only keeping useful

siddiquesalman · Jun 5, 2023 · 1374153 · 1374153
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diff --git a/.ipynb_checkpoints/flatnet3d_test-checkpoint.ipynb b/.ipynb_checkpoints/flatnet3d_test-checkpoint.ipynb
diff --git a/flatnet3d_test.ipynb b/flatnet3d_test.ipynb
@@ -13,138 +13,54 @@
     "import torch\n",
     "import scipy.io\n",
     "import mat73\n",
-    "import random\n",
     "import torchvision\n",
-    "import time\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "import torchvision.transforms as T\n",
     "import torch.nn as nn\n",
     "import torch.fft as fft\n",
     "import torch.nn.functional as F\n",
     "import cv2 as cv\n",
-    "from PIL import Image\n",
-    "from skimage import color, data, restoration, img_as_float\n",
     "from unet import UNet\n",
     "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
-    "from pypfm import PFMLoader\n",
-    "loader = PFMLoader(color=False, compress=False)\n",
     "%matplotlib inline"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9de939d7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tested on Torch version: 1.13.1\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"tested on Torch version:\",torch.__version__)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "fad5f90b",
    "metadata": {},
    "source": [
-    "### helper functions"
+    "### load PSFs"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "04899513",
    "metadata": {},
    "outputs": [],
    "source": [
     "data_dict_psf = mat73.loadmat('data/psfs_save_magfs.mat')\n",
-    "psfs = data_dict_psf['psfs'][:,:,:,-25:][::2,::2]\n",
-    "\n",
-    "def show_figure(image1, title1, mode=\"single\", image2=None, title2=None, save=False, img_name=None, cmap='gray'):\n",
-    "    \n",
-    "    if mode=='single':\n",
-    "        fig = plt.figure()\n",
-    "        plt.axis('off')\n",
-    "        plt.imshow(image1, cmap=cmap)\n",
-    "        \n",
-    "    if mode=='single-colorbar':\n",
-    "        fig, ax = plt.subplots()\n",
-    "        divider = make_axes_locatable(ax)\n",
-    "        cax = divider.append_axes('right', size='5%', pad=0.2)\n",
-    "\n",
-    "        im1 = ax.imshow(image1, cmap=cmap)\n",
-    "        ax.set_title(title1)\n",
-    "\n",
-    "        fig.colorbar(im1, cax=cax, orientation='vertical')\n",
-    "        \n",
-    "    elif mode=='comparison':\n",
-    "        fig, (ax1, ax2) = plt.subplots(1, 2)\n",
-    "        divider = make_axes_locatable(ax1)\n",
-    "        cax = divider.append_axes('right', size='5%', pad=0.2)\n",
-    "\n",
-    "        im1 = ax1.imshow(image1, cmap=cmap)\n",
-    "        ax1.set_title(title1)\n",
-    "\n",
-    "        fig.colorbar(im1, cax=cax, orientation='vertical')\n",
-    "        \n",
-    "        divider = make_axes_locatable(ax2)\n",
-    "        cax = divider.append_axes('right', size='5%', pad=0.2)\n",
-    "\n",
-    "        im2 = ax2.imshow(image2, cmap=cmap)\n",
-    "        ax2.set_title(title2)\n",
-    "\n",
-    "        fig.colorbar(im2, cax=cax, orientation='vertical')\n",
-    "        fig.tight_layout(pad=1.0)\n",
-    "        fig.show()\n",
-    "        \n",
-    "    if save:\n",
-    "        fig.savefig(img_name)\n",
-    "\n",
-    "    \n",
-    "from struct import *\n",
-    "def load_pfm(file_path):\n",
-    "    \"\"\"\n",
-    "    load image in PFM type.\n",
-    "    Args:\n",
-    "        file_path string: file path(absolute)\n",
-    "    Returns:\n",
-    "        data (numpy.array): data of image in (Height, Width[, 3]) layout\n",
-    "        scale (float): scale of image\n",
-    "    \"\"\"\n",
-    "    with open(file_path, encoding=\"ISO-8859-1\") as fp:\n",
-    "        color = None\n",
-    "        width = None\n",
-    "        height = None\n",
-    "        scale = None\n",
-    "        endian = None\n",
-    "\n",
-    "        # load file header and grab channels, if is 'PF' 3 channels else 1 channel(gray scale)\n",
-    "        header = fp.readline().rstrip()\n",
-    "        if header == 'PF':\n",
-    "            color = True\n",
-    "        elif header == 'Pf':\n",
-    "            color = False\n",
-    "        else:\n",
-    "            raise Exception('Not a PFM file.')\n",
-    "\n",
-    "        # grab image dimensions\n",
-    "        dim_match = re.match(r'^(\\d+)\\s(\\d+)\\s$', fp.readline())\n",
-    "        if dim_match:\n",
-    "            width, height = map(int, dim_match.groups())\n",
-    "        else:\n",
-    "            raise Exception('Malformed PFM header.')\n",
-    "\n",
-    "        # grab image scale\n",
-    "        scale = float(fp.readline().rstrip())\n",
-    "        if scale < 0:  # little-endian\n",
-    "            endian = '<'\n",
-    "            scale = -scale\n",
-    "        else:\n",
-    "            endian = '>'  # big-endian\n",
-    "\n",
-    "        # grab image data\n",
-    "        data = np.fromfile(fp, endian + 'f')\n",
-    "        shape = (height, width, 3) if color else (height, width)\n",
-    "\n",
-    "        # reshape data to [Height, Width, Channels]\n",
-    "        data = np.reshape(data, shape)\n",
-    "        data = np.flipud(data)\n",
-    "\n",
-    "        return data\n",
-    "\n",
-    "\n",
-    "    \n",
-    "## AIF metrics; gt, recon must be scaled from 0-1, dim:(128, 128, 3)\n"
+    "psfs = data_dict_psf['psfs'][:,:,:,-25:][::2,::2]\n"
    ]
   },
   {
@@ -157,7 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "2157dcf3",
    "metadata": {},
    "outputs": [