4cCGampqwbt06rF+/HieeeCLe\nf/992Gw27LfffvjnP/8JAJgyZQpsNhv+9Kc/IZ/P4/rrr8fZZ5+NMWPG4C9/+Quuvvpq3HfffQIU\nTCKq1rx8Po9PPvkE4XAYJ510kgAcpYyDDz4YGo0Gb731Fj766COMHj0a8+fPR7FYxJAhQ/DJJ5+g\nI9TRuUKO1QCNTgcUihgz5GR8/PHHWLt+HZAvAU4zGtZdh62+6Tj00EPR0tKCq6++Gul0Gna7Hfl8\nHitXrhRGbTKZsGLFChxxxBFwOBwIh8NS2ANAJLNisbOv+vTp07Fy5Uo899xzMhCREHBGQTar2kdV\np4kK2qy+5f8kHOrsSg3V/sjrluyc15I6Q+Q+q7Fvxi4B+9xzz8XLL7+Muro6YTnBYBDjxo3Dhg0b\n0Lt3bzz11FNwu90AgDlz5uCvf/0rdDod7rjjDgwfPnyPDy4cDkv1XqWOTS2SAFfJeqjtFotFeDwe\nSUZx9WxWAVKnZtc2p9OJWCwmQMWCF3qfCbpsm8qEk1rhxpuPhR/qTUhtMhaLiR+avbKpq9MiSKbF\nBRFaW1vlJn7iiScwaNAgtLS0oK2tDRs2bIDH48GiRYvQ0dEhU/MtW7agvb0dq1atgtfrhVarxRdf\nfIFevXqVsefa2lq0tLTgwAMPxKuvvoqWlhb4fD5phKS6GEqlEtrb23H55ZfjjDPOgM/nE6B74YUX\ncPjhhwPoLOO+5ZZbMHHiRGklG41GpQMeCiXAoodhgB+FdQHo+9Qhk8mgtbUV0GoBTQlaox7pVz4B\nAKxZswaJRAJXXXWVnGv6rS+88EIpcGJDL5fLhUAgAAAisyQSCZnh/OAHP0AsFkPfvn2h0WiwefNm\nWViCsyk2uVKvOxIGnotKqYI5BvUYVYatzqiA8l4kDPVarmTTVXa978YuAXvKlCm45JJLMHHiRHns\nxhtvxLBhw3DVVVfhpptuwo033ogbb7wRn376KZ588kl8+umn2Lx5M4YOHYrPP/98j7PaZEJqiTCB\nW2U5QLkeqBbP0N6l1Wpl5RgyM5Zts89GIBBAOBwWsGbxC33aHDhUeYTJNHWxAg4W9DNTv1Q7CtLy\nl8/npXFSTU2NMCu1p3exWMR5552HXC6HpqYmabb01ltv4a233pJzEBngwqJ/vA787yK0f/3rX+U5\njcOE6CE+FJd04M0335THhw4dijfeeAP/+Mc/MGLECLzyyiuS7Gxra5PzzaIh2tf+P3tvHh9ldfb/\nv2fPzGQmk8lOAgn7KqggoqKCa6tQcd/ZXOpSbYtVqT+tuKBWi3Vp5Vsfte5giygIrUtB0GJbquIG\ngqAQyJ7MTDJ7Mtvvj/E6OTMG28c+f/A85LxeeQVmJjP33Pe5P+c6n+tzfa758+czadIkLrvsMqXO\niMfj7N27l+uvvx6/388f/vAHHA4HRx55JGvWrFHXz2Qy0dbWBhkwGI0UzDyE8K/WkdjaROzIwXi9\nXpLt7XTH46R9ETqvXIbRaCQSjVDy56tJftlB1/UryNhMPPbwbzGZTEQiESKRiDqngIp2w+GwAuxw\nOMwbb7wBwD/+8Q/q6urYu3evAl6x5ZXzrqs8JKGcn5SEXtWMHlj0pSzJ56L1+dsXcMvQi336okj6\nx8Ex/iVgH3vssezZsyfnsdWrV7Nx40YA5syZw7Rp07jvvvtYtWoVF154IRaLhbq6OoYNG8bmzZuZ\nMmXKdzo43Q1NryaDXgmUbM91jaseyYgmN51O09TURCQSweFwUFxcTGVlperXKKAs21OJ3js6OpQO\nWegZAWyRHUoUpVfP5cve5HFJHsoC5HQ61d8Jby78tpSMNzU1cd1119HU1MSKFSt47733FAddXFzM\n7t27AfC+ejmx1Z/QuWAllnCSkpISfD4fCdJU7L4D3ym/wTyhmsxuPwO92Q45yWSS6dOn8+677/Lh\nhx8ycOBAIGuSJZG1fF+RKs6dO5fS0lJuvPFG7r77bva1NDFyyDAqKipwOBzU1tYqKV5TUxPz589X\nC+q9997LAw88wJYtW7LXqCtG6NYsmDscDhobG2loaOiNItMZylzFdKW7SJYWYJ1ch3VyHV0/eZm0\nxUR7eztDhgwhmUwqP+zKykpisZiinZYsWUIwGCSTybB48WIMrgLs844g8vgmtRs85JBDVK9OAWRZ\n1IUWkYVM5pge6eYXvujzUQdo+ZEFXEY+N66rQfoj7P4h4ztx2K2traryr6KigtbWbCeRpqamHHCu\nqamhsbHxOx+cRNfwzQy9nqjR+T0dwCXhFwwGSafTtLS0YDJlW4B1d3eTTCYpKyvDZrMRDAYZPXo0\nH3/8sdIVixeHFHwACswl2iooKFAJJF17rasB8tUh8j46T2mz2ZRHiUSDTqeTlpYWWltbcbvd1NXV\nMWjQIPbt24fNZmPChAls3rwZjAZIZ0h+2Y79B+OJv7iFxPodypCqNejPShc/bcb70jwCFz3DjBkz\n+M1vfkNraytz587l6KOPxuPxUF9fz2OPPaZ2A3KcUt6+ceNGWlpasFqtzJo1CwwGrNOGs6/+I9Jv\ntXP0UUepsu6FCxcqvfzGjRtZs2YNmQIL1/7keuKRCIsWLWLAgAH8+c9/Zt26dTz11FNkMhlWr17N\nypUrOeOMM1i+fDmhTA9pA6Sag6T9EXo+aoB0BmIJKisrKSgoUK3fioqKlBWr1Wqlp6eHa665hp6e\nHnbs2MHad9dR/uktGJ1WXDeeRNu4xUwePxG32608tfUIG8jRkutRt74Y6+Cs51vk+vfFXefvCHVA\n7ysSz5/7/ePgG/9x0vFfbc/299yiRYvUv6dNm8a0adO+8RoBi74SLvnbRx2w5TW665rD4aCoqIiS\nkhJVMh2NRpW50+DBgzEas3anu3btyvGtDgaDVFRUKICWIhnhq/MLHHRVhV5AIhFVfpWdyPuk07pw\n221tbTQ2NqpozmQy0dDQwPDhw6moqOCvf/0rF154Ic8vexHIYB5aRmJ7K91/+5JMKsXMmTNpb2+n\n9b1NJL/sgESKyDP/wFXkZtCgQQCMHDmSnp4eqqqqMJlMvPDCCxx++OFKCy7GUXLOTzvtNKZPn857\n773Hr597nPJPfo7BYiId6qZt9F2cffbZOeXzcg0+/fRTehI9JH4yhehNr0I6w913360Wq1A4zHlz\nLsZitWJNwpAhQ3hp5QrSZgP2x84iuvJjEss/oHX4ndkFymzkyIlHKP8QiaYzmYzKNUjlo1zHzs5O\nTCVOjM6vo2R3AcYiu5JwCkjr/jRy3nV6Sm+sLLkUvSRdp+PyOW59nsrvviR8+b//3cTjhg0b2LBh\nQ5/P9Y///eM7AXZFRQUtLS1UVlbS3NxMeXk5ANXV1ezbt0+9rqGhgerq6j7fQwfs/Y18ENRvAn3o\n8qr8smnobTvl8XiU/4Mu0YtEIpSWllJaWkptbS1ms1kVl4gxfjqdzuGkJcFVVlbGG2+8wTvvvKNk\nd/Pnz1efL6De3d2tJHxCi8hNLhGpw+FQgNPe3k5JSQmRSITVq1f3ng8DfN6+l3S0B1Ipli9fjjED\naaCl5lYyyTQjhgxj186dTJgwgUAgwObNm2k/5kEAuld9SvprMyWANRveZPXaNZDKnrPBgwcr8yUg\npwFvKpUiEAgozbKp2InB8nUFaaEVgz1rbCWqGulKn0qlqPe3UvzcHAq+PwbnvCmEl6zHvXw7d9+2\niCuuvwbnj47HMXcy3W/tIHTHn/D5fKQLTFR+cQcGkxHr9BG0b9pNZSrL/Q8bNoyjjz5aOfBJXiAY\nDFJeXq6ubTgcJpFIEIlEKCwsJNUcJPLE3yj4wTjif9xCujOGa7BLJRP1KlfZAUkEHQwGldbc4XCo\ncyLALqok4enz53D+3O6Ly5aRH5VLslr0+fsD7Pzg54477ujzdf3jf+f4ToAtZcU333wzzzzzTHZr\n/PXjF110EQsWLKCxsZGdO3cyefLk73xwehKnLz2qTpP0BeK6YkQc3OR1DodD8ZGZTAafz4fJZGLQ\noEEqaVhfX69AVlqC6YCbyWSrDzdu3MgVV1xBdXU1d955J59++inDhg1TPKXQNMJJC/hLJCYRv3yW\nRHTJZJJBgwaxcOFCLBYLTz3zNC11VoqXzcE34/+ReH+vWngAylzFrFy5kquvvpp0Os2dd96pvl9l\nZSUdHR088MADDBo0iMuuupLODh+elZeT2NZC8GevsHDBjYwaNUqBg1SRynewWq243W6MRiMDBgwg\nsaOF5vKfg9GAaaAHUzJDU1MTixcvVovmmWeeydFHHw1kMNh7i58MTgvx7m5efPFFUiZw3f697GJ4\nxdHEnvsnTVubMLgLstSHCchkIJVW/uDxeJwtW7aQSqWora2lsLCQ+vp6ysrKVOFPaWkp8Xic1tZW\ntXCMGDSYXYvfIPiLNZisVg4ZNkpZ3ObzyPkqDdkp5RdCyU4qX8Yn8zB/Tstv3eZVrpM8p1Mr+uIv\nv/vHwTn+pXzjwgsv5Oijj2bHjh0MHDiQ3//+9yxcuJC33nqLESNGsH79ehYuXAjAmDFjOO+88xgz\nZgzf//73eeyxx/6jbLbcEHrhzP54vnzglptB5yMNBgPFxcXK/8NkMmG321WJt0SGw4cPZ9SoUdjt\ndhWBx+NxddOn02m15d+6dSsFBQUMGjQIp9PJ0KFD+fvf/54TBenud7KlloguGo2qBUDv1F5QUEAo\nFMoxneqKRyiYdQgGs4nS16+lZO3VWLwurr766izYF1g455KLOO2003A6ndx0001cddVV2YpNY4qM\nAR588EG6urro7PBhnlCNZUI1jgsnUnD6ON5++231eS6XS1EhmUwGt9utTK6sViu1tbXMmTOHwhIP\nWE2kvvJx1ZzLeO655zjzzDN54oknmD59OqtXr6awsJCJow6h67o/El+3g9grHxO69y3qKquzxkyx\nBJlQlrfPJFKkfFk/cEMqQ+DiZ4mt+oTOK5eT6Ywrrr+9vZ1QKMSXX37Jnj17aG1tZciQIdjtdlpb\nW4lEIgQCAWWYJcZMbrebI8ZMYOoRUzjykENzSvAlZ9KXZa9OZ0kCVsBWdl06WPcFuvkRdT5loo/8\n4EReq79f/zj4xr+MsJctW9bn43/5y1/6fPyWW25R2+3/dOgtv3TXMuEP8xM9+ZVoEono21a58QQ0\npSjHZrPR1tZGMplU0Wh1dTXt7e2qLN1gMCg7TUk6SmGGRKWlpaXs2rUrJ3LWjaiECpGKR0AtSICy\nSq2oqGDv3r10dXVRXV2Ny+Wi0lPKVy9twX7uYWAxEVv2IW57IRs2bCDeHcf648nEXvmYX/7ylwDc\nf//9AGTIYL/9ROw7Wtn34NtcdtllkAHXXTPUuU77IhQUeNSCJ3plUa1IMlTAaejQodTW1nLFFVdg\nNBqZMWOGMrXq7OwkGAzi9/vVrmHu7Dmkf/97PrpmBWRg6mGTKS0t5Y033siW/J/8W+znH073G9sh\n2E1FRQU1NTXs+WIfnTetwWN3cdEPr8Hj8WC32/noo4/Ytm0bY8eOxel0UlVVRVNTE4FAgPLycqUQ\nqqmpUcZRW7duVYvnxIkTMZlMbNu2TenuAaqqqlSULnNMT3BLtaxcL5k/or/WTcZ0Wk73B9GrG3Xw\n1XeA+Y8JWMvoB+yDcxzQlY56n0bRMuvbUd1ZDXIb8gqHKZ4W0sVFZFqizpAy80wmQ3FxMT6fj0gk\nQmVlpUr8ideIJCClp2BFRUXO8eifrVdiyrHL99BlgtBr0+lwOEin06oyT8yaJCq/bN487rj/XlpH\n3Y3BYsLUk2HB9T/l/qWP4Pn9pdhnjsM5dwrhRzYQX7KRYkchHd0hip++BNtxw7In1WLC9OQWHAUF\ntP1wOanrjifxcRPJf+7ljMXXKApE2l6VlJTk9E+U7ybHnEwm+fTTT+ns7OSkk05ixIgRLFy4UGmd\nf/7zn6sk7OxLL+XU1laSySTr168nlUpx3nnnsX37dvbs2UP3Ex9SbLNz9g+vUUZWqVRK0VfFxcVY\nLBalD3e73Wzfvp1BgwapRgh1dXVqoYFeDj6ZTFJeXo7FYmHPnj05VITH42HIkCE5gYDMCQFsPZGt\ng6o+N/WIWW/OnB+N/ydgmw/y/ePgGgc0YIv+VW6KvjyD82VVkFuEIJNbGgFIJCQUhxSDGAwG1ear\nubkZr9dLXV0dHR0dfPbZZ6oNlgC+mEK5XC7VmspgMOD3+3G73SqaEs5bFolYLKaA2mw2Y7fbVbGG\nyNHkb0wmEz6fT3Hn5eXlPHDnYj755BOCwSAmk4kNGzZkeWy71nLKbsVis2bdBW1GMGnMl9GIyWTk\njBkzeeedd2hY8leKC+ycf+XVQK8HudGY7XnZ3t6uFjZJoEpjW8ga9994441ccMEFVFVVcfnll3P6\n6adz8skns3z5ch5++GGWLFmiwNDpdPL6669jMpkoLi5mwIABDB06lJqaGhWpulwugsEgJSUldHd3\nK0dEg8FAKBTCZrPh9Xrxer2MGDFCKWukQYXkPsLhMOPGjeOdd97B7/dTWlqqemMKmOrzSFd+6BGu\n7OBsNhsul0t5qcuiq8v3JJEsxyR5DhnfVhzz7ww9Mu8fB984oAFboiOdEslP5ujUh3DMkpxJp9OK\no5Zu59I2S3hi6SojBk9ut5umpib8fj/l5eWMGDFClXr39PRQXl6urFitViuHHXYY69ev58FfqQ4D\nJAAAIABJREFU/xrX14mviy++WFEfMnR5nFRYSmJRWlhB9oYUjXtnZ6eichKJhOpM09PTwwcffEBD\nQwPpdJqSQie+61+GX59FJtpD6O7XMXd/3Ukl0kPnD5fhvvcMMv4IkYfeZtyEiXR0dHD88ccD5BxD\nKBRSxkmyQIomXdQR4j+dTqe56KKLmDx5Mtdcc42qKpw/fz7hcJizzz6b9957T+0Q3G43Tz31FJMn\nT6aqqgqLxUJVVZUqww+Hw9hsNmKxGKWlpaprjMj0pFgpFAqRSCQYP3487e3tqnxcKC5JOgq9Jc2B\n5fzKNRDgCwaDfPzxx1gsFoYOHao8QYR+cblceL1eKioqKCkpoaioCJfLpa6xyB8TiQThcJhwOKyO\nUxo76AvEfwra37VyuH/87x8HNGBL8YOecMzfXgLqptH9HoSmiEajalstgC7FHAIOOtUSjUapq6vj\n888/JxKJUFJSwpAhQ5TUT4ppRGHy3nvvkTEbaGtvo62tFQwGPB7PNyJ/WWzkt0SCsq12uVxKKiif\nUVZWprTZ4ji3ZcsWPv/8c5LJJEcffTRer5eioiLeWreOvdeuIJNO48iYKa4oJpVKceKJJ/LHFX8k\nsuBVCh1Obv7xDYwfP56VK1fS2NjIwIEDVa9D6RlpMBhUlaNEm6InD4VC6vWXXHIJFRUVHHvsscw8\n/xwS6ew1WLt2LccccwwbN27EYrFQWFjI4MGD+eyzz7jggguoqalRlFU6nVa9NWXhzJdRSg7CaDQq\nTxKz2UwwGFQ5BXE2lF2QuPK1trYyadIkurq6lCxP5ozRaGTQoEGKe96+fTtfffUVU6ZMoaKiAqfT\nSXFxMbW1tdTV1aku7FIsJfNQXCNFRhgIBOjs7MTn8xEIBJQV7/46IwH/rai5P8I+eMcBD9iS5NEz\n5HoyCHKNcqBXly0TW++pmEqlVM9BSWJKSbiAvcViUSZQVquVQYMG5ci4TCYTJSUlpFIpNm/9CO+L\nc7GdMBKAzmv/wJq1a7j4oovV95Akoww5XpGTyedKU4NQKJSzXTebzUQiERoaGvjwww8pLi5m2rRp\nuN1uZTF6zVVXqcIeaeSwZcsW2tvbOfWUU5kyZQrDhg0jHo/T1NREQUEBzc3NGAwGysvLqaysxGKx\nKC5YzmFBQYFKHMZiMT7//HPGjBnD66+/TmNjI2azmcWLF4PZiG3mIWTWh3nqqad45plnMBqNzJo1\nS3mfWCwWSktLCQQCqmJUEpNy7FJwBL3JZDmHAtRCa8l8ELpG6C1Z4CKRCD6fj0mTJrFt2zZisVhO\n9aLZbFZNl8WZUZoluN1u7HY7AwcOpK6ujsLCwpyEo8wdWZhlF+BwOJQ/jRiKSUMN2SXqyWa9ylEf\nfem09fneH2UfnOOABmyr1arAViaoHnFJ4lB0zkKHQO/NINwjoLhkMa3XOU8dOHt6epSvhHThdjqd\nijaRhgXJZJJ0Ko2x2qOO2VTnJbopW6ovoCc+FBKxiimR9GdMpVKEw2EFkE6nM6cRgwDpli1bmDRp\nkvIfsVqtlJaWUlJSgslkIhgMqmazlZWVTJ06lb179yrOXfpIer1eJkyYwJQpU+jo6KChoYFNmzYx\nZswYDj30UJLJJK2trUohIoDa3d1NMBgkFosxc+ZMzj77bC774ZW0zhqE66aTAeh+7ytCs1/giYd+\ni91uZ+/evYqrLykpoaOjg0AgoEyzZCEVlY9cm66uLtU9R3TxcjxCJQn4iR+5PC5ALrkCq9XKhAkT\n6OzspKmpCcg6Ce5ubSSRTOJxujh1+ol89dVXuFwuampqsFgsVFRUUFdXpwqudKvffOc9masSZMg1\n7+7uzlkoZH79JxFyf9Lx4B0HNGDrEbYu3cuvSNNd8ERZIryvlCzrniSSQJQISTTVIsMTr2yPx5MD\n0hJ1iwe32WymrLiEwIJXKHrkHFLNXUQee5djj5meEx1LAlG4X4mQpJmvJK9SqRTxeFxt3eW45WfE\niBEquSbALgCSyWQYMmSIWrCk+7vQMwJ0ApzSUXzUqFGkUil2797Nnj17sFgsqnmBLJSRSISCggKs\nViuHH364ai+2e/dudu/cRfpXOwn/+m1sp4zGecXRpLsTXHnllSqH8NBDDymVh4BzV1eXoqckmakr\neZxOJ5FIJKcgymQyqfMuHHNZWRnQm4yTfIcs5mJdO3LkSO666y6VdNyxYwfmQ2swNHcRaOtg+fLl\nOBwOpWl3Op1UVFTg9XoVNScJcL0KUY5Pomfh0/OdAmW3JoZm+UOXAPaP/rG/cUADtoC1nqzT+T+p\nTpNItKenR7XtEhBMJBIK+CTq1t87FArR09OD2WxWOmOJuGXbLhGivhjI41fMmcfjz/ye9umPYDQZ\nOXLsYRx55JEqESUJUImkZeGQzxFViERoAtzd3d2K4xXQFN23aIDlnMTjcUpKSggGgxQXFyslg3wP\nOVeiUolGoyqpGI/HsdvtuN1uBcZmsxmPx6MqM4uKilSDiFgshsvlArIL6llnncXLa1fhvP54wr9a\nR/e7uzDGE1w0Zw5Tp07lueee44EHHuC+++6jp6dHKSwqKipoa2tT1YMSiUrUHA6Hs6Xkqd7OK9Iw\nQkyeJLEnNIXw2KJ5lr/x+/0UFRVx3XXX0dDQwMaNG2kb4cT7h3kApCM9tA7+BTfccAMVFRWqk5AU\nWemFVnrlLeSWnuuFMiITLS0tVcljUQHpxTX6XPh3Abuvyt7+cXCMAxqwxWdaN9+B3KpGuaF1MHU4\nHDluc+I5LWZAwnXKAqBXuRkMBrWFla2vaJMlypKbV37/6IofKkWFLByQ2wVb1CmA2urrxy26ZuE7\nhR6RBUeSVtKMQY45GAxSWFhIQ0MDJpMJv9+vQM1oNKqOOQK2At4StRsMBlpaWhS1UFVVpcAPssob\nv9+vzpnowi0WCwMHDmT+/PlUV1fz3PMvYcjAqAGD+fzzz5kxYwbd3d0cd9xx3HPPPep4TCaTWlBF\nDSMRfGlpqfIEkUUpkUhQWFioOrYbDAblnqjbv0oTZqnUhF4lkcvlIpPJNiGORqNZTj7SG+lmYj2A\nQUXSkigtLCxUSW8dqPP5Y3lcAFioL1GY6A0qQqHQNzj6vvxx9jf6gfrgHgc8YEtUo/s16ElGKUjJ\nb3IgQC49H30+n5JkiVdyYWEhnZ2dOWW/8vfSjFd4UOEnxRNZXqtrw/UdgPCzAqySdBLJmdA88rho\nncUJUG54KYsX3lp2AbKTkLJrm81GOBxW58vv9ysKSTTDQgcJ+IuTXWFhIV6vl9LSUpxOZ06LMqGc\nYrEYkC1AkkjW7XYD8L3vfY+6ujpuuOEGFi1axNy5c3nxxRc5//zzWbNmjWrJZjKZlA0AoBYe4agj\nkQgej0cl3FKplEreif5dlDyA2qEA6jlR2Mjf6/kDj8eD3+9n4sSJfPnaK3T9ZCWWIwYS+c07VFVX\nqwjearWqLj96JNxXdK1HyfmJaTEJk6BDFhvZReUnD/WqxvyhLwr9/PXBOw5owO5r2wjfNMmR1+oG\nPLoHhGiLe3p61PY+k8lgt9tVdAuo6FE4a7PZTGFhoVIhQBagRc2h+25LJKb3P5TjkiGdWfL9IOQ4\nRa0iDRaEk5UFQQA8Go3S3t6u/DIkkhO5YCQSUdI44VH1RJ108nE4HAwaNAiTyUR5eXmOxl2KV3Sf\nk2g0qr6vcPNutxu/38/ChQs5++yzKS0t5Y477uCuu+7itddeY/jw4UqJo7v+OZ3OnKpCyUfE43EF\nsLJT0pORwt/LIi4ArRe4yG5FPs9gMBCJRFT5emVlJWd9fyZvv/UO3W/sYoi3lAvmnp8DunK8/x2Q\n1OeqLJyyK5PFU2gvoeGAHAuF/PfKf1/53a8SOTjHAQ3YMpF1hUg+cOsALVGt/FuUI9Kwtb29Hbfb\nrXr+CXAIDyoWrBUVFbhcLqLRKLFYTN1IAsgiQZPWYuJgJzeqAIwOSCI7kySj/L18P0nKCV2iF6fo\nXLdoeSsrK7HZbHR0dCiOVJKQksiTUnpdySDvJcnHTCZDbW2toiXC4bDawktULYoYUYvIuRd65fLL\nL+eII47g+uuvJ5lMMnHiRF566SUSiQTvv/8+X375pXqtRJ16FGm1WolEIjkVgqlUitbWVpVclORx\nJBLBbrcrxY8eSevvmW8XIIuqUFlut5szTpuhdguA0lNLYlAkoP8dgMwHd0k8y/zJN4aS49RlqvJ3\nMjf0ea8HMf3j4BsHNGDrkz8frPO3oH1NZAFt2f63tbWpzL8U1UgkKaqKgoICBRA63ys3m0RJYj36\n5JNPEggEMJvN3H777TmSQ90GU/hsfcstx2g0GhVnrHO4mUwGj8ejolyhPmS73tPToyrwfD6fOk63\n2008HlcNgmVnkUwmcTqdKlKVhUZeK+XuUmAki6HepAF6GzQUFhYyb948ysvLWbRokSq7lyg2Ho/z\n+OOPc+yxx+Y4FObLNBOJhPJREQpIStRlgRB1iUgc5TG9lyagFlOZH0JDdHR0cNVVV9HY2IjJZGL2\n7Nk5ieoXXniBL7/8koULF+Y0Q8jX9P+roedZZLGWY5GFQ6dW9Oi6L8CWf+sLRj8tcvCOAxqw86OR\n/ImqS6kkqtVL2PWIKxqNqrLhoqIinE4n4XCY6upqbDYbgUBAFT/IFl0idOmCLdtsAZ1UKqWKLFas\nWJFT0COvF7pFaAVd8iVJRb3kXmgRUWJIxNnT04PH41E7BofDoVzmotEoFRUVKnIPBAJ4PB5FhQj9\nUF5erqR2Ims0mbIWs2JFKlF8LBZTLbbkOCXalHPz0ksv0dzcjNVq5bTTTst+V4uRTCqDIZ1dTIcN\nG8aNN96oIk0BXQE0yFJRUrovlJOcP5H+yeIlyVu5tjrQSdJWFmIBdNl1nHHGGTQ3N7N69eqchbW1\ntZXGxkZFyYTDYSKRSI7vy78aAuoyd/QfOX7ZqelBhp53kdd8W5CST4/0j4NrHNBEmO4lIlGp/uNw\nOHA4HCq7L68RekOf8AJEnZ2dqixdbiCn06mSduIDIZFQKpWis7NTRUu6R0gqleLQQw9VRki6X7do\ntfN5dt2WU6JYibyFchAdtMgHhQsVQCgoKMjhvMVsKhKJKE7XZrMp7bjb7VZgJ4uSgG8oFCIYDCrw\nkGIPoRuEZgJUhCyL0KxZs1i3bh0bNmzgmKlTMdZ6KXnrR5S+9SOM1UWccOKJ3H///TmUEqCKguR8\nyAIkICZFSjqFIQlfATjdeVH6bkruQTr3AAosq6urmTlzpkreipNiIpHgrbfe+rrJQvbYAoEAe/bs\nIRQKKUmoRMe6k1/+j24glUgkFPjrXurwzWa8+r9l4d7frhH6lSIH8zigI2zRSutRs879yc0oI9/O\nVIBaB99gMKi0x8JfS9Qbi8Xo6urC6XSqUmS5CUWZYbfbVZQnkaLczAJCEpnpyUpZVPIrH4XbloRe\ncXGxoigkMSptyuT95Hvp6hRJIgqXLSoPGX6/Xx1/MplU+nM5vxKNCojqi4tw2QLg+ntLEvOf2z7G\n/cDpWMYNAMC16DQ2/+IvKhqXBUCOX/cHES5fV33IeRYwk8VPtzIV2knmgC6/04FU3lsWXOhVeHz8\n8cfYbDZqamqArMQwGAxSX1+Py+XKeU/9ffRKR/mtR9RSFer3+1WOAfhW4JZr2tdusn/0DzjAAVu2\ns/r2Ud9O6zeSRH7CWev6Vj3ClihUPDMikQher1f1KQwGg8pZzuv1KsWE3EhCO8hn6uoHg8Ggsv+S\nnBRglgSWXvgj9InuliegIt1Ruru7lT+21+slHo+rH5GIyQKhL152uz0naSrFIO3t7Tmvlco8AVSJ\nJt1uN6lUShk9STm1GBlJEYhYw4Zb/TDveTAasIyvpuD0cZgzBubMmUM0GsXhcPDEE09QU1Ojzosk\nAuXcCvUi51YWELENkJ2F0Zg1gRKppahE5HzqJeoC6HpjYBnRaJQvvviCU045RS1Kfr+fnp4elXg1\nGo2MHDmSoqKinObL8ln64infq7u7W3XFke43gMp7yPfVF1x9Acj3yekf/UPGAU2JCN0hZjoFBQVq\nGyxgLiCuG8n3xWPrFIOUl8vNlclkGDBgAC5Xthmrz+dj3759BAIBVSEo2mTZRodCIRW1i4QPUMAn\nSTIBS+HZdeWC8J3yN/L9zGYzxcXFijoQ3bjeB1KSlgIaumudSBhNJpMyI7JYLMofRBY7j8ejXivn\n0Ol0UlZWpqR7UkTkcrkUkAs1Ijx3UVERN/7sZxjMJuxzppD4qIHQ4tdxGM2MGjWKFStWMHz4cG6/\n/XZCoRAtLS05sjahknRA1dU0breboqIiRY2I5M/j8agchp7Ak+svTRfk/STZLCMQCJBKpXj99ddZ\nsWIFmUyGP/3pT7S0tBAMBmlqauL999/ns88+o729XdEbMgekGlZ+YrEY4XCYjo4O6uvr2bdvHy0t\nLUovLw6CMvaXm9EXgL6G7Pr6x8E3DvgIW/dvAHIATyInvWeiPuSG0JUGIt3Sn/P7/QwaNIja2lol\nhfP5fMqQqaioKCdRJL4a4gWybv06UqkUzz3/POecfXaOx4nFYqGzszPnPQR49O8mUbqAvM/nU+Xl\nEvXqHDX0UkBCaciCpKsa5N+RSET5kAj1IECvl1yLtM/j8RCJRNRuQSJWAVrZ+cTjcTKZDDNmzKCs\nrIxnnn2Wz9Mwd+5cnn32WW699VZMJhOXXHIJN910E8lkks7OTr766ivsdjs1NTVqR6Pr2HUHRbnO\nOpUiC4eoTwScZeck51foB50ag2x0vW3nDgpKinCarUw+fBKvv/46J5xwgloIIAvqW7duVddFPLJ1\nbbXs7kKhkDLTamhoIBgMqspGmYN6Ba0epesaeNlp6UMPPPo12AfvOKABu69qM8iNMHQzKP3/0Mu5\niieGPB+JROju7lbqiba2NoxGI263m7KyMkVFBAIBJXWTwhgprpHE5OJ77iHz9eft2rmT+x/8FQuu\n/4nSYYvuWC/yEKWHRMn5HWmkLDqTyagdgERx8hqhC8SbWaRxckML0ANKDgioHYnuWaJ3lA+FQrhc\nLsLhsFLDSCGOyWRSJdbyeqFmuru7ufXWW+np6WHMmDHMnTuXp556imHDhhGLxRg6dCjJZJKuri6S\nySRut5uOjg727NlDSUkJdXV1KnkKqB2VvpCJ06FEoMJzy+5DqBEBellUZBE466yz6OjoIJPJsGrV\nKowDi3HfczrhFz5g3XvvAL12CEJ9QLarzvbt2+np6VE7MVkgZDGU7jwNDQ20t7erBK8EE/KTT4Po\nNI5OleiyRMilSvQgpH8cXOOABmzZpucnX3R5FHwz8aNPdAEvKa5IJBJEo1HlpSEdZ5qamhR9IWZI\n8Xicjo4O/H4/VVVVOZWNdrs9a9XpsFC5/TYMdguZZIq28ffx+eefM2TIkG+UH0t0KpGw3MRCX0jp\ntvC2AriyOMj3EipBCneKiopy2pTpemn5jplMRtEaTqeT7u5uVYAi50q29LFYTFVl6olUyG3EoJev\n22w21q1bR0tLC7Nnz+bll19W1zAej9PZ2QlkF6eioiLsdjvV1dX09PSwe/dutm3bRk1NDUVFRQps\npVmC0ES67E2iaZkfAuxC18j1liSiy+Xij3/8I//4xz94+eWX+aBhB2Uf3oTBaKTg9HG0jriTqVOn\n5li1Cs0i71NfX08oFMLj8ahdji4X9fv9hMPhHMteOV45Z/mRtTynJyL1ka//lnPQH2UfnONfXvX5\n8+dTUVHBIYccoh5btGgRNTU1HHbYYRx22GH8+c9/Vs/de++9DB8+nFGjRvHmm2/+Rwenc9O6r8i3\nVX9JFCNAqYOXAHckElHJMgFfqb4zm7PdX6xWq+rmIjehAGA4HFacpMFmhoIsgBrMJoxOa862V8BV\nvzEl4hdFgS5xAxQfKhps+ZHkpb7ll0468lp5XCJoSUzqCU2JRkVbnUql8Pv97Nq1S3lGt7W10dbW\nRldXF52dnTl8v0T8Qk/ogDR8+HDGjRvHhx9+iNlsZt++fbhcLnw+X055v4Ch1WplzJgxWK1Wmpub\naW1tJRwO09zcTE9Pj5LWSSWkrnUXjxKhrmRREQqps7OTTCZDYWGhqtxU6hqzCQQIjQYMplwFEvQm\nsuV7xmIxfD4f9fX17N27l927d7N3717q6+tpbGxUxVe6jl/fDernKV9jrQN6X5y2LhuUx/rHwTf+\nZYQ9b948rrvuOmbPnq0eMxgMLFiwgAULFuS8dtu2bbz00kts27aNxsZGTjrpJL744ovvHA3oCSU9\naaiDszynl4Hrki79hpCbQfjG4uJiDAaDAmjhUEUDXF5erv5WbkJAbb1ramow9qQJ3bwa+0UTia/Z\nSro1xPAZw3OSckJHyPEIoEsELZGuqBIkqShqBCkCKSgooK2tjZKSEkWRSFWeALpeYSkyQrFfFepF\nOGmJHP1+P42NjQrYhGYRkBAaRBoPZzIZVZlotVoVHz1y5EhaW1vZunUrRx11FNXV1SxdupTbb7+d\nG264gUwmw+WXX87QoUN55JFHuOmmm/j000/VQjVp0iRmzJihaI9gMKgkii6XSxlVQS/oC9XU1dWl\ndiYSIevAbjBk/UQMBgMDBw5ky/bPCC54hYIfjCP6/PuYUlBeXq7mEmQBWzhxHTR1C1+hPvILZHTZ\npVx7+Z0fYff1k/93+VLFfsA+OMe/BOxjjz2WPXv2fOPxvibMqlWruPDCC7FYLNTV1TFs2DA2b97M\nlClTvtPB6ZVgeplvfimyDtjyO5/z0284ad2UTCYV7ysJQsg60kmPRa/XqyI82YYLIKRSKS6/eA4v\nvvJHAis+wm4tYM55FykQlWIOAcf8BKhEvpBr/COAla98CIfDlJaWEo1GVaLSYDAo32j5nnJsAq7y\nWxYrkylr8xmJRJT8zOv1kkwm+fGPf6zO39ChQ3nggQd4/vnn+dOf/kQymWTevHkce+yxShdtMplo\naGjg3nvvVd8jmU6xcc8nJNs72bdvH6effjoOh4PHH3+cdDrN5Zdfztq1azGZTBx11FHce++9hMNh\n/vrXvxIIBFRloux4pMhJut3rJf8i4xT9vQC57iUu31sSl1arlVOPO4F3//Q3Qmu2YTdZOe64E3J4\nZL1Yxmg05uQAZFHVdxl6v8b8qFp2IftLOMrQg4v8ua5X0PaVYO8fB8f4zhz2o48+yrPPPsukSZNY\nsmQJHo+HpqamHHCuqamhsbHxOx+cHjHnl/wKB63/W+gFkVzpUbee9JHISbw4TCaT4h8lyo7H48rA\nvrS0lFQqpUAeUNra8vJyLj3nAioqKhQoipkU8A3g1R/v7u5WPRhFwqa77dntdnWDijezRJuSAJTv\no9/k8jn58q98SkiaCkvDA4ClS5cqC9SLLrqI119/ncmTJzNhwgSWLFmSU/koicETTzyRWbNmAXD4\n1CnQkyHZGIBUhrTZwFWXX8kll1xCKpXi+uuvV+3BAEWLOBwOioqKaGhoUAAo30PoHtGk62XrYimb\nX3Qi51h2ZZJ8lk7mTqeT700/6RuJPSBn7uhVrbq/jChQpKJRAFtUOnLN9Wuvf9b+fueP/Mg6/1j7\nx8E1vhNgX3311fziF78A4LbbbuOGG27gySef7PO1+5uIixYtUv+eNm0a06ZN+8ZrdD2q3DxyY8hW\nWLb3AtT6/+XmyU9Oyt8CSt8rUTSgbkS9o7rYfkoSTAAyHo+r5J8eDcvxSBQsoJO/I4DehgbyHqIY\n0f2tu7q6KCoqUn7R0qhXuGi9qEinjgSswuEwra2tlJaWEovFaGtrU+fR4/GoKLSoqCjnupWWljJ2\n7FguvPBCZXa1fv16Fi9ezMKFC9mzZ49S2Lz44ouko92Uf7QQU7WHdLyH1trbeeutt5g3bx7HH3+8\nKow56qijePfdd9m0aRPHHXcc5eXlzJkzJ6dk3+/3qySf0DCi1ZbvKNSMTlMIdzxnzhyampowm82s\nWrUKs9nMU089RXNzs7pOU6dOpbS0NGfXJkGA/BaQlnmhV2vKnOvu7lbnUxLDenf1/d0b+VH2fzo2\nbNjAhg0b/sfer38cWOM7AbZwuwCXX345M2fOBKC6upp9+/ap5xoaGqiuru7zPXTA3t+QLacAnH5z\nSPJOz9LLNl9vrwUoXlciMwFTfasqQCH0hUSiAnw6QIvyIRQK4fV6sdvt6t9Go5FgMKhMk1KpFB0d\nHdTW1uaYPAlwSQQmkbdwxSIFFBCVRsCijCgrK8Pv9+dEm/nqAfEEERqnsrKSQCCgNOZS1Skl2CLd\nO++88+jp6WHkyJF873vfw2g08txzzzF37lzmzZvHf/3Xf7F+/XqOO+44li5disPh4Ic//CE33ngj\nVreD7rd34rjkCNINXZBKM3bsWEpKSiguLmbu3Lncf//9vPnmm9x+++3K2nXevHn87ne/Y86cOaqC\nUc6lz+fDYMh2uxENvFgK6M0BJNKVhev000+noKCApUuXKg+VqVOn0tDQQEFBAVu3bmXz5s2cdNJJ\nORSEgLUkmkXdI3y2DP11MlcFrIVq218krF+n/0nQzg9+7rjjjv+R9+0fB8b4ToDd3NxMVVUVAK+8\n8opSkPzgBz/goosuYsGCBTQ2NrJz504mT578nQ9Ots76TSE/shWVKrJgMEhXV5eqDoTcCEYiTQFv\n4T51rlEel0he5xyht6glHo8DKKDPZDKqAEVPekmJfFFRkYrSJOLSVS8CtDpHLnSH7qAnRRgOh0PR\nJuFwGCBH8y0Ljf594vE4kUiEpqYmOjs7c5JwugeLwWDg1VdfpbOzk8suu4yXX36ZSy+9lIEDB+bI\n5wYMGMDEiROZOXNmznf7zW9+w5VXXknXj1eo63juuedy33334fV6Oeecc7j//vvZsmUL1157LcFg\nkGg0yjnnnMM999yjmjfINUmlsv4vHR0dOVLMTCajlD5yjnSlTSqVYsaMGWzbtg3IShblvAgtIny4\nJCyh1ywKUIu1LAhyjfQdnxyjzDlJ/sox6ACfP/6no+v+8X9//EvAvvDCC9m4cSMdHR3ptnSOAAAg\nAElEQVQMHDiQO+64gw0bNvDRRx9hMBgYPHgwv/vd7wAYM2YM5513HmPGjMFsNvPYY4/9RxMyFArl\nALZsOwW0hZPs6uoiEAioLtsCiLJtlhsLekFWKAe9Ua7ceHpl3/6OobS0VAGiAIW8r8lkUlGZDrhS\nGSmvkR2AALyAV1lZmQJS0fvG43GsVisej0cVzsj3TSaTituVqFrfncjC1tDQoJr4ynlqaWmhsLAQ\ng8GA3W5Xi1RFRQVjx47l/fff59JLL1UmVL/+9a8ZPXo006dPJ5lM8txzz1FeXs6sWbMIBoPs3LmT\nVatWsX37dgoKCliwYAFXXnklqVSKZcuWsXv3bvV9Vq5cyRFHHEEkEuGVV15RBTwCej09Paq4SexO\n5bvpqh6hnHRqSsBdpHyyyO/evZsdO3ao3pljx45VckB9CL2hX+O+omW5jrqrYn7iUa7z/iLufHmf\nPl/lM+R65atP+sfBNf4lYC9btuwbj82fP3+/r7/lllu45ZZb/rOj+nr4/X4VFetAqlMj4l0sNpj5\nVZGQy6Pn0yuRSEQVq0hVn66ogN5ISdcP6224xEZzyZIl6m+GDBnCzJkz1c2l+zLrHWEEZPVSe+lM\nLlEdZG9k6U2pR7RifiQOgiaTiUAgkAMcgUCAQCBAe3s7VquVwsJCbDYb5eXlfPnll6qDemdnJzab\njbq6OmKxGJ988gllZWXceOON3HzzzbhcLn70ox/x0EMP8Yc//IGZM2fidruVvNNisTBgwACGDx9O\nXV0d6XRa0Tjd3d2ceeaZ6jp89tlnfPbZZ2oHY7PZuOCCC1QjXp2mKigoIB6P4/f7FUAKZSIRrFx3\nXYoIqGYHElmHQiFKS0sxm820tbWxfft2hg8f3uf80/MOugxTn1d6ElBeI/JCUZZIFC5gLAvmvzP6\nCnj6o/KDdxzQlY7i0yzAo3PPQonoOlgBVf1m0KMbufH04o94PK4SjxKJ6qXnIgcTv2qhBfQiENHj\nzpw5k1GjRhEKhXjkkUfYtWsXI0eO/IbiQG/jJcArxyZctC5Dk5tfAKO7u5uWlhZMJhNlZWWqhFwi\nSqFUAFpbW/H7/bS0tOBwOKiurlZNeSGb8Ny3bx/BYJA9e/bw4osvAl+bUxmg88xhrFv9Pm+ddBIA\n9913H0ajkX/84x8cf/zxLF26lA8++ACA0aNHM2DAAPbs2cMtt9zCxx9/TCaTUdz3okWL+KvvCxJb\nmyn7x89IfLiP8M9WcdsNN2M2mykpKVE8ui6fFOAXWiiT6e3aAr0VnXIOhPrQfbFFq637WzscDnw+\nn6KGdCCUhVJXfeQ/l//vvipw91eVqOuy/x3w7kv+1z8OvnHAA7ZwhrqkT6LadDqtbk69UkyX8+k8\npB6FJRIJpZyorKxUNAugInmdQxbQdjqdtLW1YbVaVTGKvG78+PGkUinVYEEqBMVBD3ojMYkUJaIX\n6sNo7G0AKwuUAIZsu2OxGJ9//jmHH3646paj91sUvlZanzU1NeF0OhkxYgQ2mw2Hw6HohcrKSgV0\nnZ2d3H777ZSUlHDtz35CycuXYT2iFvvFk+j68QqOcQzm3HPP5UfXXcfHn29l/hWXEwtHWLJkCXa7\nnWuuuYYLLrhAAZC879NPP83TTz+dPfdkIAPtxzyYrTDMZHj++eeV1t9isXDdddcxatQourq6yGQy\nOZ4hcr7S6bRqSiw7HZ27z2SyHh9tbW1All5raGhQuw/RosvORZfXyc5G/9FBVa6HDpy6+kcWYfE+\n0ZPect3zgfrfBW35jG/jxvvH/91xQAO2JIN0oAYUEEu0JFFvfrGCrsGW/+sdYwKBAK2trfh8PkWH\nSFQnPDSgCjdEsdHZ2amoh0gkQklJiZKXpVIpmpqaiEajjBo1Kid6ls8HFA8tHLTwtzIk4aobEJlM\nJrxeL2azmUmTJqljFjCQxKKAVyQSYe/evVgsFoYMGZJDkxQWFmKxWAiHw3i9XmKxGJMnT8bv91Nf\nX086kcR3+tJsCXc6A4kUG6jPSsYMkIjHSaSyUfzNN9+swGvMmDHcdddddHR0cPVPr8MyroLEZ804\nrzqWyG83Qga8r1+DddIgwovfJPXsh1x33XUUFhaSSCR47LHHeOqpp1i4cKE6T3Lc0oBB9OsSvcoO\nRE8cZzIZFi1apEB/4cKFZIxABgj12hWUlJR8A6zzqQ75/W2v25+eWt/hye++OOj/jq6630fk4B0H\nNGCLnEuGXr2oJ3X0yFm4YAF0iUYkSpIkFWTBQLwzqqqqVPJNqgQl4Sg3iER1hYWFKqknUbdE7T09\nPbzwwgsceeSRStMsYCNRl3wHSUwK6OhctHTzFt8R+XtxD5RzoTfMlX6UkOX/m5ubSSQSjB8/XhXb\nyOcKwElzXlE2DBs2jLKyMjwlXjpb2vG+egV0pwhc/DTnzzyL5X9YDmm+BvIkZLJSsra2Nj755BO2\nbt3KbbfdxogRIzCUuzANLCbtj+Ja9H0iT70H0QT+05disFsxGYz85IfXkk6nlb+4lMb7fD7VGk7s\ncIVKMhgMqkOP5BXkHEniOB6Pc+ONN2I0Zpst3/fIg9hvPQXn/Cmkg3E6pj1MeY9N9ZOUxV3nxGVe\nydyRc5T/vMzHfB8QPVEoP3pFq1xD/bc8r0fgevJSjqU/8XhwjgMasCXC1reoOlDrEWj+9lR4Svhm\nVCMALNvi5uZmFSXLTSnqEZ3zlkhfl3K5XC7lG51Op3n00UcZOnQoJ5xwAtArDZPjks+Xmw96CzUs\nFgsOhwOXy6V8pqXMXaJ3XeGhF+QEAgG1xQ8Gg7S3txMIBDjuuOOUXazw8EajkVNPPRW73c7rr7/O\nxo0bufvuu5Xa5K677uKRXy5h9uzZ+M94HJPNyhknn8ahhx7K8uXLwWSgbNMCYn/aSvgXa1m/fn3O\n+d26dStbt27NfudoN96VV0AsAdFsQtaEEUM8xejRI5SPyiOPPKI0/CaTiQceeICf/exnqmBp7dq1\nbN++nZ/85CequYMAue4rItdGwF+eS8TieM8anz3/7gIKThtL6uUdlJWVZV0XoU/A1rXzemSrP55P\no+j0mz7yKxX7qmD8ttHPXfePA3pvpVMhUkQibZaEO9arIfWEnf68/l755e09PT20t7dTX1+vInJJ\ncknzWvEVkbZZorHWRzAY5OGHH6YnkSDWHVdqDrmJJfKXf0uULEU+UpIuNI1E3aFQCOiVe4lcTa/0\n9Pl8KvIMh8N0dXXh8/k4/PDDFbftdDrVonL33Xfj9XpVBH/nnXdyySWXsGzZMkaMGMFDDz3El19+\nmY1aM0ZM3Snq6+uVAoZ0hvi7u0juageyUXnBmYdSsuF6DEUF2C44DACz3Ya5toTut7+gdfTdYDBw\nxhlnMHv2bE477TS2bdvG22+/TSAQ4Mwzz8RgMFBTU4PT6WTOnDn4fD7a29vZvn079fX16njNZrPy\noxZglHMYjUaJRqNKKy9Jaou9gPgrn2QPPxgn/udtVFVVUV5eTmlpqVLbyIIswJv/IwVGem/J/Ghb\n/lYWVH0IQOs89rclHvOpln83Sdk//m+OAzrCFlUGkDP5dQ/nfBVIvo+IviXV30fAU/7mq6++wmAw\nUFVVpegIiaB0OZ5YreoNYqPRKK+tXZuVkJmN7N23l9/97ndMnjyZE088Mac8Xb6XbMMFICKRiPpc\nMafSJWyiyc5kMqpkXrhr3Tc7GAyyb98+Bg8ejNfrVZSJFALV19ezZcsWLr74Yl566SX8fj/d3d2M\nGjWKrVu3MnbsWJ555hmsVitXX321ohkee+wxPB5P9sJkIPTTleo6RbvjWMYMxuixkwnG6f7jRwDY\njGZ6tjQS2rwHQCUHfT4fPp8Ph8PBtm3b+OCDD5R1q9vtpqmpiUgkwsaNG2lqasJms3HEEUewadMm\n/H6/WkSFhoJeNYcAq3xv2THNO/9invjF00Qe2UjKH6HCW8Zpp52Gz+dTSWufz6fOkyiB9F2cHj3r\nuyP5LRx6foSt2yvo808PKL4NhPsj6/4h44AGbAG6fLpD9K1yE0BvBKorPHTOW24UAWJ5XqRwZrOZ\nHTt2EAqFGDJkCLFYTGmIpYFrZ2cnfr9fJfdsNhsdHR14vV784U5K//pTLKMrAfBf8DThxnAOLyl9\nF/XFQvhtOUYBGUmAiuWpdIbJZHqtTSXpKi523d3d1NfXU1RURHV1tVKJSFFMIpFg8eLFzJ49W+1A\n9uzZg81m45VXXuH888/n6aefJpVK0djYSCgUoq2tjXfeeYdUKsXbb78NZP1FOjo61DVpqN8LDzYR\n+uVb2aReuhd8ioqK8Pl8zJw5k7/97W+8+eabnHTSSVRXV7Np0yaMRiNer5dZs2axbNkyVZm4bt06\n/H4/kKUfpOhIvpNoyY1GIw899JDSaIvlwVNPPUVLSwsGQ7bt2f33388fTnmR999/H7fbTU1NDe3t\n7TmqolQqRSAQyKE25Efmow7IsmDoPLcO1H3RH/v7/787+sH74B4HNGBLRKn/SLQL5Hg2y6TX5VMS\nLeXz1/oNJ9REOBzG6XTi9/vx+/1qqyyG/7FYjK6uLlpbW3N0wAIcmVQaY2mh+hxThYue3f6c4g85\nPn03IFGZaL/FH0MibSm1NxiyLoA6gMv7SQHQ7t27efLJJykoKOCee+5hw4YNrFmzRgHJkCFDsFgs\neL1e3n33XdLpNJ2dncycOZPVq1fzt7/9Da/XC2QLW7xeLxs2bKCsrIyWlhYGDRpEW1ubajkmCVHx\nUBEJHV/jTyQWVYZaa9euVQvXn//85+z1MqIi7uXLlwPZRW3ixIls2rQJt9tNMBikvLyclpYWAHbt\n2kVxcTGFhYVUVVUpfxCr1corr7yiqKSRI0dy2WWXkclkePLJJ3n44Yd5/vnnqa6uJpFI0NXVpeaN\nLPJAjsmX6ODlWutNnoGc+SPXVI++5f3zFSfyWflzVw8yZOTz23I8/ePgHAc0YEtJeF8ZcT3hI9Eq\n9E56PWrZ39ZTzH3kNZLos1qtNDY20tzcrJz0RDYnCoby8nIlIbNYLBR5ium6Yhmuu04nubON2Mtb\nmHTG2UpHHYvFclpyieFTNBpV/iNyc+qRt2y1BXSFw5fkYTqdJhqN0t7ezurVq5Ul66233kooFMJg\nMHDqqafS3t6uClwWL16szsHDDz/MrFmzOProoxk1ahRvvfUWgUAAh8PBq6++CkBjYyMZA+yJdJCm\nB6K9/H06nSYcjWC3FSgVDAA2M4YSJ2Xrr6ftkHtIJbLf44ILLiCVSvHH117BPnsysWc2kzEAsQQe\nj4cf/OAHvP/++xiNRsVD637sO3fuZPDgwQwdOlQlFKdPn86OHTtydlEnn3yyAuLa2lrq6+sVny/0\ni8wtyY1I1WlnZ6dy2tNtYHWOWp9XOrUlczJfLZIfUesJzPzndfqsr8SlnhztHwfXOKCTjvvTu+rb\nUn0Lqkc6ugF9ftGN/jq9AhGywNzV1aU+SxwBxYFP2lFJWzGPx0MymeTCs86h8MsQgR88TvSmNXxv\n2kmMHj1a6a2lKlN03rI7kEXJYDCoiE78SsR9ThYSAWxx9BPjK9Fbt7S0cOSRRxKPx6mpqcHhcDBy\n5EjKy8vZunUrJpOJc889F6/XqxrcZgwGVqxYQWNjI11dXbS0tFBVVUVlZSVVVVVZYDEYwGDA4LJS\n9Ntzv3Gdum0QKOjl0rMPJiGVxlRWSOF1xzN48GBGjBjB+vXraWhowH7WYVjHV0M8gfv274Mp68b3\nzjvvsHPnTqDXdrasrIy6ujr177KyMpxOp5I66s16CwsLsdvtKiFrtVr55JNPOOWUUyguLsZutys3\nQKfTSWFhIUVFRZSUlFBSUkJFRQXFxcU4nU6KioooLCzE4/HgcDjUNRebAd3A69ta2OXvEvf3A+QE\nJ/mRtT7H+xOPB+c4oCPsfJ1qfvJGXqODtN5dPB+o87lFucklYpHkk81my2mCm6+VdTqdRKNRBQyQ\nLa4587SZlJWVqapFoUwkCpeIWvdJNpvNqjJRvEGgd3chUaaAvagjJPqWLfyqVasYN24cbW1tZDIZ\nhg0bhtFoZOvWrWzfvh2AqVOnsnv3bk444QRWrMi66dmunETshX+yc+dOdu3aRW1tLQsWLMDn83HU\nUUexcuVKjA4r3pWX0/WzV4gu3UTBxZOIv/A+APb5R5HYvIeM0UCqJUTd0CHU79lDxmzAkEqTSaTo\nXv8FVVWDOP7443nggQcYOnQoqZYg9nEDwGTEOnUomIw0NzfnAJYsnO3t7arU3m6343Q6cblcADid\nTiVnBFTzCLmmv//977FarTz22GPf8EoXtUlhYaFaFCXKFntc6KXR9MhXFnmdBtFd/XTZnz6f9yfr\nywdhHez1kR/A9I+DaxzQEXY+WEuSUJf66TI+veOHlHXnS/7k3/labRmiupDf8p7ymPxtT08PwWCQ\neDyeU5wTi8UUMAgo6wlDoQ0kEShJVJH4CWUii4VeXAMoH+5oNEomk20wK4b11dXVCuTefPNNtm7d\nisFgYNCgQQD8/e9/z1HeeFdchuvmk6n45BbsF0xk3CGH8OijjzJq1ChOPfVUTjzxREwmE8XFXuIv\nf4z90smkdrWT2t6aPVkGMBXbccyeTKapC6wmGhsaMBuMEE+SjiZoGXM3toYIZ511Fq+99houl4tJ\nkyaR/Ptuoo9sBLORjtOWMqC8srcwxWrCdefplH+8MBvd2y2MHz+eyZMnM27cOKqrq0mn0xQUFKjz\nLBSBKFEMBgNr166loaGB5cuXq0VOytLFAkC65ng8HhVRu91u7Ha7WkB1KZ9cU11SqAO2HEtf1Yj/\njjSvX4/dP75tHNARtoCm8Ixi8pMv5cuPnPRuM7rntZ4s6msLKolIoVLkeVFv6I/JNly23XJc4XBY\neYdIdCwJrEgkQiqVbTUl30mKQKT6UCI8AXjhpEX/LZSKRNqhUIgvvviCaDTK2rVr1THqLbakw0oy\nmeSII45Qi4Gp2qO+u2lgMaF/fkUwGCSTydDY2Kg+78RjjmPl8tdIdvdAKkNBOojRZqO7p4foix9g\nrCjE4HVCV4xEIuvlgcEAsSzfHSbKzTffjM1m45hjjqGzs5MTjzme9976G4ZUhkwwTlOwEYwGCs49\njMQHe0nubMNY7QGTAYPTRlFRkepnWVxcrBZTu92e07otkUjQ2NjIli1b+Oijj5g7dy4TJkxQICc+\nLXJupBWbzCOhPHQ9tj5n9DkgoC9zQ28YnZ9j0eer/m95T/3v9Dmog3M+1dI/Dr5xQAO27synZ9Z1\nIJZIWV6bz1NDL+jK6+XfegGLLv/TP0f+Pj8q0jvaiG9zOp1W3WecTqeKlB966CH191VVVcyZM0cB\nt94oIZ1O5zSdlYhdijpEPQLkdGKZNm2acsZraWmhs7OTqqoqpWGWBUzc/b766isAun7yMkUPnU2q\nqYvI/3uXQ8YdzsaNG9XCmMlkmDp1KitXrvx6J5KBAgvpeEKpVNLNXaSbu8BuhkTv4obRgGlYOSWv\n/RD/jN8x1jmAww87jDPPPJO2tjZee+01vJ5i4tEYFdXVNHa0Uv7xzzGVFZKO9NB+9BKSW5up2LWI\ntrF3U1dXR3V1NTZbFrxNJpPqmHPbbbcRCATIZDLceuutYDJAKnutnnnmGV544QWGDBnC+++/ryJg\noa3S6bSyshXAFrMp3REQerXekGutqlfb6gCdP5/yf+cnImVeylzXTaf6SlL2j4NvHNCArXei1k3k\n9ShFp0fybwA9QtFLwYGcxyWa0l+Tn7WX5/TCFo/Ho5QHOgAnk0n1uMlkUuXUooPesmULhx56KIAq\nbRdjfn0hEee/fM1vIBCgvr4eu92Ox+NRbn3Nzc0KSJvaWqDQpiolISuZ27JlCxs2bKCoqIjUzk46\nTv4NBqORQwaPZOLEiVlFyNcLy6RJkzj55JNJJBK8+8k/8T4/G6PXSec1f2BgVwWDqgbw3tYP8b44\nF2NpIZ1Xv0RpR4aOYAD3C5diPbIOAOePjqX1oX9y2WWXUVdXx+bNm5WkUHYLxkIbprKsLNLotGL0\nOggv/SvJD/dR5i1lypQpqqBFFjDxAfnlL39JLBbjrgfuIzSpDM//Ox96UvjPfILDbQN4d8M7OedV\n6A25tgaDIafrej71IfNBtzTIr1zVKZK+hlzDfF46P9KW1+oRdv579kfYB+84oAFbWkDJhNYLXvRC\nEz3yyb8BdLMlGX3JroTLzo+I9H8LzSFl5+KAJ0oRAVSHw5HTBUbvcJPJZPB6vXg8HuLxuOqYnm/D\nmUqllIOfLBLy+bFYjMrKStVtXABMVYAWFUBPChLZSNc4shxTYQHhf9azYsUK7HY7v/3tb9mxYwfb\nt2/niiuuoLS0lMLCQtra2li3bh3Tp0+npqaGiooKbrn9FzgXTMc6ZTAA7gdm0XLu77HbCyj86XQF\nzEW/mkXHmU/iKnSR+GCfejyxeR81RcWqS8/GjRt54403FAAXFRVB014iS9/Ffulkuv+yndTOdio7\nzQwfOpbZs2crykG+r8gZoXcH1BkJ4r78BxjMJjCbsM89kj0P/l2dU7mGejGMzBEBcJlbutpDAgLd\nGlUAWnYufUXT+nzLDyTkuPU8jQB1X3NRn/+y8PSPg28c0IAtetn9ATbk6rB1INdvBvhmVl4oBx0M\nRbWhvx56o/N4PE5jY6OS+JWXlzNgwAC1qEhySgpZRMkgkXUymaS6uprRo0erUnPhTnX6o7CwMOfY\nhSMHcLvd6n2FTrFarbS1tWG324nFYjjOOZyi+88gdP9bJHf78Dx2PgaDgcjjm0g++C6vv7wKh8PB\nUUcdxY4dO5TEzWq1UlNTw2GHHaYona6uLpwFBbTWB9R1STVk7WVdzkIadvt7H9/Xicls5rFfPcSF\n82bTs3EX6VA36a0t/HrlKrq7u9m3bx+vvfYaBkO2AnHYsGFUVVVRW1vLaw+8QfD2P2Fy2PjR5Vdx\nyimn0NHRQTweVzyzNDeQCFRsZDOZDHZLAd1/+QLrlMHZJO6b2xlVVZ2zUwJyImEBb32eAd/go/Of\n14MBmUv5tIU+N+Vz5d99ufLpUbX+WTpw60nO/nHwjQMasJXZ0NdDJrQeweiTNx+UdQlgX0kjAW79\nRs4HeunCnUwm2bdvn+paIl1fSktLFf0hEaOUTgNqEfjFL36Bz+dj6dKl/P3vf+fII49Un1lQUKB8\nqSUZKaqGTCZDKBRS2l9dhy5mTpWVlQwcOJB0Ok1ZWRmfrv+CdKSHdEsQ66TaXhnjEbVEE+vYs2cP\no0ePJhwOE41mqxErKirU+1VVVamOO8lkkrvvvIszLziXTCyBsayQyH9t4uc//hnTp0/n1DNOJxNP\nYKxwEX3iPW5dcDOjR4+mxOnGv/4LABYuXMjPf/5ztmzZorrsFBUVMWbMGAYOHEhFRQVOp5MHp0+n\noqJCyRd1r3NJ7grQiReL6NSNRiMXzjqb/3r8abrf3E4m1oPRF+ePn277BtjqQJof5Uqhkx6By7zT\nFUbyI8eo50VkyGPyefnzT94//3P0n2+jUvrHwTcOaMDOB+f8Sa5H1vJ8vixPnu9rC6n/nR7VyA0i\njW8BOjo6CIVCSj4IWb/ucDis/LH1xKPZbFZ+2pDVaZeVlTFw4EC++OILjj32WKC323lRURGpVErJ\n9cTDBFBSNFGfCAUikXxlZaXirouLi9n3wnO0T7gX7BYMm77CPms8BpeNyK/fxm628eqrrzJgwACa\nm5u58cYbufbaa5VuW87Lli1bKC8vp62tjSuvvBJjIk3sxfcZWDsIi9XJkiVLuOeeewCILf+A2tpa\n/r9f/4bXXnuNu+66C6PRyPjx43n00UfJZDKsWbOGsWPHMmvWLLZv347f76e2tjbH1lY8u0XJIbzy\nwoULaW1txWQy8eyzz2I0Glm2bBlvvvkmyWSSSy65hDFjxjBs2DBuuu6niiN/4d0XKCsr+8Y1l0VP\nj5L/f/a+PEzSqrz+fLV0Vdfa1XtPzwbMwMywNuAw/sAwyGokk3nUsBjISEQRTRBRRFEUcGFIggTi\nEqOoLDFiNCxGEQHBwKggIyowwAzTM0Pva+1Ld3VV/f4oz+1Td6oHQpLnae1+n6ef7q7lW+5377nv\nPe9538tYCfuDetUM2lImass+ARjppcZYCNRaR7te37NBvN5r9bz3RVt4Nq8B29701PaSgVrQVg+o\nHhdoG5eyPLYmz9Dz5sBMpVImUYWeD5N0+D8LQuXzeQQCAbMzjeM4aG9vx/T0NPr7+3Hqqaea77CA\nETdWYEIM9yPk5yjnI5gXCgUEAgH4/X4EAgGsXLnSfO6z13wau3btwuTkJH76xM+wb+1nAQCN0TCO\nP/pY7NmzB1u3boXH48EZZ5yBXC6Hvr4+rFixAgDwyiuvoLm5GZlMBueffz7e+MY34hOf+IQBuO7u\nbvzJn/wJTjjhBLz00kvwer3YunUrfv7znxuVSX9/P7Zv3454PI5YLAbHcZBKpbBnzx5873vfq5Go\nXXnllbjrrrvQ29trJHfvfOc7sXnzZjiOg7POOgsAcNdddxkwPfTQQ3HwwQfj61//ek0lw0AggJNP\nPhlHHHEEWltbzTNU+aZ6vMwoJfgSgOlBqw6f/YrtoIDNSd9WdvAZ2tpsXQHO5S3r6zZvrfezaAvH\nDgjYfX19+Ku/+iuMjo7CcRy8973vxWWXXYbJyUmce+652LdvH1auXInvfve7pvTmDTfcgG984xtw\nu9249dZbccYZZ7zui6vXKfU19WbqLW9t5YdtHMgMRNWjUvx+P8bGxmoSdgAYGVgymTSJHHyPG8YG\ng0E8+OCDJtUaAJYvX46TTjrJXDMnHL/fbwKQTG4hP00PTXel4WYHjuMgEokYaoAc77p16+A4Ds4/\n/3wUCgWkUinMzMxg3759SKVSSCaTGBgYwO7du7F27VqMj48jEong+eefh8fjwTHHHIOxsTEMDQ3h\nmmuuMZNPZ2cn9u7di/7+fjz88MNYs2YNbrzxRmSzWXzlK1/Bxo0b8fDDD+OEE9OhmNEAACAASURB\nVE7AyMgIotGoUXHs27cPfX19qFQquOiii7B69WokEglEIhG4XC4cc8wx+MxnPmOeA2MYp512Gp57\n7jnzzGZmZrB27Vqjc+eERxCNx+M46qijTBvbz1X/56Sby+UMN05axNb083VOohor4XHVm1aJHyks\nuy/PRZPYsRqdCGx6ZNEWjh0QsL1eL26++WYcc8wxyGQyOO6443D66afjm9/8Jk4//XR89KMfxY03\n3oitW7di69at2LFjB+6++27s2LEDAwMDOO2007Bz587/cYBEgzL8zWPaSQl2HWxbG0uuULWzHHB6\nnaQ2CMpUJfB45JcZFKNH7HK5kMlkzG7kLw/sQ/P9l8B7dDcyn/8JRu7+rQmi0ftjXZFwOIxEImFk\nZhzMHo8HyWQSra2thiZobW01YE6g4b6I/A4DdaRoqGA577zzalQNRx99NB555BFTRjUQCODOO+/E\n888/D6/XizPPPNOcn7JEj8eDnp4elEolXHvttTj33HMxNjaGbdu2IZfLYXp6Gn/xF3+BJ554Ap/9\n7GdxzjnnYGZmBslkEl/72tfwve99Dx/72McMHUIPlDw6Acvr9Zqd0vX5ATCSRe0XuVwOLpcL3d3d\nNf2CP3Zgj5seELjz+bwBctIk9WIdfG56HPLz/AxXV1w1KL9tg7S+rgFJzR8AYEB/Mei4MO2AT72z\ns9PohUOhENauXYuBgQHcf//92LJlCwBgy5Ytpqrbfffdh/PPPx9erxcrV67EqlWr8NRTT73ui1Nq\nQzclAGpriKj0j/ZaOD47Gq+cdzAYhM/nM54pt+nSzzN5gxX3ZmZmMDExAaDqZe/btw++09fCd+LB\ncIV8CF//p5hKZQwIaGF8AAas3W63SZ6Znp42daEZACXA0QtsbGw03rYJMMqmxKRKNGHk4x//OD73\nuc/hyiuvNGVUTz31VFxxxRVYvnw5Lr30Ujz66KMoFAo44ogj8L73vQ/FYhHXXHMNBgYGzE7ja9eu\nRTgcxiOPPGLaxOVy4bzzzsPdd9+NY489FiMjIwiFQkaFwnu95ppr8L3vfQ/BYBAA8Mwzz2DTpk14\nz3veg6GhIXN/GlhWcLbropNjPu+88wyYal/SQCGPTe86nU4jkUjULcmrHi8BVTdM4PG1PAI/wx/d\nWYiTqt2X+T3byeBn2F/5/6ItPHvN0/TevXvxzDPPmKVuR0cHAKCjowMjI9XaEoODg2ZAAsDSpUsx\nMDDwui9OB0i9BBm+TqBVegR49QQD9WDUqwGAlpYWs28ggJrEHfUI+T0OxlgsZq7R7/dj5qURVErV\n65l5eQzwuMxxdKkNzKaws3QqQTYYDJpVgcfjMZptr9drqtaxHSgL5DVSCUI1CNujqakJbrfbaMhn\nZmZw2GGHAQBOPvlkjI6OmkDkG9/4RgSDQaxfvx7xeNzUzM5kMjjllFPwxje+EePj4/D5fDjllFPg\n9XoRiURQqVTwowcewHSxiCeffBLr1q1Da2srVq1ahZaWFrz//e/H888/jwcffBAXXXQR7rnnHjzw\nwAOIRqP49Kc/bZ6LlsFl/RB9tuVy2ewyHwgE0NPTs9+zr0dxlEolZLNZTE5OYmxszOi6GTtR9Qf/\nB2apNC1XYNe00R/2Da1HY6tBtF/PpQbR9xeDjgvTXlPQMZPJ4O1vfztuueUWowGmvRoozvUedwYB\nqrtub9y4cb/PKCDa0Xe+T9Mls3boVwNsUiEEUbfbjebmZiQSCWQyGeTz+f2Sc/hdyu9KpeoGBXru\nqakpbNiwATv+7S5MnPZFeHuWIX/Pb3D0uiON9pteMOuH6OTxyU9+Eg0NDbjyyiuNYoTcdUNDg9lt\nJhAI1OiA8/m84bd1ec4Sr/Q8P/7xj8NxHBxxxBE4++yz0dDQgP/6r//CiSeeiIceegilUgnd3d3w\ner0YHBzE0UcfjWeffdbU3qAq4sQTT8T111+PcDiMaDSKX//617jkkkvwpS99qdpGHiD47g34wRd/\ngB/+8Idwu90IhUK46KKL0NTUhOXLl6O3txfvete7DDX03ve+F1deeSWi0Sji8bhJFQeq2nxWPVRv\nm4DZ09NTo6GmkebQoGGpVC2lOzY2hnQ6bV7ToLN6uqpCsr169iX2E8o5tV+x37DP2H1X9daqDimX\nZ5N2dNOOevbYY4+ZYmCL9sdnrwrYxWIRb3/723HhhRdi8+bNAKpe9fDwMDo7OzE0NIT29nYA1Wpx\n3PkaAPr7+w2XaJsC9lxmDwTtxHNpXBU0NVGhntnctuM4iMVihoagxM72fDTpolQqYXR0FAcffDCS\nyaRJfpmenkYoFMJfn39BldfdNo6DN/wJjj322JolMUGbIOHz+XD77bcjHA6bSn0csA0NDeZzPAZ3\nf9FiT6Q9dC9KbbMvfOELWL58OZ599llcf/316Orqwlvf+lY88MAD+N3vfmdWT+VyGZs3b8a3v/1t\n3HHHHVXgWdWGL379n+H5Pc++ZcsWzJRmgIgfQ8lxOIXq/o+lchneNx2C1nvfCwBoOH4Fclfch89f\n/WlMTk6isbERqVQKr7zyCqKxGK786JX4mw/8DdatW4e7774bTU1NSKVSmJqawkc+8hFMTk6iUqng\n3e9+N+Bxo1IpAzPVZ3vffffhwQcfxCWXXILTTz+97iStIE3QzeVymJiYMKVbNSmFlJOmoLMvqS6b\n7aRgzj7KdtcApSbtzOVJ26/ZCTx2jRM12/m57rrr5ur+i/YHaAcEbA6QdevW4fLLLzevb9q0Cbff\nfjuuuuoq3H777QbIN23ahHe+85244oorMDAwgF27dmH9+vWv++KUd7Qj6OpBawCnXjBHg49KRegu\nLy6Xy1SBi8fj+3lwHGzKl/Mck5OTJk2ZdbIrlYpJ9jjllFNqijlxWV8sFtHa2moGu8fjwSuvvII9\ne/bg1FNPNXsoMtORATVeL6mRfD4Px5ndAIGqCVIoXI4zCLl8+XKUy2UcdthhOPjgg7Fnzx5ccMEF\nOPjgg02C0P33349cLoe1a9dWPeavfxVtj30QntVtmNk1hvGNt+DaT16LL379q8i8qRvRW95Wrd/x\n9tuwOhfC8797FsVf7MFQ9yfguBw0f+9ilMol3HLLLXjllVdmH7LLwdRfHoGXv/5zfPCDHzR67E99\n6lMAqjTRrbfeilwuh+effx63fPVLiNz45/BtXI3c13+BwjefxMc++GG43W4sW7bMVDnkc9e+RCXN\nzMwM0um0KVNLgObzpNcM1FbI00mb/Yj9Q6kNfpexCLt/HshDptl0zKItGvAqgL1t2zbcddddOOqo\no9DT0wOgKtv72Mc+hnPOOQe33XabkfUBwLp163DOOedg3bp18Hg8+PKXv/w/4tpsXs8GY/VcaMpL\ns9Pby1Eeg5F99awnJiZMFp1y5TYdo8Em6rR1QwQGxDKZDCKRiPkOPV7ufJLL5VAulxEIBOB2u3Hn\nnXdi8+bNZnsv3YXG5/Mhk8mYxJlsNgu/349SqYSmpiazSUIymTTlWumVk0rIZDKYnp5GLBbD+Pg4\nXnnlFZxxxhmIx+Po6OhANpvFt771LaxZswblchnXXXfd79uzjPE334LOvs9i6ql9qEwV8elPf7ra\n6HcPoXDvb9DZ91kUXxzG84mqx4qZMuBy0Hz/+5D8m+8i7PZjdHQUn/jEJ9DV1YUrPnEVAv+wCY1v\nOwbha85C6tM/QuuP+/HlW25FpVIxe0YmEgmUSiXs2rUL3jVdCPzlGwAAoU+dhew3f4nBwUE0Nzdj\n5cqVGB8fR0tLi+Gqc7mckTAODg6aOub0rNPptHkWnNw0AYYTrQYsAdTULVeNNq1e+vh/B3zZ9+qp\nQV6Nhly0P147IGCfdNJJc3oCDz/8cN3Xr776alx99dX/8ytDrRKknmeifyvfqANjruWxei8MvI2O\njtbI6XTQ6vf03PSsKe2jJA+A+Z+DnBQIgJqiQawp8sgjj6CxsRE9PT14/PHHDU/OCYBefrFYNBX+\nABjdNieOeDyOlpYWQ9kkEgm0trbC4/Fg9+7d+Oxnq4k0xWIRFVRw/w9/AM+DP0Zlpnqf3d3duOCC\nC5DJZAAAb3vb2/D9/7wXzfddAgBIffw+wOWCU67A429AsTSDzr7PolIqo+ENK7HslRJ6d71c1ZZP\nTyHxF9/A0rZOxKfHcdZZZ6G9vb16brcL7iVR81zcy2OYnuk1qxO/349isWi2/YpEIig9k0KlWILj\ndaMymUOlUEQkEkGhUMD3v/997N6926h3gNlgsNYfYZuyeFZTUxNisZjJtPT5fDUKHk3AUvqNG05o\nIFFXX5rU9VoDhXbQ8fV+ZtH+OG1eZzraAE1vl+CsyQVzFd850DFdLpfRLo+Pjxvpng7KuY7JAcNB\nyYEbCARQLpeNR0wAV42xJsVoEaqdO3didHQUH/vYx8z5b7rpJnzoQx8ywMM0dQI+wSSZTMLtdiOR\nSKC9vd141NRqE3iOOeYY/Ou//ivuuusu/Of2n6Hlh++rlkx9z7+h6cU0rvrgFYYmaG5uhuM46O7u\nxvpjjseTZ/8z3LEgkJ1GR2cnRkdGsLRzCfbs3YOxN/wDKvlpePJlvO29l+Lv/u7vkMvl4Ha7ccTK\n1diyZQuuuuoq/O53v8OPfvQjuFwutHe0Y/TK+xD9l/NQSeaRufEhnH3mnxsaIZfLIRAIYGpqCul0\nGhs2bMD9P3kAE2/5CnynHYr83c+ge2k3gsEgduzYgV/96lfGC6YHzMxUPjOqbNhnmEQ0OTmJYDCI\nSCRilDYul8tMilQF2TVG7NWXrsDsGjdAbbLUazF+Xo+jmvBFW1g2rwEbqPVwgFnOWnls9WCUDuF7\nDNrxfxqTXZiYoUFIlWzxvDQOVAItl96xWKzmWhk0ZFo5uXPSGKzSRyC/5JJLDAg/9dRTeOSRR/Ch\nD33InI9AzWtgESiCE5Umo6OjRj1SLlezKNPptClI5ff7sf3Z3yJ46UlwL40BAEIfPx1jm76G7u5u\nUyOFHvaXvvQlOI6Dww89DCeccAJKpZIJQu7ZswdutxtdRT82nLQRRx11FHw+H970pjfhl7/8Jd7z\nnvfgX/7lX/DjH/8Y5XK1xOxnPvMZvPDCC7jjjjuwet1avPyWr6CUmQIqFfz7v/87LrzwQni9XgwP\nD+Oiiy4ygdwPf/jDuPJvL8c999yDybt34pjl67Bx40aMjY3hySefNEkl9MwJ0ACMFFBT0qlpp/TO\n7/cbCoU7B3m9XrMHJ3lu7gKkAXE7E/bVrJ6HbMsQtb/r+xq4XLSFZfMasLkRrQaFNLCjnrWt9lDP\nmINUFQD0nhKJRA1vqcbJgufWSD+DhHyd1e3U+1H1gGbGcedzUh0E3McffxyPPrUN5ZkSfG4vXOKZ\nsWIdAZ0bxGoSDgGb2uzh4WEsWbIEY2NjCAQCiMViiMfjVZ10YwDjT/cj8Pv2Kv52AA2/lwNSkZJI\nJHDppZciEolgdHQU3/rWt9DV1YXHH38cxx57LA477DC88MILeP755zE4OIiBgQG0traiUqng+eef\nx/Lly+F2u9HR0YEXXngBDQ0NOProoxEIBHDSSSfhzjvvxEc/dAWamprwk5/8BLFYDDfddJOZ9P7+\n7/8eq1atwgc+8AHcfPPNuP3223HxxRfjbW97m+kX09PTePbZZ5FKpYzckO2qUkz1anWyZ1uyz3DP\nzWw2W/OcuBpT5Qh3UWeNcmZMKqVmy0vtXAL2WX7GBmL2Y9tRWcx0XJg2rwGb4KTADdTfgEDlUxo0\n4kBl8km5XEYqlTKccKFQ2E+mp8d+NVqFv6mL5kYCCijkqDnYGAjlgC6Xy3jhhRfwyM//C023vROe\ntZ1If+pHcP+y3yzfyX+zlCglZI2NjZiamkIulzM7tDNzDwB27tyJcDhs7j8cDqNYLOKvL/prfOy6\nazD51q/C1RbC1MMv4ooPXAbHmd2AgUoU6qA7Ojqwa9cuTE1N4Q1vqAb+li5dimeeeQaRSAQvvfQS\nlixZglwuh8nJSRx33HHYvXs3BgcHEQiFEAqF0Nvbi5aWFuzbtw+VSsXw02effbbZ3Z10T29vL66/\n/noAwGmnnYYvfelLhsPnyoL1SVQeCcCALwDzTFUOx88yqEtaizQW1TcuV7UOerFYNBsc04LBoJkk\nmKzEIl7sT/xND1/7Ma9LnYV6VJ7tSCxy2AvX5jVgA6hZ8ivg2YBaz+tQDpcb4HKZT+UEPRcCI81W\nn9hGWRfPqRvsMkHDcRxTZtXeloqTCcuiPvfcc/BvPhr+M9YCAKK3vB0jq64zWmqlepSSAYDLLrus\nZjL7whe+YGRs5NOj0ahRjBQKBXR2duKmz27Fj370IxTSBZx69TU49thjDa/OrcdY/rRYLGJ4eNhw\nu7t27cLy5ctNrZh0Oo3m5maMjIxgcHAQAPDII49Un1lzEK73n4ixrz6BRF8SW7Zsgcvlwrve9S5D\nFWlhJILozMwMWltbMTU1hXA4jFKpZGp9kF7Ztm0bxsbGDEAzSYh9R58XnzvbkbJHth0nWo0RkMLS\nglCksxj41R/W8db78Xg8ZvcgUij03jnx1ivBCtRy3prA81qpl0X747J5DdgH8jTm4vCU9qAXnUql\nkM1mDZBGIpH9uEEG9OpNBPWMA08LAHEAa6o4TUEXgFl6E0B8Ph9KeyZmQbk/DsdbHdAMfOkEwx9m\nADIzEIAJGg4ODqKrq8soRAiOLEXa2dmJd77znQYsxsbGEA6HjUpifHwcl112mblXJ+JH6a96UP7m\nL/DTn/601stzOUi1efHE07+Er+LGCSecAJ/Ph19k9qDlJx+A4zjwv+1ojJ3wD/j+d75rzkFJHDcZ\nZptzImNQkP9zh3kAePrppzE6Omral0Cmz5LArBI9tqF6uqr2aWxsNJtWEKRZf5xeNPsjNe5TU1OG\nInG73SbYyc+zNg3jGZysNRmnnvxUqRVt70XAXpg2r4kwAoX+BmopEdvbdrvdphhSoVDAyMiI2dKL\ngzQUCtUEcHTQ0Oodv54phUK6gkttAoUGChVwle446aSTUHp2EPHzvoX05x/E5KZ/wdFrD0epVDLF\npZRCsflP0j4dHR1oa2vD4OAgotEourq6kMvlMDw8bECPIM8lPeWH5XIZ6XTaFLzq6enBt7/9bWza\ntAnetV3o2P1pRK77U7T97HJU3A7uuOMOvP/974cTbED7M1ehdduH0PKf70OhMoOLL764Gqhb0jRL\nEXRGgFLZTBikKJhoZKeau91ujIyMmE2Hqclmmdjt27cb2oZ1V4BqsDedTqNQKJh7ZtBQd+ux4x52\nHyCI03Sy5STP5+h2u01iDidMoDrB5PN5xONxZDIZsxKjQ6GKJDX9Xydo+7kv2sKyee1hE5iUg1TQ\nqrfkDQaDKBaLRulAz0uXt7os5rF5LoIJMEtdkErQYBVQHdyNjY1obm42PLsupXldmlxBcKe3zwJN\nXq8Xf33+hXjssceQfeElrO/ZgP/3//6f4cunpqZMRmMul0MwGDTnBICbbroJjuNg9erVePOb34zp\n6WlEo1E8/fTT6OjowFFHHWW8QO4ZyWslP06A4vKde1Sm02m4D2qB83sQci9rAsoVk5bvXd1h1Cbe\nY5bCFfJhz5492LhxIx79/GeQv+e38B7djfQNDyHS1mwyNHUSsmVwu3btQjQaxXe+8x284x3vwM9+\n9jO0tLSgUCigv78fTz75pOGbFfx5P9Re01vXLFDeK428P2kHFrjiMdlHGGwkQNNr50qJ8QvtX7ra\nokdOntvv99dIP7V/2LJSpUS0vy/awrJ5DdiaxALULgNV2uQ41eSTcDiMcrmMRCJhvFJ+j5+lpE49\nKZoGE/m/LkV1kBDQIpEIIpGIUXFwt5l6XjmLPOnSl8WaSH2cffbZNQOTg5uTDcGVhYsCgQAuvvhi\ndHd3Y2BgALfddhui0SiOPfbYap2OaBSxWMyABb1ZWyLIcq4ej8fcA5UQf/qnf4qHr/4oCg++AG/P\nUmRufBiBWASBQADr16/H9390P2Z2jsJzaDumntiNSnYKS5YswcEHH4zLLnk/vnLlNzBTLKKluQW3\n/uMXTSErFq9yuarlWMfGxlCpVPBnf/ZngNuBe1UHJl/qw8033wyPx4MTTzwRLpcLvb29JguSE62q\nf/ijlfny+Tw8Ho/xtNmm9gqOdVq49RqfJSWYPB8nSwVfnpdtzevhBKUUGPsn64HPpRxZtEVTm9eA\nTU6Sg08Da2putxvhcBgulwujo6OmDggDVwAMIOrgsCkPVXLoNdBzU0rDcarp7M3NzYYrr+c1chDW\nq0HCAU0AoGqlXC6bfSIJMqzSRu6bYDo9PY2mpiZMTU1h+fLlWLp0Kfbu3Wsq+h100EFYsWIFJiYm\nEAgEzOYKuuIgF09eld47vdJ169bhby5+H77yvttQmppGOBbDF2/+JzQ1NaG5uRlvefPpeGDjLXC1\nBFGezOHCc96JFStWwOfzYdOmTdi8ebOZ4Ng+LpfLXEe5XMa9996LbDaL3t5eXHLZB9D607+Fd00n\nSgMJjG24CYevXotQKISf//znGBsbMxOvJjpxgtagLicintOOJShQ0gngZKhBa05mzJjkM2epAe4U\npBSbBqY1qM3+wR2CQqGQmfDtlZhttlxw0RaW/UEAtlIUduCRu6+USiVMTk7WqAg4oAmeXMrau7HT\n5hoMKgkjODQ2NqKlpcVonrn85gBmbYpSqWSUHnpf9j2Q/3Scqo46k8mYTX3p9WmKPOmbkZEROI6D\n5uZmTExMYHBwEKtXr0YoFILP58Pq1asxPDyMUqlaLnXp0qVGYsbAGpfyCqZsaybenHvuuTj77LMN\nmFPGWC6X8dGPXIm/uuBC7Ny5E4cffrgBIJ1gCVgMoPK5Tk1NoampyQQK+/v74WoKwLumEwDg7m6C\n56BWI10cHh4218yiWPReeQ6lFThR6I42+hwpkVR5H8E/mUzC5/MZeoTPjdfK42p9bT4vbUftT7q6\nIGj7/X6jBeeErH23Xj9dtIVpfxCArUkrBFQOFu4HODw8bOpHALPejQb3SCXoMtqmOTgoubwl/60a\nXnqfVDZokga3mlL9MpfM2WzWHJecJfXDVBfMzMwgkUiYwk3Ki7INeE0zMzPo7e3FE088Ye4hGo3i\nuOOOQzqdxpo1a5DL5YyemOnr7e3thpdXo9fKIJ7q2TkpaD1m/l0sFtHR0WE2vSU/z/ajVlwnTGrK\ng8Eg3G43kskkCoUCVq1ahUoyj6nHd8P3pkNQfHYQM71j8BzSjKeffto8Px5Dde88pwYUgdkJg6Ct\nIEjvV1c7BPFisWj2soxEIvtlmzKLVb115eHV2eBrPAYnaXrWmkfg9/vNBK7XowHKRdBemDavAduW\nNCm/VyqVTNLFwMCAAWsOFA0G0aPi+0AtraIDjd6RrTwhYPN/AAZQNfipXjYHNJUKrJGhXhx5VgCG\n+uCkwa3BotGoWd5TgscdZH7xm6cR/uRZCF56Eqa29SKx5U68/PLLOOqoo0zCTnNzM/L5PDo6OhCN\nRjE9PW226GK7vf/978fJJ59stuui98p7YDafptpzCU/wJJ0wNTVVkz04Pj6OcDhswJzP5frrr8eT\nTz4JAHjDG96Ad73rXXC73XjraWfih+d9E07Ih3K6gNZoDCMjI/B6vWbXHNJHlAcS1PjseW5Vf+gE\nrZ44OWb1wAuFgukL8Xgc5XLZxCp0padAr+fmc2V2Kld45K3D4XDNbu2qRolEIjUbMauTof1y0Rae\n/UEANrB/TepoNIpQKISRkZGajQb0s+zgHIjqrdsBRgA1g96OyuvWXDwmy3ICqPGE6YWxBgYHLK9N\nl75cGufzeZOpSC6Zlf1SqVRNRT6WTqWXHrx8Y9UzO/UweHuWI5et7gDODRUqlQpWrVplgmkzMzO4\n/vrr0dPTgyuuuAKVSgWjo6MolUooFAoGrFl/hBQIVwRer9doigneVGVQr0zaIpfLoaGhwQQyy+Vq\n2vijjz6KJ598Et/4xjfg9Xrx7ne/G08//TSOPPJInHnmmejs7MTLL79stvAaHh42AKyxAVIKgUDA\nrCSUilDgPpBnymdNtQfrjHDllE6nTb0RTmCclIHqpM+d123w1kmfE3hzczOCwSCy2ax5JgTxYrGI\n5uZmE4cAZnddrxcsX7SFY/MasJUG4IArFosIh8NobW1FMplENpvdj3emBw7Mesi6fFdvmZ8HZrll\nLlt1WW97vxzgXH6rR6oJNRzU5Jy5zGW9Dt4ftyKjJ6r8Lz1X6nt9Pp/RGVeKJZT6E/Asi6EyNYPS\nnnH4lrWgWCzihRdeQLFYxLJly4ynx510xsfH8Zd/+ZdmEmhubsbMzIwJnOVyOWQyGTNxeb1eA/5U\nObB9XC6XkailUqmabeRYn9vtdmPnzp3w+XxobW3Fb3/7W0OjDA4OoqOjAw899BA6Oztr6qYkEgn0\n9/cb9QrbhM+Jsj2ei89TgVqDynY/YdvqKkl3nOfEo31BvWsGggHUZC9qkJUOACdbetXhcNiUAeCE\nR6pEg8NaaGox4LiwbV4DtuquAZgsxWXLliEejyMej9fwfPSQaRy0ykdrENKW7HFw2x42ByWXtOTH\nGUgkp00FAflhDjbywrbKQwc6J4VkMmm8WmbQ0Yun4oF6bI/Hg+4l3Rh6863wv/UITP9iD3xTQDgc\nxp49e8zkND4+bgKl1Bl7PB585CMfQTqdRltbGz7+8Y+jubkZlUoFiUQC4+PjCAQCiEajaG9vN/y7\n3+83QB6JRAztQv6eqfkEoFAoZEoCLF26FKVStT73QQcdhP/4j//A9u3b0dDQgL6+PoTDYTOh/Pzn\nP4fjOOjr6zOZhXaf0GfHdiK4apxCn+Ncz1udAwA1AV9dXakun8fQZ6uSUT4j3VuT15/JZEzAlbTa\n9PS0WYWQ7mH/UmrEjr0s2sKxeQ3YlJzxx+/3Y9WqVUin05icnDQDWb0o9aaA2UFiD9q59NbqdfE7\nVAjojiSq8QVmvTsOWF4HQZ5JKhz4vFbSDADMkn5yctLUZNb0bU4GHNwAVfR4kAAAIABJREFUcNZp\np+PFF1/EwOMDaGtbicNPOhzxeBy7d++Gx+OB3+9HU1OTWa53dXUZT2/Dhg3YtGkTrr32Wtx44424\n5pprjLfJICOBlxv4plIpU1dk9erVhtfO5XKG3kmlUigUCmhpaUEymURDQwNCoRDi8bgJ5h1yyCFY\nv349rrvuOrhcLqP73rt3r0li4S7m7Af6vPhs9Znz2YVCIUxNTRkvXUFO09NpCv4EW8rtMplMTf8i\neGpQln/zuSgFpvw2V2n8bDabxcjICHw+n6mVwnsol6tZpz6fz1RQ1D65CNgL0+Y1YAOzFfQaGhqw\nfPlyADA7w6g8i6bqENIOtjcN7C+tswM6qsbg50mtkOpIpVJYsmSJ+Y4uq9XDY51lDYDy+gDUDHYu\nwdXzozdPYCR4d3R0oFgs4rDDDsMhhxxiJotwOIy2tjZMTEygVCphbGwMAIwHSgBasmQJfvGLX2DF\nihV47rnn0NvbC5fLhY6ODng8HkxOTsJxHGzbtg3XXXedab9isYjjjz8ef/u3f4uWlhYzySQSCcRi\nMTiOgxtuuMHs3RiNRvG5z33OSA/z+TySySQ2bdqEt7zlLejv78d3v/tdBAIBJJNJ7Nmzx9w3PVrd\nZ5ETsK2hBmbjF5wEqcDg81GwVqDX2ISd0chzq4qEz9jmxunR6yRP+aRK/hzHQSQSQSaTQTqdNtpu\nfl+dCPXYbRpv0RaWzWvA1g7a1dWFaDSK3t5eZDIZA8oqxQNqva9AIGA4WR5PTTlNDTBq8FE9Gk4A\n5CrT6TTy+bzhnSnvA2ZVCVxSM2XeXn6rl07A4OvKcysVwL+p8CgUCojH4+js7DT88eGHH45kMonR\n0VH09vbC5/OhpaUFw8PDJrvwxz/+Mbq6ujAwMGBomGQyCY/HYwr4U2/+uc99DqFQCOPj4/jUpz6F\njRs3GppEN0vo7e3FxMQE9u7di6uvvhpLly7FVVddha997Ws499xzDXi1tLTgqaeeQiKRwL59+5BM\nJrFu3TqMjY0ZyoftyKqD7A8qybRlmYxTsHIeA5P1wNr2Vm0FEekO6qJJe+i18L4J0Aqo5LF1dUBJ\nIksHNDU1AQDi8bjJ1iXFRm+dkzXPschjL1yb14BNwFuyZAna2trQ39+PiYkJAKjxdJQGUcDWQU8e\nGZjdCUYHvHpYGuDRABIHLL37XC6HVCplZHf0pHl9HGjkMoHZinvKiSoVQ4CgMkMlX/QcCfpUoXi9\nXkSjUVNYiHJDO/07kUjA4/HgN88/i5LXQf/gQDVRxe3GGaefjomJCWSzWWQyGeTzebS3txtOuVKp\nYHBwEE8++SS8Xi9aWlpMoHTfvn2YmppCW1sbIpGIqRudyWSMJC4cDmNiYsLcy/DwML797W+bZ+32\nejE0NIRgMIhQKISJiQkzSRIs2a58FuqN6nMnKFYqFcP7U70BoAa866lJNOZBlQ+D23aMZK5cAe2D\n7ANKlZHyCIfDiMVimJmZMd42J0Bd3XHDCs34XbSFZ/MasB3HQTQaRTAYxPDwMAYGBszr5Am5zAT2\nr2qmwAvM0iAKxPyfvxk40oAUKRUCNcHQcRwkk0ksXbrUeL22x8/zUn/Lwa8TAe+J1AevQ6kTSsm4\nIUI6nTbyP15bKBRCoVCoUWZolh7phlQug/ZffRTuJVHMvDyGsT/5R/T19aG1tRUDAwNm1UAvMJvN\noru7G47j4LnnnsMhhxyCvr4+NDU11Sz54/E4pqensWzZMhx99NH4x3/8RwDVTY7f9KY3YWhoyChQ\n/v2H9yF0+SkIffJMVOI5jJ/6TxgdHcXatWuNAkX7gQIsn0m9yVmfL+kU8uPk/SnZ0+9qoFnjGFSM\nMCGKz1O5ZnUcdBJW/b5SNloIKpPJIBKJGGqJ+m9OVOwPkUikhnJbtIVpB5yq+/r6cMopp+Dwww/H\nEUccgVtvvRUAcO2112Lp0qXo6elBT08PHnjgAfOdG264AatXr8aaNWvwk5/85H90cVyS9/f3o7+/\n3wCfTWXYy1EOGAVDDhR+h14al9g2R6nejXq/HEw8J8tmErhUb81z8bistdzW1maClsyW5DGZUk4a\ngMfS0q35fB4zM9VtrNgelKF5vV4TkGXAk5sONDU1IZvNwr2yxexW7lnVBlcsgOHhYbzyyisoFArI\nZrOIx+MYHR1FoVDAxMQEhoeH0dfXh1QqheOPPx6FQgGjo6MYHBw0nvnIyAjK5TK2bduG3/72t3jP\ne96Dyy+/HFNTU7j33nsRCAQwMDCA4eFhFKemEPjrDVUwaw6i8dxjkcvnDSViqy00DmGDNSc0DQRq\nTMHtdpuJv1gs1tTUrmfsL/wbAEKhkKnkyGdHMGW/1JRydQbUUaBxAmHBMMdxjMyPfUEzKTW4rWny\ni7aw7IAettfrxc0334xjjjkGmUwGxx13HE4//XQ4joMrrrgCV1xxRc3nd+zYgbvvvhs7duzAwMAA\nTjvtNLMjyeuxjo4OjI2NIZVKGemb8to0pRKU56zHbwKzWXy2MkSXvLbXxL/pzdLL41KWHlA4HDbK\nAtVg85p53o6ODrPRLTnLcrlsqr/pzjW8Hlaoc5xqDWlKz8hzcunP4FWhUEA0GkUul0NLS4vZUX1P\nbz+mt/eh4bhlmHp0J8qJPBCsUhIeT3V3nsbGRsORh0IhJBIJPPXUUybxg5rsYrGIoaEhs0nCyy+/\njF/+8pcG4Hbt2oW2tjbs27cP8Xgcvb29SKfTcNxuTP10JwIXrkdlegZTD70El1PdQJi0jybIKL+s\nf9ejMthefHaUNzY0NCAYDJoa1QDMRKeSUAYLNX3/QEE+XcHVu1abc7Z5eGbGMtVe09cdxzE73lBl\notvaLdrCsgMCdmdnJzo7q0V4QqEQ1q5da2iJeh34vvvuw/nnnw+v14uVK1di1apVeOqpp7Bhw4bX\ndXFDQ0Po6+szA5PLRJp2Wg5Qcnw2N2x/xw70AfunpWvKs/KRPAeVDPF4HB0dHWaAK6iQj9ZkHf5Q\nx5xIJGr4UqpFyGWqvpuep3LuXDlQWjcxMQGfz2d21iFwR6NRpFIpRCYaMXH2P8Np9KJSKMJbdoxy\ng0v6TCYDn89nsvImJycxMjKCaDSKvr4+c0+NjY0YGxsz8r3GxkY0NTVhYGAATz31lMlGbWxsxPbt\n2zE5OYl4PA6/x4PUx+5H7ptPojSaApLVXdMrlWpSDjM56wUClb9WmZzdJxRIld6oVKo6aCpIqHe2\nj0/T1Zs+v7nAWb1qlZfaDgQpNmrrlQZjf7c3WgBQIw1dtIVlr5nD3rt3L5555hls2LAB27Ztwz/9\n0z/hjjvuwPHHH4+bbroJTU1NGBwcrAHnpUuXGoB/PTY4OLifttVeqgKzu6sTQOiZqmesASxy1Lp0\nBWa38bIVBBpU4vl4LMdxkE6nTf0MoDoYFQx4LuVNeW0+n88E9zhoOVDpNWvQiiCqNStUl62SNi0k\n5TgOEokE/H4/1qxZg0KhUJXdNfoMiKVSKVNNj8HUVCqFdCaDyVQcmCljIhXHjhd2INZU3bAgGo2a\nACmf9StjQ6i4HfzqV78CMKtjHx0dRblcNrrw5sYI8rsm4QWQy03VpP4z64//a/IInyn7hPLEBHGl\nutjWTGBhxUE+N67QbJ5cnQOdJNRs4LZXdsp1299RD1ufJWkXl8tlVgD8HAOpix72wrTXBNiZTAbv\neMc7cMsttyAUCuHSSy/Fpz71KQDANddcgw9/+MO47bbb6n53ro517bXXmr83btyIjRs31v0cO656\nv+rtALX74RHgSFvQOyYXSJBWLS9fs70gPYdSJHZd50QigcnJSSOpCwaDRsPMiUNrmdg0idfrRWdn\np6mbwXP5/X7j0XNpr/VKgCoIUQ2Sy+VMnY98Pm/+r1QqGB4eRkNDAyKRiPHIGVAEYHhj1gOJRCKG\nIprMJNHyn5ei4fjlKD43iPEzvwxX0mV49EAgYPazHI1PwrvxELTdfgEAIPHe76D4k5fgdruRy+UM\nbbRixQqzEUGlUql5PgRfTkqcwLRQlk6sGnTkM1HqSsGWkkmv14tQKFRT/4Pn0u/rRK+8OID9HIK5\n+ry9SrC/w3bWYlbqxdMh4STGwHc9e+yxx/DYY4/VfW/R/vDtVQG7WCzi7W9/Oy644AJs3rwZANDe\n3m7ev/jii6s7hADo7u5GX1+fea+/vx/d3d11j6uAfSCzvRMNuBBoNcuQWmgCEAepyvg4QOjx2lpa\n/qjyQ4HAHsRerxcjIyPo6OhAIBAAAFNOldy6er28Zg5KenJNTU0IBAImkKlbT+ngZhYfU81ZxU+p\nIOrPGWDjtaZSKQQCAaTT6aqX+/sNGEijcMPbxsZGA+bu1hAajq8mLXmPWALP8mYU+lKmHbmtWCqV\nQqXBhcbzjoXjrk46jecdi+Kju0xAtbm5GcuWLYPf78dLL71knms9xYdOyHzeSo/p89Bnwu/a9JSt\nGmIhJ9IjfMaUgCqvbQe3baqN/8+l7VYjjaXHYVtyNal9mquIfD5vuGzVdqvZzs91111X93OL9odp\nB4wGVioVvPvd78a6detw+eWXm9eHhobM3/fccw+OPPJIAMCmTZvwne98B9PT09izZw927dqF9evX\nv+6LU6+aARct78nBocteYP9U5XocNgBDI9hJFfTClFbRSQCAAUpKtFKplKEE3O7q7iNUAii3rstg\nDlLeD4OK7e3t6OrqMsEm0jjkiLVKIAHB7a5u6hoMBhEOh01gjaAzPT1tNh3o7+838sCZmRlMTk6i\nXC4bj5yVEF2u6obFpfEMii8MV9uhdxwzfZOoVCpmJ3AmggSDQbhmgPw9v0Pl98BY+I/fwZmpAuq6\ndetw+OGHm0lcwVPN9lZtrlhpCZuCsI9jA7ftSTMhS/uEBp+VcrFrhHDC52v16BH7fvS6bKOMj8+L\n1AiPTaeDq6lFW3h2QA9727ZtuOuuu3DUUUehp6cHAPD5z38e//Zv/4bf/OY3cBwHBx10EL761a8C\nANatW4dzzjkH69atg8fjwZe//OX/EddmezD0evkeB7xmD+ogVQqi3jHteg/knWl2TRB6kwwu0kvn\nxDI2Nobly5ebxBVuYOD3+42XbKsXWIKUnjoAU0Spu7sbqVQKyWSyJoGGigf19vg626S9vd141jw+\nAYEg7fP5kM1mTVlPeuycpFpbqzu9zJRKmDj9i3CvaEFp3wT8Li/CgaCZrFg+NRqNItTgQ/KhFzF6\nxA2AywFSBSxv64LX6zU74czMzOCZZ57ZD3TsvmLrqznhEWwJrATUesdg22jRLQ0qp9PpmtrTlUp1\n/0duKKHHYdvYE4ACs02P2KaThnrwGqjkioz9jwoSrUY4l4e9aH/c5lQO1Lv+r076Kp2adtBBB+23\nnLUBVZfD/D09PY1kMmnqatiRdh3cHPg8viowOEhVd83/CQDkHukBrV27FkuWLDHJNawhEg6Ha7TC\nSq0AtUWFeF08D2tbp1Ip47GXy2XDvRK46nGi5NszmYypq0KqQxOEuNTO5/M1tUx4Lel0uqrh/n1g\nl+/xe0opURoYCATQ3NyMlpYWuN1uHHXUUXC5XMhms7j33nsxPDxsnoOCo/LTdsxC+XsFY3uVpO8B\nqCllQB6d7cfKeaSquIpraGgwwM3j6cbQmlH5Wvo1J03GJJSz10mElAi5aqpb6BywD2zfvv1Vx9Br\nHWuL9odh8zrT0V766v8azbcruXFga50O/R6NOmo9F8GDNIYOKj0GB53H40EoFEI6nQYAs1M5l8yh\nUMhUr6NXrFQKs/EYXNJrobyPqeCNjY3IZDLI5XKmFCevhck01HJ7vV7DY09PT9dsjsAEEm6SQD47\nGo0ajzwQCNQoNZgCzwQeAOZ9AgzvubGxEYceeih8Ph9isRh8Pl8N7TA5OYlMJrPf87aBWakA7RM2\nKNd7xnxNPVg+W7/fb8ryxuNxM8GpB2179zqB2VSLXrt60HafrHeN+jonUDoD7J/2pDUzM1MjRVy0\nhWPzGrC5RKTciyVWOai0ip160PQkORA1om57oRrwUSUBz1uPT9XP8nXyzJlMBv39/QgEAuY6wuEw\ncrmc2ZyXnq9y5goy9FZ12e/xeBCJREzpUOqmWdiINAzlhTyW1qRmUadKpWISb3K5nNlqjfQN6SEG\n8ZiYQ++axyLP7fV6EQwG4TjVhJ5oNGp2beFuMFzO53I5DA0N1WzkwAlSM1P1t9Jg+h5BFJilEfhM\nNFDMVQOv2ePxIB6Pmy3YlNPmpgHsPyop1cmbf5NXtvl4W7utqyANWLMv6oRNsOaKr1KpatNjsZg5\nrkoOF23h2LwGbHqkunxUmR89W8q9NH2Z3PBcy0F7wNuSPjtIpd4Qv6PRem735Pf7MTQ0hLa2NrS3\ntxuPk0FF0iIcsPW0vXOtCqjXDQQCpl52oVBAIpEw3p5uSqtAwXNRUaIFlOhxao0NTlbZbNYUUOK1\nMljJNOpwOGyAkEBdLpcNd099OqWGo6Oj+7VxPbC2gZuv6eSmbaeUEttRd4Gh/jqTyWB8fLxm302d\n6O2+oBQI+4FNp9FUqVPv+/p8bS9c+5h+R50TtueBUusX7Y/X5jVgO061GH0+nzfLb6UwxsbGaiRy\n+j0u4e3BYQexbP5RwU0/Yw8opUTo3VHV4TgOdu/ejebmZkNLcJKhcoOTEVArV9Pj2+8RYHktrG/N\nOtLpdNqAEBUh1GVz0BOouSJobm42mw0wXVu961AoZICQXiY9WQIgqRkAZtJsbGw0z4WeouM4GBsb\nMzvW8L7owfI51HtWdvvwXAqCpINcrtnkmcbGRgN0DQ0NyGQypp466R7KEm1uXE3Bmp+xKRxVkeh1\nqlS03vva//RetO3o7WuVx0VbeDavAZsRe2qZyQNrMgo9DVUBkFclRUAqAtg/EUYBUOkQe0lL09eU\nP69UKgawy+VqaveePXtw2GGHmYCRblhLb1g9NHugqmxRA2701vXeY7EYgsGgoUtIbRC4eV28BuXQ\nNVOU0kAFULYfQZufUypK26SxsdFct9Y5YU0Ytju9dj4vNRvQ6k28BHulG9g3+Dy9Xq9JAqJ3z3aj\npJL3oklU9jXoSsv2qnUFZoN9PbpE71+/b98n208Bm5Sg3T6LtjBs3gM26Q56qfT+OGC1vga3kiJP\nyDRuHYjKE9cLLOkAqTcoNPipdUI4YRC0K5Vq/ejm5mZ0dXUZEKNXSE/bTjO2l/o8H70r3htpCU23\np0dLnpxeJK+HIK8BON4HOXcGuZQDBmBWCrxXVU4QXDgpafYiJzVu6qt1pRV06wXh5mp/+zNKU7A9\nCJKRSMTw2NSb63E8Ho9ZgaiHbXvB9kStn5kLvOfygm1HoB7Y2wAOzKqiuEpatIVn8xqwVaqmniCA\nms0BNBmFn2XSB1ANvFH5oIVzVBFAUy8XqK1TojpenpceNtOKCZqUX+3evRuBQMDwuwAMV8raIfRc\nlYtX+mdmZsYkvjDQp94XAUrLi9JrdBzH6LG5PyA9RM0g5PXyntku9FJ1qzVdkpMDp5yS2mrea6lU\nMju8M9Bo0xo2J12P4+X//FFNut4vJW8ATKnaeDxutktTSo3qFrsPsG3t66xHedRLqrGt3v0oN23T\nXfW+Qw+bwV877rFoC8PmNWCrB2N7czYXrd/RQkHklrmRLF+jB8hzcDBz4KhWWr1NPS6Bixyp8qc8\nRiqVws6dO3HEEUegubnZXC9/SBEAs4OfyS08H4GoUqlmF2otbS0YZJvX60VjY6PZjICgzPojNJ/P\nV7NsJ+3B6yFYAzAabd06i3QVwYSlYelZ8xoVnOvRDraXPdcqR/sBJ9N6AWly1uPj4wbIdcLlBEuz\nvWZb9z9XMFivsx79UY8q4aRT7z01O9We5XMXOeyFafMasO3BS1O6QKVS9IwIYOoNhsNhk0DC5T+N\nAFkvsKXLVQVsBRwO0kqlYnhz1REnEgns3r0bQLXgkoIgj8OBSbWEvTUYlSYq52LCDicfAPtNOgRR\nnndmZsbw+vTaWTyKy21eu3rppEGoIZ+enjYTIAPCjY2NZsIhUJP/1kCnrorYhq/2/OuZ9gNOmlSt\n8DmQs+YKhOfU1ZDNIWucQ1cj2hfrcdL1QFT7k55D+9WrgTYwq0wqFotGdbNoC8/mPWBrwE2TIFjI\nXfk8eoHs3Py/WCyaDWPp9an3qktipp1XKpWa7Zp4fh5bB7D+n0wmDXjS256ZmcHQ0BAqlWo9DVbh\n8/v9RjLHJS/PQcDh9ZJ20PR4leaxip8G4vQ1zcgj8PJc9I7JcXNSymazxpsmYDNphx4/E1HYtnyP\nnnwsFoPb7Tbp9VxRsF0UMG1wO9Cy3w6WqocbDoeRzWbNtfJYKqvUCbveKo7H0tXLgUC1XuxBuWp7\nQtBz8R7qHV8dD8YhVGe/aAvL5jVg0+p5JAQ1gp3tqfJvDcZx810ANct6erx8nwCotRt04rD5RmC2\nCp+WTnWcqqyMlMHw8DAaGxtxyCGHmKxBep+alMJ61z6fzwROK5WKkd1Rh6uqEbaNrjToUWq6PVcc\nBDL+uFwus/JQXpz3RmUL74/UCI+vgU169bFYDH6/H4lEAoVCoYb75uSjKxH+1Es6odWbwPkdThCV\nSrUY1+TkZE1/oP6cYD0XUGu7sG3s61HPW0skKLev12uDtr7Oicf+nJ6LwM57X6REFqbNe8Bm57U7\nNF8n6HJJT9BSD1g9GDtYR4DWgJotDVNVgA3UOlHowNJB7fP54Pf7kc/nMTg4iGAwiCVLliAUCtVM\nEvSOmS5O02QYes5A7YpCAVnbjTQI24Dn0/0ISb1Q+sdjauo+JwaCMc/B9tb6GA0NDWhqakJjYyNy\nuZyZIPgMuDrgpGODoc1l8/xaC9tOeOKzZB2TVCpVlze2NypQQORneG86cfA+tV3Z7vysns/mw7W9\n9F7refX8XycbBWy29aItPJvXgK3ehD2wVEGh1AMHku2FsLNz4LMWB6V1ABCJRJDP581Arcdd6pIX\nmAUyfpavMUmGfGNLS4u5jhdeeAHZbBZr1qwxNTvUawWqew3S22W1PXrgvD5OOlosSDXqpCm01gqp\nJGBWHcIf3fmEyTeaos1gLjBL97jdbkPdUMMdjUZNJUBy5spfM9PTllXqM9akGJVacmNh/RyBkRJJ\n1ZjzWgm4Gntg/5qr7+kP+5P9ulIhOlnaEw6PadMr9QLodpKOfU31ApuLtjBsXgM2B612UvV0+Z5y\noTZ/y+/ZSR4EIU27JmDZnLh6z6rfVtrAluXxc/QsE4kEYrEYEokEgOr2Z6FQCCtWrKipjqfXRxAC\nZre34q4zwGyNFd6vAhQ/owNbwZ76dL6mXrqClNIOzJxke/K7bnd1c4JwOIy2tja43W5T8IorA7YZ\nwbqezQVCfC7arnpMTnbcA5PUET+vfUZ5chsQ5zKdsOtRErwGe7XF93RiAWaVJLwe/V9XGPZqQz35\nRcBemDavAftAyz6qQTR6bi9zba5ZAZ2DnEE2eozAbKlTm7dW0Ab2z1ZTSoUenS778/k82traTOnX\ngYEBBINBNDc3G+pEB3Y+nzc8NrnwfD5v7ls9TZdrdmca5YpVIqhLanvAK/3De1CQ0yU+PXYGG2Ox\nGMLhsNnBhRmN5O41G5TBVJqCIdtUvWOdQDQISO6Xr1O9otes/ceWar4aWCtIavvM5eG+VvDXY9fj\nq9X4DHQyUCdk0RaezXvAVgDWjmoPWuWrgf29IqVOgGq9DIIfta0KyArQPIfy3kAtuCi48z2lYEh7\nFItFLFu2zGxI++KLL2L16tXo6OgAMBsY03rbjuOYWhgM+tGDprJDvf1AIGC4ad2UWGkJarJtAFKK\nQT1GqitIzfj9fkQiEVM+lRMDd+VR4Kc6g4kzfM/OLNS/FaTtpBYbwKn64NZmunkxz6fPXkFd+4q+\npqnyPIZqtpVT1wlGr1OPreBr8+E02+HgNdnv6/EXbWHZvAdsBU7t0CpzImdrD0RgNuDIlGkOeLfb\njUKhgFAoVKOm0MFbT6LF6yJg1OM46e3r5wiwpVK1BGssFkMqlYLjOGZrMe6VSaBjBiQwy9Xz2slv\na83rYrFoCmU1NDSYlGsWYtIND1RTzmtWz1y5Vcr6SGmw6JMmrPB5UJ/NOIEmhxCElDJQsz3Oeu/T\nNFDMCYM8POkwXWlpOVteA49pB2x1ouB7djq4Tkp6b+pc2NRGPZWHTW8oQNsTmvb7/45Hv2h/PDbv\nAdte/jE5gkBgS6roCSnY2Lys8tC6/ZJ6Y3YwiuDEH1vHDdQGIjkBqPqE+x6Oj4/joIMOqslAHBwc\nhNfrRXt7+34bMlAJA8zy00oJkQ4JhUJoa2szQKl8N7XbvE/eo04CPL5Ofkop0eMnMCu1ohpsTfoh\nWKoXSoC3JX0Kstqe9Ehp9J75PQZI+VtjDgBqPquUSD3vnW3A8/DzjHfQeO/Kx9ugra/P9b+9arSv\nyQZmnlO9/UVbODavAVs5aHo0BCEthASgxmMBZreNAma9KQKQboCr+zOqp6VgwuOoHJCmckMG1NQL\n4rE4SElD7Ny5EwcffDACgYDxSJPJJMLhMMLhcE2SkO3t89qVU3Ucx6wYmFih185rpaeuxyLoMfvP\npk5UTWJ71GxXZk7SU9fPuN2zFftIT9nApCsj24PUe+D/7AORSMRsyhCNRpFOp2tUJTy27lqj1MJc\n/U4Bld/RZ8rj2wFUm1Lj8+O987t6Lv2tqxydNPW6mNW5aAvP5jVg65KSS2DboyYwK/fIYJcmlXDQ\nkj5QHtEeXDY9ohODza1SAsfvqVeqA1ezFAnu/f39OPTQQw0AZTIZDA0NoVwuIxgMmutgWVldUZC/\nVT6dXi4LY/G6WPAJmE19V06b18g0dTVtG5UIqkKH7W1z6SpzJH/N79ajAWwKQekR/bzywtyrMhAI\nIJ/Pm/tXgLXVQXo8O3lH+4C+BszuBMOVhh0v4fE1q5TtZrfpXL91ktH39Lv1gsaLtjBsXgO2gqfK\nwgi4zFpTAGcdD+6ETVMwpTqEgJ3L5WoCejY4qCdlUxx8TYswcRL4eZxhAAAe8UlEQVThdTLApzW7\nCd4vvvgiVq1aZThpJnx0dnaaOs70yimlU7UDaRd6zsyeZFsoLcBrVm9TPXECDTlgYBaYyQ+rZ0z6\ngabeIZ8HVzG8Bhae4oRTL/CnVRH5zNheunJiMJcrA8oOeY2kjrRyoE6sNmhrn9Pr0pWWqnPU4+Zn\nbW6a56LpSk4/oxw3v68ySptasifWRVsYdkDALhQKOPnkk40S4c///M9xww03YHJyEueeey727duH\nlStX4rvf/S6ampoAADfccAO+8Y1vwO1249Zbb8UZZ5zxui9Og4j0ADlwdDcTx3HMJrQMiAG1AMLj\nEfgUTO2Ivb1cJhiSNyYYMImDZVKBWuWIZlzyHAQkAGZndW4pBsDU3SBQsTQrOWPlmgGYsrH0wFW9\noFI33pOtLtDEGAId62nX45yB2t3qK5XZmisKYHyPO6zXC/LZHjA9dpfLZYCXr3Gy5qTBjYTZ3ul0\nGn6/H11dXUilUkbvrtmdNF392EofnRB4jfTY2Wf0GgGYErkM9Pr9fgSDQYTDYQQCAUQiEbO1l25i\nwbZjrZvBwUG8/PLLmJyc3G8y4A5F2r6LtvDsgIDt9/vx6KOPIhAIYGZmBieddBKeeOIJ3H///Tj9\n9NPx0Y9+FDfeeCO2bt2KrVu3YseOHbj77ruxY8cODAwM4LTTTsPOnTv3C+D9d0ypB62PQSAvFArI\n5/OoVCqmQJJG93kMBQPd2ICDFZhVlNDU67OX5bwnKig0GKkgpNfBc5EnzuVyCIfDiMfjBpDC4TB8\nPh8ymQzGxsbQ0tKCSCRigFXTzAkCBFytI2JTMUrrqN6akxbBSrlZera2/liDr8pT00vkBEOpJMGf\noKkBSfVCeTx6+1x18Nj0MmdmZpDNZo3nTNBlRihrhsfjcVPAihMsP6tJRxqHAKrguGzZMrS3t6Oj\nowPt7e1YsmQJWlpa0NLSgra2thqlDJ+FTuh2MPVAxjbN5/OYmJjAD37wA9x55514+eWXa2gkPaY9\n8S7awrBXpUQCgQAAGH4yFovh/vvvx89+9jMAwJYtW7Bx40Zs3boV9913H84//3x4vV6sXLkSq1at\nwlNPPYUNGza8rovTQe5yucymsxyA3D4sFArVAIpda4EApkDm8/nMANeAmh384m9dFhNcdYlOD18n\nEx2sNkfOAUjPcGxsDF1dXejr60NnZycCgQDi8bjhfqPRaE3wzg7aEdiUoiAlwKU0dwTXeyEI8hrZ\nhqQvtGyrSv40KGqflyCvShwApn63etj28+b16eTB+AM9atZWIf1FkOTEnslk4HK5EIlEDLfOCYHg\nynuLxWJob2/H0UcfjRNPPBE9PT1YsmQJgsFgTcDvQEFK2lyfUYrlQO+zRO2WLVvwlre8BVdddRUe\nf/xx00e1kuSih70w7VUBu1wu49hjj8Xu3btx6aWX4vDDD8fIyIhJ9Ojo6MDIyAiAarq1gvPSpUuN\nxvj1GAFbS0q6XC6jX45EIuZzWvDf9piA2eUtwYJ0BEFoenra8OH8PI+tg1ZBmEDFAKd6qwQepRHo\nsapHye8HAgGMjo4iGo0ik8nAcRwzqQwMDKBcLqO5udl4naxlTcDyeDxmpaFV6XhNyqPzNeVElQ4h\nZ25PZtqO2h68Vy0URYAhXQLMFuqyFSZagoDgbO9/CcDcj+NUk3dIJ1CWyevmxFCpVNDa2opEIoF8\nPg/HcdDZ2YmzzjoLp5xyClavXo2uri40NTXtV7pAJ1qlb16P1fuezZPbq43Ozk5s2rQJjz/+eI0T\nwD656GEvTHtVwHa5XPjNb36DZDKJM888E48++mjN+zYw2jbXe9dee635e+PGjdi4ceN+n2G1t0gk\nYjLmpqamanbp1kFmKzZo9bwR8sPpdLpm9xTV4uog4XGUAuBrCjgcfAwYERgJ0ABqQJ2DNJfLobGx\nEalUCqFQCMlkEh5PdXPdfD6PoaEhFAoFRCIRk8LOABhBkMfTwBi111qdj0BMmkmDXbYGXL05nWyU\nSqoH4jwnvWstFEWP1342bO9oNIpisWiUMmxPAjJ5aR6P6hBO2gR9XuvGjRuxfv16bNiwAT09PWa1\nUq8P2WYHRQ9kCu76fX1d20m5fjod5Ojz+bwJIGsq/1yrE9pjjz2Gxx577FWvddH+MO01q0Si0Sje\n+ta3Yvv27ejo6MDw8DA6OzsxNDRkMvS6u7vR19dnvtPf34/u7u66x1PAnsuo5uBv7nBNzS+pCBu0\nldJQEKXxbxZ+4jEILqywZw8yAIaD5mtaJZCgzPMSQHQiAWAyFG1PVjnttrY2VCoVjI+Po729HVNT\nUxgZGcHU1BSi0SjC4XBNhqauKsjRKhjwfmhazY8gx3tTrlpXA8rVq+JC6SZgNtBHENJJi6sAfRY6\ngXHfyYmJCVMgq6mpCcuXL0cikcDQ0FDNKoHAqxUP+Rw3b96Myy67DEuXLq0pq8p7+t8wGzgVkLXv\n2H9rpqQGcWm6+QRXK/ZEX89s5+e66677X7nPRZsfdsBeOz4+bqLt+XweDz30EHp6erBp0ybcfvvt\nAIDbb78dmzdvBgBs2rQJ3/nOdzA9PY09e/Zg165dWL9+/eu+uHK5uknB8PAwAJgAFgGJXqwGYeyO\nbwOWes6kANRD1traNrVie5r16BcNOqkHrZ4mZXcqTyOPzN1wUqmUmUi4s065XMbY2BgmJiaQy+WM\n52W3AduOXq6qLOhxk4rg/1Q4aJYolRA2F09g1RUIaRn+toNjnEBIH7G9lTri66VSCStXrjQ00b59\n+9Db24twOAyPx4NcLmfak+2nAcVAIIDPfOYz2Lp1Kw455BCTvq/PRe318MH26uNA76v3zM2IufpQ\niogATi05683wOZJaWqREFq4d0MMeGhrCli1bTAe58MILceqpp6KnpwfnnHMObrvtNqz8vawPANat\nW4dzzjkH69atg8fjwZe//OXXzfsB1U4fj8cRDAZRKBTMoNSOy88pONLs5Wy9a/F4PAgGg0ilUmYS\noL6agSAOdh5b63qoCsTW9vLa7GCeflc3JyBYUZ5YLBaRSqWQyWQMf93Q0IBUKmV2VwkEAqauN69D\nvWelY7jcpidKr1m9Tt6zeoNUffAeeR5SPurxaRswRkA1SyKRqNkM184SrFSqapfJyUmzkvD5fBge\nHsbk5CQaGxtNYSt7ZQXMctwnnXQSjj/++JpsQNVX1wPZ/y5HbfPaPKbSHPrsta9qLITtqqobBk7H\nx8fNxKSTn03VLdrCsQMC9pFHHolf//rX+73e3NyMhx9+uO53rr76alx99dX/KxdXLBbR3NxsAo/Z\nbNaoFpSCUODkgKi35LUHrHp4pEeoYyYVo7I2gqAG2HgN9aRcuqGCctvAbE0UelC5XM4AH5f4wWAQ\n5XIZmUwGABCLxTA+Pm42Q+AmDKxFTW7f5pZtuSKBwXGcmjRntpkG+3g8ldYBszw8JzmlTth+qr3m\nM+TrNtDZAWINLK9ZswaDg4Po6+tDS0sLYrEYHMcxahACI4PTK1asMEWouHmx3vtccZd6AGy/X4/O\nUVDWictemej5VT5ZD+RzuRyGh4drVl+vRocs2h+/zetMR3LWunGrcn4AaoJH9Ab5twbIbEAAaotL\nMbWZfKsqJ3T5aXvT6jHZEwb5YF4PjeBCNQc5StUFE9iDwSAaGhqQTqdRKpUMvxsMBtHR0YFkMol8\nPo9sNoumpiYzwbFdtH00icdePWjAkm3NdtZKd0rvaPCPy3ZgdtNjno9JPYlEoiaLktfE8+tEx3bg\naiISiSCXy5nza3YnKZpCoWC81mw2i5GREQSDQQQCgRqNtD5H9gN9vso/K0fPCZwJXDbA8/pt75p/\n68pQ39O24O98Po90Ol0D6npse3WyaAvD5jVg0yNl4EqDX/oZBV5b1VEvGFgvUOQ4DgKBQE2ZUYIm\nBzE94gPxljRbgVAvAKXqDk4SynWTr2dBJ5/PhxUrVmBoaAjxeBzFYhFLliwxnC7BMxwOw+VyGe9S\nZYj8XwNw+qOvA3PXdeZ79NyVf2bAkWDNiSuZTNYAYD1Fhbax1utwuVzmvvL5vCn4RNOiU3v37sXw\n8LDJIVDJoE6u9Sgz+3VdMakDoM/Sfv52/1CAPlC8Rfsin6e2td1/Fm3h2bwGbEq2bC0zMOtNq/eh\nvLFyhApYyjkr2HMwU1rHgaVenA78evyrbbbnzetS+aAqMeiVq2KDVfyWLl2K1tZW7Ny5E+VyGX6/\n39QdWbZsmQloUf7X1tZmKBL19BUotS1VsqdeKP9mW9D7tZf//M36IgpwDQ0NyGazyGaz+00Q6qmS\natLEG05s2WwWuVzO9AP9DHlgr9eLfD6P/v5+9Pb2oqWlpWYFoaCtPPBcQK6rM92CTSse6vPXCUj/\nt++3Hm2ljoWdNar1a9RjX7SFZ/MasIHZWsa29ImvAbPlN9UTsr0zmgKofodeu9frNRvjEjzo6di1\npJWa4bHUbA9OQROoDUjSc1XA5KRULpfR19eHiYkJ+P1+A4Ctra2YnJxEb28vOjs70dTUhFwuh0wm\nY+5H61jY3jZQWx5WAYbn52/dm9GWTvI49Ao1KMtNGHK5nEkTZ1vYNTtsuktBX7MV+ZxcLpdR1fC6\nQ6EQMpkMnn32WXR2dpqJlmULdOMFBU8FbV6TrS5SZUo9SkIDrvp8bbC2J0v9PH/r5hWc9NhuiyqR\nhWvzGrDpQWt6NLC/56cDm4CiKdm2h8tjKE8LzMr1tGARgUQr89me2FygrYBge2AKPsod6/1ogJVB\nNhaaCofDyOVyJlg6NjZm+OFYLIZMJlMjGyMXrpsY8NhsK16LenPk0xV49NlQdkhOmdetE+HU1BTS\n6bRpQ5v7tRU3Nl2jbaJcu3q/nNhCoRBGRkbgOA7Wrl2LWCxmvmMrY/RZ8hw0DQDrtemz1TZUgNd+\nYDsIB3qNxgmmsbFxvzbnOFj0sBemzWvArlQqCAaDyOVyBrwU3DjoCBLcN9AONNrLTnZ2Bq/orStQ\nRCIRIx/j+Zi8Qw+Nx7ZVGPY96DXXG6RasEppGn6GwKerBnLYsVgMlUoFyWQSqVQKzc3N8Pl86Orq\nQqlUQjKZxPT0NKLRKEKhkMnyY8CT7cIEIHsDAm0/Xr+2kwZpgdnVjGqxZ2ZmEI/Ha7xaPZ7SADyf\nDWhKgTDw5/F44Pf7zXNasmQJCoWC2bF99+7dWLlyZU1dkHo0jp6vHvjqfdvtoWYDun7Ppkrq3aee\nPxQKoaOjo6beizodc/W3RfvjtnkN2FxmA7O7otvvc7nI2sj8n6Cj3pEuxwkyykfqAHK73Ub/TUqA\nwKLZgfWWtHP9z2u2uVO7DgkHuS67eV+6LCcv7PV60djYaKrjDQwMYHBwELFYDN3d3fD5fBgfH8fE\nxAQ6OzvR2tpqKAJOCEo5qRyPxrbReIKdNKQTEP/msVKp1H6TkB77QKZet4I264i43W50dHTAcRyM\njIyYNPxdu3bhuOOOQ0tLi1mJ2CoO29uv97d9LfbvA72mIMz/aXP1F8YyWLIYmM2oBfbfAGLRFo7N\na8AGYEAYmOXvKK8igHGpzU7NAa3L6nrKCDVWg+Pg4jI7Eokgm80aj5OF43WDBPXodZlc7zewvyaX\nZnuumgxE5YVy+lzGs3IdUK2uyPTuRCKB0dFRtLe34+CDDzbAPTU1hc7OTnPNTEaxeValfvi/xgWU\nitL7YkINg33pdBrZbLaG8mCb2EHgesZr01KxGjRkoav+/n6zapqensb4+LjRsOuEo/dlt79+Vv+e\n67V6n6cdCPDt/sL3+L/b7Ybf76+JG2h6+qKsb2HavAds0g+sJwKgRqnAkqOO49RsJKBJBtQJs7Nz\ngNFbJnAoj8vflIZxUwHy2Y7j1GzKqt/jwLN50XoeFb13G0hUAsbBrbQQvVh6maRMstms0WV3dXXB\ncRzs3bsXe/fuxXHHHWeq11UqFUOfUGOskr+5wJOgqYEwx3GQy+Vqgnd8Bo7jmDT7em3wWo20EdtM\nN6Ftbm7G0NCQCUxyowG2A69Ddee2WkRXB8D+iS/23zYY1/v/1SYi+3vafzweD5qamsz9aJGuxeSZ\nhWvzGrArlVkdtnKKWlSJnZuA63a79wuCEVh0CWyrDVQaqOdiELJUKpkNXrWMqKZ2Kw2gwTEdlFrS\nVJfl/ByBSYs32SVJ9V44kJkYwmMVi0UMDAyY1PWZmRls374dxxxzjJn8mE0JzKpJgFmPVlUxbGue\nU8GTz4RtYmvL6dXXk8Ipb6/ft9uN7c5rJnfe3t6OTCaDTCazXzXBbDZr0uOVTuHfdiLNq/3MZXN5\n1fYEfiCzKRi3241oNFrjqGicZdEWps17wFZvit6onYnI/3XJrpps1XLrMtr2ZpU35v/0fkOhENxu\nt9m+iYEuJrTYumpd8tqD2KZN7O/ZmmHenw3YOrEoBaHLak5eBNDe3l40NTVh5cqVpkLg+Pi4ySqt\nl9BixwDsoC4zRDnh8PsejwfZbBbj4+M13H29ttDJS//XZ62V+YLBIKLRKKanpxGPx2s0+nbGoNIH\nc4GrDcqvBtL/XXstoK3X5HK50NLSYkoAA7VttBh0XJj2v1Nj8v/IuDGuze0pwCo4amdX/leX+F6v\n15RP1V3AgdoNUoHaQKfLVd3BJBQKmc/T49PCSMpD0xSg7YQT9fLITVLLrLuzqLKD37Ff4z2Q2mEq\nO8/LPQWfe+45/OpXvzIrlUwms9/O3lx5cPXBc/EY5NkZ4OPEQlCltC+ZTCIej+93fLtt6rUPn7HW\nFW9sbARQLY3r8XgwOTmJbDZb43lyEnecqhSSFMlcNhcf/X9pc51D6bpYLIZQKFSz0rTzERZtYdm8\n9rBVlaGDsZ4HSNBQL5nct6oxCDJ2xhhBjoCjwUsCVLFYRGtrKwAgnU4bqiCXyyEUCtVsnmADNgei\nzZPTbPWCJp/YEjQb5PQ8XBUAMFXfuDUYj82A409/+lOsWLECRx55JCYmJlAqldDU1IRgMGjOWy6X\nzQqC96HPgwE+thVBnkv54eHhmqJd9UwDl8Csh2xPupwYW1tbEYlEMDw8bHbn4QRCgGd75fN5M6nU\na7P/LdMVh72Ceq3etX7X5XKZ6oTse3RW2MaLtvBsXgM2O6VdmAioXU7bGYSqUlBuGkBNkO7/t3cu\nMU01URz/F+0XMIBRlIpg0lgoz9I2QXGhASO4MaIGF2gkJMLGndEY4w4XPjC6QOPKaMJOV4oLIBgj\nQlyID4xREiURDG8CyrPV8phv8eWM00tL+aS3UDi/5CbQxz0z9/b+Z+bMnDNqQAj1XNRJHXWiSh2q\nx8TEAICc0BJCyL0mya2gDZMHvCMx1cAUtYes+rTJptoAaScx1dUwdM1U/z2NAMhX7XK5ZE953bp1\n+PLlC1wuF+x2u7xOHo8HsbGxXqlgtfbUyTra0Jg+R2lOadMFdeNgLb78vPS3OrqgRoHcU2NjYxgd\nHZ03uac2cHNzczJ5VKDoQK3g6iHqixFu1UUXHR2NLVu2zHODaJ8FZu2wogUb8O6lkIuCfJvaYIqZ\nmRlERkbK/Q1pWEw9QlXE5+bmvIQd+DOZqS5XU4fpJK5GoxFxcXEwGAxyI18KOqEePQkb2aKetbpb\niupDJ6EFIP30al4NrU9cK350ndTGSxX+qakpjI+P459//sGGDRtk3g1advf69WsYjUY4HA4kJSUB\ngNwwgNarq6MDNXMijWTUCUjq3Q8NDc1zWdE51LJTWek6qH5o1Q1AZRoYGPCax1AbV3VOY3x83Gul\niNZPrr2GWrHWCrcvl4l6Pnrfl0tsIbQNFvDfFnnbt2+XowYacdKqHmbtsaIFWxU61Y+r9iYByN4X\nBdCowTDqA6hGG6rLpFSx0AqrmrxfG8pMuTwo78jv379lGdWGgVAFQRU8bc9OXVqmfpc+46sHqDZs\n6muqSFGdxsbGpJuCXA3UuL18+RIREREyWjIxMVEmniKhVxtLcr+oLglqLEZHRzE2NjZvZOALqhOJ\nErlUyB9O9YmNjUVfX5+cSFaDdNRGjxpR2u9RHc38DYvtdWtFN9DntH8T9DswmUwyRiAqKkrO6zBr\nkxV951XBUUWXHkbqhaoiqvqkqVcOQIo54P2AqL06daWH2kOm3o3q0qBhelxcnFcv0u12e221RcKt\nujXUCT3q+auipq70UOutugl8uUd8iTa9R+UA/uxeTgdtdkvuEwrxn5iYwKdPn2AwGJCcnIz09HRY\nrVZERUVJGzRBqg2ocbvdGBgYkHstau+j+r92Ylh1hdDIZXZ2FnFxcXC73RgeHp7XU1ZdIcCfvDAu\nl0umF/AljIGEWC/3iHp+LWRv/fr1MJlMiImJkYmz1PkNZu2xogU7PT1drm4gH7G6vEv1QVPCJ1UI\n1ElIdbWJKnyq0Ku9a1rOR4E51JtUxZZ2T0lJSYHb7Za9PnqgfK3/phUe6qYAJOja3rPq0tCuV9aK\nsz+xBrw3Jgb+JJ6ia6gKuRpc4vF4kJqairGxMbhcLnz//h1DQ0PYuXMnMjIypO+a/Pa0coPKGhkZ\niYyMDHluQq13RESE3OIM+LPKhRozdWPkzZs3Y3Bw0Ot9CopS5x3oXgnxX/Y+yiceFRUl66iuzlH9\n8f4OKncg8V7InaKi9UFre9z0XYvFgl27dsnNh+ka69mIMCsXg1js9HUwjS5i8oVhmKXDz9rqgsdV\nDMMwYQILNsMwTJiwoGD/+vULubm5cDgcyMjIwKVLlwAAlZWVSEpKgtPphNPpRH19vfzOtWvXkJKS\ngrS0NDQ2NupbeoZhmDVEQB+2y+WSyYP27t2Lmzdv4vnz54iJicG5c+e8Ptve3o6TJ0/izZs36O3t\nRUFBAb5+/TpvRpv9agwTGvhZW10EdIlQelFaEbFp0yYAvpcj1dbW4sSJEzAajTCbzUhOTkZra2uQ\ni8wwDLM2CSjYc3NzcDgcMJlM2L9/PzIzMwEAd+7cgd1uR3l5OUZHRwEAfX19MkoOAJKSktDb2/vX\nhWtqavrr7y4Ftst2V5NdZvUQULAjIiLw4cMH9PT0oLm5GU1NTThz5gw6Ozvx4cMHJCQk4Pz5836/\n72+9aGVlpTz8/ZDX2oPFdtluMGyozxazulh04MzGjRtx6NAhvH37Fvn5+fL1iooKHD58GACQmJiI\n7u5u+V5PTw8SExN9no9/TAwTfPLz872ez8uXLy9fYZigs2APe3h4WLo73G43nj17BqfTiYGBAfmZ\nx48fw2azAQCKiorw8OFDeDwedHZ2oqOjA7t379ax+AzDMGsIsQAfP34UTqdT2O12YbPZxI0bN4QQ\nQpSWlgqbzSays7PFkSNHxMDAgPzOlStXhMViEampqaKhocHnefPy8gQAPvjgQ+cjLy9voUecCTOW\nJTSdYRiG+f9wpCPDMEyYwILNMAwTJqxYwW5oaEBaWhpSUlJQVVWlqy2z2Yzs7Gw4nU45Sfrjxw8U\nFhbCarXi4MGDcvJ1KZw+fRomk0lO0gayE6wwf1929U4v0N3dLdftZ2Vl4fbt2wD0r68/u3rX118a\nh1DcX2YNsdxOdF/MzMwIi8UiOjs7hcfjEXa7XbS3t+tmz2w2i5GREa/XLly4IKqqqoQQQly/fl1c\nvHhxyXaam5vF+/fvRVZWVkA7nz9/Fna7XXg8HtHZ2SksFouYnZ0Nmt3Kykpx69ateZ8Nlt3+/n7R\n1tYmhBBiYmJCWK1W0d7ernt9/dnVu75CCDE1NSWEEGJ6elrk5uaKlpaWkNxfZu2wInvYra2tSE5O\nhtlshtFoRElJCWpra3W1KTRzr0+fPkVZWRkAoKysDE+ePFmyjX379snQ/kB2ghnm78suML/OwbS7\nbds2OBwOAEB0dDTS09PR29ure3392dW7voDvNA6huL/M2mFFCnZvby927Ngh/19qiHsgDAYDCgoK\nkJOTg3v37gEABgcHYTKZAAAmkwmDg4O62PZnJ9hh/r4IRXoBAOjq6kJbWxtyc3NDWl+yu2fPHgD6\n19dXGoflvL/M6mNFCnaotz969eoV2traUF9fj7t376KlpWVeeUJRpkB2glmGYKQXWAyTk5MoLi5G\ndXU1YmJi5p1Xr/pOTk7i+PHjqK6uRnR0dEjqq03j8OLFi3nnDdX9ZVYnK1KwtSHu3d3dXr2RYJOQ\nkAAA2Lp1K44dO4bW1laYTCYZ0dnf34/4+HhdbPuz83/C/P+G+Ph4KSAVFRVyOB5Mu9PT0yguLkZp\naSmOHj0KIDT1JbunTp2SdkNRX4LSOLx7927Z7i+zOlmRgp2Tk4OOjg50dXXB4/Hg0aNHKCoq0sWW\ny+XCxMQEAGBqagqNjY2w2WwoKipCTU0NAKCmpkY++MHGnx29w/z7+/vl33qkFxBCoLy8HBkZGTh7\n9qx8Xe/6+rOrd339pXFYrvvLrFKWdcpzAerq6oTVahUWi0VcvXpVNzvfvn0Tdrtd2O12kZmZKW2N\njIyIAwcOiJSUFFFYWCh+/vy5ZFslJSUiISFBGI1GkZSUJB48eLCgncWE+f+N3fv37y85vUAgWlpa\nhMFgEHa7XTgcDuFwOER9fb3u9fVlt66uTvf6+kvjEIr7y6wdODSdYRgmTFiRLhGGYRhmPizYDMMw\nYQILNsMwTJjAgs0wDBMmsGAzDMOECSzYDMMwYQILNsMwTJjAgs0wDBMm/Avhoj/ZusMzLAAAAABJ\nRU5ErkJggg==\n", "text": [ - "" + "" ] } ], "prompt_number": 16 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Furthermore, `FittingResults` can be used to visualize the evolution of the landmark error throughout the fitting procedure:" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%matplotlib inline\n", - "\n", - "fr.plot_error(color_list=['b'], marker_list=['*'])" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "apply_inplace can only be used on Transformable objects.", - "output_type": "pyerr", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolor_list\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'b'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmarker_list\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'*'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[1;32m/home/nontas/Documents/Research/menpo/menpo/fitmultilevel/fittingresult.pyc\u001b[0m in \u001b[0;36mplot_error\u001b[1;34m(self, figure_id, new_figure, **kwargs)\u001b[0m\n\u001b[0;32m 177\u001b[0m \u001b[0mx_label\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'Number of iterations'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 178\u001b[0m \u001b[0my_label\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_error_text\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 179\u001b[1;33m \u001b[0merrors\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 180\u001b[0m \u001b[0mx_limit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_iters\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_levels\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 181\u001b[0m \u001b[0maxis_limits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx_limit\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m/home/nontas/Documents/Research/menpo/menpo/fit/fittingresult.pyc\u001b[0m in \u001b[0;36merrors\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 109\u001b[0m return [compute_error(t, self.gt_shape.points,\n\u001b[0;32m 110\u001b[0m self.error_type)\n\u001b[1;32m--> 111\u001b[1;33m for t in self.shapes(as_points=True)]\n\u001b[0m\u001b[0;32m 112\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 113\u001b[0m raise ValueError('Ground truth has not been set, errors cannot '\n", - "\u001b[1;32m/home/nontas/Documents/Research/menpo/menpo/fitmultilevel/fittingresult.pyc\u001b[0m in \u001b[0;36mshapes\u001b[1;34m(self, as_points)\u001b[0m\n\u001b[0;32m 131\u001b[0m \u001b[0mtransform\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mScale\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdownscale\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 132\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mt\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshapes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mas_points\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mas_points\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 133\u001b[1;33m \u001b[0mtransform\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_inplace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 134\u001b[0m \u001b[0mshapes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_affine_correction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m/home/nontas/Documents/Research/menpo/menpo/transform/base/__init__.pyc\u001b[0m in \u001b[0;36mapply_inplace\u001b[1;34m(self, x, **kwargs)\u001b[0m\n\u001b[0;32m 124\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_transform_inplace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtransform\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 125\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 126\u001b[1;33m raise ValueError('apply_inplace can only be used on Transformable'\n\u001b[0m\u001b[0;32m 127\u001b[0m ' objects.')\n\u001b[0;32m 128\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mValueError\u001b[0m: apply_inplace can only be used on Transformable objects." - ] - } - ], - "prompt_number": 17 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally, note that we can visually inspect the final fitting results for all images by using the previously defined function `browse_images`:" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%matplotlib inline\n", - "\n", - "fitted_images = [fr.final_fitting for fr in fitting_results]\n", - "browse_images(fitted_images, group='fitted')" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'AAMMultilevelFittingResult' object has no attribute 'final_fitting'", - "output_type": "pyerr", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mfitted_images\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinal_fitting\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mfr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfitting_results\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[0mbrowse_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfitted_images\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'fitted'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'AAMMultilevelFittingResult' object has no attribute 'final_fitting'" - ] - } - ], - "prompt_number": 18 } ], "metadata": {} From 03269860fe683a71b4f18929a16a6b83b1f33290 Mon Sep 17 00:00:00 2001 From: Epameinondas Antonakos Date: Wed, 28 May 2014 17:23:04 +0100 Subject: [PATCH 3/3] removes pca notebook cause it doesn't work --- notebooks/Models/PCAModel.ipynb | 337 -------------------------------- 1 file changed, 337 deletions(-) delete mode 100644 notebooks/Models/PCAModel.ipynb diff --git a/notebooks/Models/PCAModel.ipynb b/notebooks/Models/PCAModel.ipynb deleted file mode 100644 index 5eadd80..0000000 --- a/notebooks/Models/PCAModel.ipynb +++ /dev/null @@ -1,337 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:59bdc8b29e9c5506be2fee5281740cd79bc54064f8be6a16d77004047dddfebe" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Principal Component Analysis Models" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Import the aligned face dataset and build a list of Image objects from it" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import scipy.io as sio\n", - "import numpy as np\n", - "from menpo.image import MaskedImage\n", - "import menpo.io as pio\n", - "\n", - "im_db = sio.loadmat(pio.data_path_to('alignedbwfaces.mat'))\n", - "imagedata = im_db['images']\n", - "mask = im_db['mask']\n", - "images = []\n", - "for i in range(imagedata.shape[-1]):\n", - " images.append(MaskedImage(imagedata[...,i], mask=mask))" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`images` is a Python list of our `menpo.image.Image` class. We can grab one of them and view it" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%matplotlib inline\n", - "image = images[0]\n", - "image.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "the `view()` method is a quick and easy visualization on all our types. For images, it's roughly equivalent to this" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import matplotlib.pyplot as plt\n", - "plt.gray()\n", - "plt.imshow(image.pixels[...,0])" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "but does some legwork to give a sensible result for B+W images too. See the `menpo.images.Images.ipynb` notebook for more examples of how our `Image` class works." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Set aside the last 10 images for testing, use the rest for constructing the model" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "training_images = images[:-10]\n", - "test_images = images[-10:]\n", - "\n", - "from menpo.model import PCAModel\n", - "pca = PCAModel(training_images)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Firstly, lets take a look at the mean" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "pca.mean.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that the method above return `Image` instances! \n" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "type(pca.mean)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This makes working with our models really convienient. Of course statistical models generally only work with vectors of data, so how is this possible? It's all done through the `Vectorizable` interface (see `menpo.vectorizable.ipynb` for details). If you ever want to see the low level vectors, just call the `mean_vector` property." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "pca.mean_vector" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "What else can we see? How about the proportion of variance captured in each of component" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import matplotlib.pyplot as plt\n", - "plt.plot(pca.eigenvalues_ratio)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "or cumulative variance captured in the first 40 components" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "plt.plot(np.cumsum(pca.eigenvalues_ratio[:40]))" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Or just the components themselves" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "print 'shape of all the components: {}'.format(pca.components.shape)\n", - "print 'pca.components[:5] grabs the first 5 components: {}'.format(pca.components[:5].shape)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now lets use our model. We can project an in-sample image onto the PCA and check the reconstruction is perfect" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "insample_image = training_images[9]\n", - "weightings = pca.project(insample_image)\n", - "rebuilt_image = pca.instance(weightings)\n", - "print 'if the reconstruction is close, an image of the reconstruction is displayed'\n", - "if np.allclose(insample_image.pixels, rebuilt_image.pixels):\n", - " rebuilt_image.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "print \"Examining the numerical error\"\n", - "plt.imshow((insample_image.pixels - rebuilt_image.pixels)[...,0])" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now lets limit the number of components used in the reconstruction a little..." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "rebuilt_image_50_comps = pca.instance(weightings[:50])\n", - "rebuilt_image_50_comps.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now lets try an out of sample image" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "test_image = test_images[0]\n", - "test_image.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "weights = pca.project(test_image)\n", - "reconstructed_image = pca.instance(weights)\n", - "reconstructed_image.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This operation of projecting to learn weights followed by reconstruction of an instance is fairly common, so we have some syntactic sugar to make things a little more natural." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "reconstructed_image_alt = pca.reconstruct(test_image)\n", - "print \"Does the easier reconstruct syntax yield the same result as before?: {}\".format(\n", - "np.all(reconstructed_image_alt.pixels == reconstructed_image.pixels))" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that you can also pass in a number of Components to limit the reconstruction power" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "reconstructed_image_limited = pca.reconstruct(test_image, n_components=50)\n", - "reconstructed_image_limited.view()" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -} \ No newline at end of file