Transfer Learning resnet152V2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transfer Learning Inception V3 using Keras"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Please download the dataset from the below url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.compat.v1 import ConfigProto\n",
    "from tensorflow.compat.v1 import InteractiveSession\n",
    "\n",
    "config = ConfigProto()\n",
    "config.gpu_options.per_process_gpu_memory_fraction = 0.2\n",
    "config.gpu_options.allow_growth = True\n",
    "session = InteractiveSession(config=config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the libraries as shown below\n",
    "\n",
    "from tensorflow.keras.layers import Input, Lambda, Dense, Flatten\n",
    "from tensorflow.keras.models import Model\n",
    "#from tensorflow.keras.applications.resnet152V2 import ResNet152V2\n",
    "#from keras.applications.vgg16 import VGG16\n",
    "from tensorflow.keras.applications.inception_v3 import preprocess_input\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator,load_img\n",
    "from tensorflow.keras.models import Sequential\n",
    "import numpy as np\n",
    "from glob import glob\n",
    "#import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# re-size all the images to this\n",
    "IMAGE_SIZE = [224, 224]\n",
    "\n",
    "train_path = 'Datasets/train'\n",
    "valid_path = 'Datasets/test'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the Vgg 16 library as shown below and add preprocessing layer to the front of VGG\n",
    "# Here we will be using imagenet weights\n",
    "import tensorflow\n",
    "resnet152V2 =tensorflow.keras.applications.ResNet152V2(input_shape=IMAGE_SIZE + [3], weights='imagenet', include_top=False)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# don't train existing weights\n",
    "for layer in resnet152V2.layers:\n",
    "    layer.trainable = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "  # useful for getting number of output classes\n",
    "folders = glob('Datasets/train/*')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# our layers - you can add more if you want\n",
    "x = Flatten()(resnet152V2.output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = Dense(len(folders), activation='softmax')(x)\n",
    "\n",
    "# create a model object\n",
    "model = Model(inputs=resnet152V2.input, outputs=prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, 224, 224, 3) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1_pad (ZeroPadding2D)       (None, 230, 230, 3)  0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv1_conv (Conv2D)             (None, 112, 112, 64) 9472        conv1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "pool1_pad (ZeroPadding2D)       (None, 114, 114, 64) 0           conv1_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "pool1_pool (MaxPooling2D)       (None, 56, 56, 64)   0           pool1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_preact_bn (BatchNo (None, 56, 56, 64)   256         pool1_pool[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_preact_relu (Activ (None, 56, 56, 64)   0           conv2_block1_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_conv (Conv2D)    (None, 56, 56, 64)   4096        conv2_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_relu (Activation (None, 56, 56, 64)   0           conv2_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block1_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_relu (Activation (None, 56, 56, 64)   0           conv2_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_0_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_out (Add)          (None, 56, 56, 256)  0           conv2_block1_0_conv[0][0]        \n",
      "                                                                 conv2_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block2_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block2_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_relu (Activation (None, 56, 56, 64)   0           conv2_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block2_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_relu (Activation (None, 56, 56, 64)   0           conv2_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_out (Add)          (None, 56, 56, 256)  0           conv2_block1_out[0][0]           \n",
      "                                                                 conv2_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block3_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block3_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_relu (Activation (None, 56, 56, 64)   0           conv2_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_conv (Conv2D)    (None, 28, 28, 64)   36864       conv2_block3_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_bn (BatchNormali (None, 28, 28, 64)   256         conv2_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_relu (Activation (None, 28, 28, 64)   0           conv2_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D)    (None, 28, 28, 256)  0           conv2_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_3_conv (Conv2D)    (None, 28, 28, 256)  16640       conv2_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_out (Add)          (None, 28, 28, 256)  0           max_pooling2d[0][0]              \n",
      "                                                                 conv2_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_preact_bn (BatchNo (None, 28, 28, 256)  1024        conv2_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_preact_relu (Activ (None, 28, 28, 256)  0           conv3_block1_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_conv (Conv2D)    (None, 28, 28, 128)  32768       conv3_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_relu (Activation (None, 28, 28, 128)  0           conv3_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block1_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_relu (Activation (None, 28, 28, 128)  0           conv3_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_0_conv (Conv2D)    (None, 28, 28, 512)  131584      conv3_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_out (Add)          (None, 28, 28, 512)  0           conv3_block1_0_conv[0][0]        \n",
      "                                                                 conv3_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block2_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block2_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_relu (Activation (None, 28, 28, 128)  0           conv3_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block2_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_relu (Activation (None, 28, 28, 128)  0           conv3_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_out (Add)          (None, 28, 28, 512)  0           conv3_block1_out[0][0]           \n",
      "                                                                 conv3_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block3_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block3_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_relu (Activation (None, 28, 28, 128)  0           conv3_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block3_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_relu (Activation (None, 28, 28, 128)  0           conv3_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_out (Add)          (None, 28, 28, 512)  0           conv3_block2_out[0][0]           \n",
      "                                                                 conv3_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block4_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block4_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block4_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_relu (Activation (None, 28, 28, 128)  0           conv3_block4_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block4_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block4_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block4_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_relu (Activation (None, 28, 28, 128)  0           conv3_block4_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block4_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_out (Add)          (None, 28, 28, 512)  0           conv3_block3_out[0][0]           \n",
      "                                                                 conv3_block4_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block4_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block5_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block5_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block5_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_relu (Activation (None, 28, 28, 128)  0           conv3_block5_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block5_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block5_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block5_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_relu (Activation (None, 28, 28, 128)  0           conv3_block5_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block5_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_out (Add)          (None, 28, 28, 512)  0           conv3_block4_out[0][0]           \n",
      "                                                                 conv3_block5_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block5_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block6_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block6_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block6_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_relu (Activation (None, 28, 28, 128)  0           conv3_block6_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block6_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block6_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block6_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_relu (Activation (None, 28, 28, 128)  0           conv3_block6_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block6_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_out (Add)          (None, 28, 28, 512)  0           conv3_block5_out[0][0]           \n",
      "                                                                 conv3_block6_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block6_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block7_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block7_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block7_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_relu (Activation (None, 28, 28, 128)  0           conv3_block7_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block7_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block7_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block7_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_relu (Activation (None, 28, 28, 128)  0           conv3_block7_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block7_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_out (Add)          (None, 28, 28, 512)  0           conv3_block6_out[0][0]           \n",
      "                                                                 conv3_block7_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block7_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block8_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block8_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block8_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_relu (Activation (None, 28, 28, 128)  0           conv3_block8_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block8_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_conv (Conv2D)    (None, 14, 14, 128)  147456      conv3_block8_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_bn (BatchNormali (None, 14, 14, 128)  512         conv3_block8_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_relu (Activation (None, 14, 14, 128)  0           conv3_block8_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 14, 14, 512)  0           conv3_block7_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_3_conv (Conv2D)    (None, 14, 14, 512)  66048       conv3_block8_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_out (Add)          (None, 14, 14, 512)  0           max_pooling2d_1[0][0]            \n",
      "                                                                 conv3_block8_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_preact_bn (BatchNo (None, 14, 14, 512)  2048        conv3_block8_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_preact_relu (Activ (None, 14, 14, 512)  0           conv4_block1_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_conv (Conv2D)    (None, 14, 14, 256)  131072      conv4_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_relu (Activation (None, 14, 14, 256)  0           conv4_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block1_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_relu (Activation (None, 14, 14, 256)  0           conv4_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_0_conv (Conv2D)    (None, 14, 14, 1024) 525312      conv4_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_0_conv[0][0]        \n",
      "                                                                 conv4_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block2_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block2_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_relu (Activation (None, 14, 14, 256)  0           conv4_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block2_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_relu (Activation (None, 14, 14, 256)  0           conv4_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_out[0][0]           \n",
      "                                                                 conv4_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block3_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block3_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_relu (Activation (None, 14, 14, 256)  0           conv4_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block3_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_relu (Activation (None, 14, 14, 256)  0           conv4_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_out (Add)          (None, 14, 14, 1024) 0           conv4_block2_out[0][0]           \n",
      "                                                                 conv4_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block4_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block4_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_relu (Activation (None, 14, 14, 256)  0           conv4_block4_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block4_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block4_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_relu (Activation (None, 14, 14, 256)  0           conv4_block4_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block4_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_out (Add)          (None, 14, 14, 1024) 0           conv4_block3_out[0][0]           \n",
      "                                                                 conv4_block4_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block4_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block5_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block5_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_relu (Activation (None, 14, 14, 256)  0           conv4_block5_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block5_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block5_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_relu (Activation (None, 14, 14, 256)  0           conv4_block5_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block5_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_out (Add)          (None, 14, 14, 1024) 0           conv4_block4_out[0][0]           \n",
      "                                                                 conv4_block5_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block5_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block6_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block6_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block6_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_relu (Activation (None, 14, 14, 256)  0           conv4_block6_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block6_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block6_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block6_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_relu (Activation (None, 14, 14, 256)  0           conv4_block6_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block6_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_out (Add)          (None, 14, 14, 1024) 0           conv4_block5_out[0][0]           \n",
      "                                                                 conv4_block6_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block6_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block7_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block7_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block7_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_relu (Activation (None, 14, 14, 256)  0           conv4_block7_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block7_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block7_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block7_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_relu (Activation (None, 14, 14, 256)  0           conv4_block7_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block7_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_out (Add)          (None, 14, 14, 1024) 0           conv4_block6_out[0][0]           \n",
      "                                                                 conv4_block7_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block7_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block8_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block8_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block8_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_relu (Activation (None, 14, 14, 256)  0           conv4_block8_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block8_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block8_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block8_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_relu (Activation (None, 14, 14, 256)  0           conv4_block8_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block8_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_out (Add)          (None, 14, 14, 1024) 0           conv4_block7_out[0][0]           \n",
      "                                                                 conv4_block8_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block8_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block9_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block9_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block9_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_relu (Activation (None, 14, 14, 256)  0           conv4_block9_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block9_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block9_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block9_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_relu (Activation (None, 14, 14, 256)  0           conv4_block9_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block9_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_out (Add)          (None, 14, 14, 1024) 0           conv4_block8_out[0][0]           \n",
      "                                                                 conv4_block9_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block9_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block10_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block10_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block10_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block10_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block10_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block10_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block10_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block10_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block10_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_out (Add)         (None, 14, 14, 1024) 0           conv4_block9_out[0][0]           \n",
      "                                                                 conv4_block10_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block10_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block11_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block11_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block11_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block11_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block11_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block11_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block11_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block11_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block11_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_out (Add)         (None, 14, 14, 1024) 0           conv4_block10_out[0][0]          \n",
      "                                                                 conv4_block11_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block11_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block12_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block12_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block12_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block12_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block12_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block12_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block12_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block12_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block12_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_out (Add)         (None, 14, 14, 1024) 0           conv4_block11_out[0][0]          \n",
      "                                                                 conv4_block12_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block12_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block13_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block13_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block13_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block13_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block13_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block13_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block13_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block13_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block13_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_out (Add)         (None, 14, 14, 1024) 0           conv4_block12_out[0][0]          \n",
      "                                                                 conv4_block13_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block13_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block14_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block14_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block14_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block14_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block14_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block14_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block14_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block14_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block14_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_out (Add)         (None, 14, 14, 1024) 0           conv4_block13_out[0][0]          \n",
      "                                                                 conv4_block14_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block14_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block15_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block15_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block15_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block15_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block15_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block15_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block15_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block15_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block15_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_out (Add)         (None, 14, 14, 1024) 0           conv4_block14_out[0][0]          \n",
      "                                                                 conv4_block15_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block15_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block16_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block16_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block16_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block16_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block16_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block16_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block16_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block16_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block16_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_out (Add)         (None, 14, 14, 1024) 0           conv4_block15_out[0][0]          \n",
      "                                                                 conv4_block16_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block16_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block17_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block17_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block17_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block17_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block17_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block17_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block17_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block17_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block17_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_out (Add)         (None, 14, 14, 1024) 0           conv4_block16_out[0][0]          \n",
      "                                                                 conv4_block17_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block17_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block18_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block18_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block18_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block18_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block18_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block18_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block18_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block18_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block18_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_out (Add)         (None, 14, 14, 1024) 0           conv4_block17_out[0][0]          \n",
      "                                                                 conv4_block18_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block18_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block19_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block19_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block19_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block19_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block19_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block19_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block19_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block19_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block19_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_out (Add)         (None, 14, 14, 1024) 0           conv4_block18_out[0][0]          \n",
      "                                                                 conv4_block19_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block19_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block20_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block20_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block20_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block20_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block20_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block20_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block20_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block20_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block20_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_out (Add)         (None, 14, 14, 1024) 0           conv4_block19_out[0][0]          \n",
      "                                                                 conv4_block20_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block20_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block21_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block21_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block21_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block21_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block21_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block21_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block21_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block21_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block21_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_out (Add)         (None, 14, 14, 1024) 0           conv4_block20_out[0][0]          \n",
      "                                                                 conv4_block21_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block21_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block22_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block22_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block22_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block22_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block22_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block22_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block22_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block22_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block22_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_out (Add)         (None, 14, 14, 1024) 0           conv4_block21_out[0][0]          \n",
      "                                                                 conv4_block22_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block22_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block23_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block23_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block23_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block23_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block23_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block23_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block23_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block23_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block23_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_out (Add)         (None, 14, 14, 1024) 0           conv4_block22_out[0][0]          \n",
      "                                                                 conv4_block23_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block23_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block24_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block24_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block24_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block24_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block24_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block24_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block24_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block24_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block24_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_out (Add)         (None, 14, 14, 1024) 0           conv4_block23_out[0][0]          \n",
      "                                                                 conv4_block24_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block24_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block25_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block25_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block25_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block25_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block25_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block25_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block25_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block25_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block25_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_out (Add)         (None, 14, 14, 1024) 0           conv4_block24_out[0][0]          \n",
      "                                                                 conv4_block25_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block25_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block26_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block26_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block26_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block26_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block26_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block26_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block26_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block26_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block26_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_out (Add)         (None, 14, 14, 1024) 0           conv4_block25_out[0][0]          \n",
      "                                                                 conv4_block26_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block26_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block27_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block27_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block27_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block27_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block27_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block27_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block27_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block27_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block27_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_out (Add)         (None, 14, 14, 1024) 0           conv4_block26_out[0][0]          \n",
      "                                                                 conv4_block27_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block27_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block28_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block28_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block28_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block28_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block28_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block28_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block28_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block28_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block28_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_out (Add)         (None, 14, 14, 1024) 0           conv4_block27_out[0][0]          \n",
      "                                                                 conv4_block28_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block28_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block29_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block29_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block29_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block29_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block29_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block29_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block29_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block29_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block29_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_out (Add)         (None, 14, 14, 1024) 0           conv4_block28_out[0][0]          \n",
      "                                                                 conv4_block29_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block29_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block30_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block30_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block30_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block30_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block30_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block30_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block30_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block30_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block30_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_out (Add)         (None, 14, 14, 1024) 0           conv4_block29_out[0][0]          \n",
      "                                                                 conv4_block30_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block30_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block31_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block31_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block31_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block31_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block31_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block31_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block31_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block31_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block31_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_out (Add)         (None, 14, 14, 1024) 0           conv4_block30_out[0][0]          \n",
      "                                                                 conv4_block31_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block31_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block32_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block32_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block32_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block32_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block32_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block32_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block32_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block32_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block32_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_out (Add)         (None, 14, 14, 1024) 0           conv4_block31_out[0][0]          \n",
      "                                                                 conv4_block32_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block32_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block33_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block33_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block33_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block33_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block33_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block33_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block33_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block33_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block33_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_out (Add)         (None, 14, 14, 1024) 0           conv4_block32_out[0][0]          \n",
      "                                                                 conv4_block33_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block33_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block34_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block34_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block34_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block34_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block34_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block34_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block34_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block34_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block34_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_out (Add)         (None, 14, 14, 1024) 0           conv4_block33_out[0][0]          \n",
      "                                                                 conv4_block34_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block34_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block35_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block35_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block35_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block35_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block35_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block35_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block35_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block35_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block35_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_out (Add)         (None, 14, 14, 1024) 0           conv4_block34_out[0][0]          \n",
      "                                                                 conv4_block35_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block35_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block36_preact_bn[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block36_preact_relu[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block36_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block36_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block36_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_conv (Conv2D)   (None, 7, 7, 256)    589824      conv4_block36_2_pad[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_bn (BatchNormal (None, 7, 7, 256)    1024        conv4_block36_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_relu (Activatio (None, 7, 7, 256)    0           conv4_block36_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 7, 7, 1024)   0           conv4_block35_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_3_conv (Conv2D)   (None, 7, 7, 1024)   263168      conv4_block36_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_out (Add)         (None, 7, 7, 1024)   0           max_pooling2d_2[0][0]            \n",
      "                                                                 conv4_block36_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_preact_bn (BatchNo (None, 7, 7, 1024)   4096        conv4_block36_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_preact_relu (Activ (None, 7, 7, 1024)   0           conv5_block1_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_conv (Conv2D)    (None, 7, 7, 512)    524288      conv5_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_relu (Activation (None, 7, 7, 512)    0           conv5_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block1_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_relu (Activation (None, 7, 7, 512)    0           conv5_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_0_conv (Conv2D)    (None, 7, 7, 2048)   2099200     conv5_block1_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_0_conv[0][0]        \n",
      "                                                                 conv5_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block2_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block2_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_relu (Activation (None, 7, 7, 512)    0           conv5_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block2_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_relu (Activation (None, 7, 7, 512)    0           conv5_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_out[0][0]           \n",
      "                                                                 conv5_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block3_preact_bn[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block3_preact_relu[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_relu (Activation (None, 7, 7, 512)    0           conv5_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block3_2_pad[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_relu (Activation (None, 7, 7, 512)    0           conv5_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_out (Add)          (None, 7, 7, 2048)   0           conv5_block2_out[0][0]           \n",
      "                                                                 conv5_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "post_bn (BatchNormalization)    (None, 7, 7, 2048)   8192        conv5_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "post_relu (Activation)          (None, 7, 7, 2048)   0           post_bn[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flatten (Flatten)               (None, 100352)       0           post_relu[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense (Dense)                   (None, 4)            401412      flatten[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 58,733,060\n",
      "Trainable params: 401,412\n",
      "Non-trainable params: 58,331,648\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# view the structure of the model\n",
    "model.summary()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tell the model what cost and optimization method to use\n",
    "model.compile(\n",
    "  loss='categorical_crossentropy',\n",
    "  optimizer='adam',\n",
    "  metrics=['accuracy']\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the Image Data Generator to import the images from the dataset\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "train_datagen = ImageDataGenerator(rescale = 1./255,\n",
    "                                   shear_range = 0.2,\n",
    "                                   zoom_range = 0.2,\n",
    "                                   horizontal_flip = True)\n",
    "\n",
    "test_datagen = ImageDataGenerator(rescale = 1./255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1951 images belonging to 4 classes.\n"
     ]
    }
   ],
   "source": [
    "# Make sure you provide the same target size as initialied for the image size\n",
    "training_set = train_datagen.flow_from_directory('Datasets/train',\n",
    "                                                 target_size = (224, 224),\n",
    "                                                 batch_size = 32,\n",
    "                                                 class_mode = 'categorical')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 18 images belonging to 4 classes.\n"
     ]
    }
   ],
   "source": [
    "test_set = test_datagen.flow_from_directory('Datasets/test',\n",
    "                                            target_size = (224, 224),\n",
    "                                            batch_size = 32,\n",
    "                                            class_mode = 'categorical')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-14-2d02736eff38>:8: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "Epoch 1/20\n",
      "61/61 [==============================] - 28s 466ms/step - loss: 1.4618 - accuracy: 0.8093 - val_loss: 0.0069 - val_accuracy: 1.0000\n",
      "Epoch 2/20\n",
      "61/61 [==============================] - 20s 324ms/step - loss: 0.4206 - accuracy: 0.9288 - val_loss: 0.0103 - val_accuracy: 1.0000\n",
      "Epoch 3/20\n",
      "61/61 [==============================] - 20s 327ms/step - loss: 0.3835 - accuracy: 0.9416 - val_loss: 0.3192 - val_accuracy: 0.8889\n",
      "Epoch 4/20\n",
      "61/61 [==============================] - 20s 327ms/step - loss: 0.3231 - accuracy: 0.9498 - val_loss: 0.9201 - val_accuracy: 0.8889\n",
      "Epoch 5/20\n",
      "61/61 [==============================] - 20s 327ms/step - loss: 0.1914 - accuracy: 0.9662 - val_loss: 0.3125 - val_accuracy: 0.9444\n",
      "Epoch 6/20\n",
      "61/61 [==============================] - 20s 330ms/step - loss: 0.2973 - accuracy: 0.9616 - val_loss: 0.7044 - val_accuracy: 0.9444\n",
      "Epoch 7/20\n",
      "61/61 [==============================] - 20s 328ms/step - loss: 0.2958 - accuracy: 0.9657 - val_loss: 0.0167 - val_accuracy: 1.0000\n",
      "Epoch 8/20\n",
      "61/61 [==============================] - 20s 328ms/step - loss: 0.3025 - accuracy: 0.9692 - val_loss: 1.0431 - val_accuracy: 0.9444\n",
      "Epoch 9/20\n",
      "61/61 [==============================] - 20s 327ms/step - loss: 0.3309 - accuracy: 0.9682 - val_loss: 0.5506 - val_accuracy: 0.9444\n",
      "Epoch 10/20\n",
      "61/61 [==============================] - 20s 321ms/step - loss: 0.2806 - accuracy: 0.9733 - val_loss: 0.4829 - val_accuracy: 0.8889\n",
      "Epoch 11/20\n",
      "61/61 [==============================] - 19s 320ms/step - loss: 0.2029 - accuracy: 0.9769 - val_loss: 0.2896 - val_accuracy: 0.9444\n",
      "Epoch 12/20\n",
      "61/61 [==============================] - 19s 319ms/step - loss: 0.2322 - accuracy: 0.9698 - val_loss: 0.1019 - val_accuracy: 0.9444\n",
      "Epoch 13/20\n",
      "61/61 [==============================] - 20s 321ms/step - loss: 0.2119 - accuracy: 0.9728 - val_loss: 1.4550e-04 - val_accuracy: 1.0000\n",
      "Epoch 14/20\n",
      "61/61 [==============================] - 20s 322ms/step - loss: 0.2009 - accuracy: 0.9769 - val_loss: 0.4633 - val_accuracy: 0.9444\n",
      "Epoch 15/20\n",
      "61/61 [==============================] - 20s 320ms/step - loss: 0.1325 - accuracy: 0.9836 - val_loss: 1.0994e-06 - val_accuracy: 1.0000\n",
      "Epoch 16/20\n",
      "61/61 [==============================] - 19s 318ms/step - loss: 0.2099 - accuracy: 0.9795 - val_loss: 0.0091 - val_accuracy: 1.0000\n",
      "Epoch 17/20\n",
      "61/61 [==============================] - 19s 318ms/step - loss: 0.1249 - accuracy: 0.9810 - val_loss: 0.0000e+00 - val_accuracy: 1.0000\n",
      "Epoch 18/20\n",
      "61/61 [==============================] - 19s 319ms/step - loss: 0.1294 - accuracy: 0.9826 - val_loss: 1.3245e-08 - val_accuracy: 1.0000\n",
      "Epoch 19/20\n",
      "61/61 [==============================] - 19s 318ms/step - loss: 0.2218 - accuracy: 0.9795 - val_loss: 1.1013e-05 - val_accuracy: 1.0000\n",
      "Epoch 20/20\n",
      "61/61 [==============================] - 19s 319ms/step - loss: 0.2298 - accuracy: 0.9800 - val_loss: 1.8554e-05 - val_accuracy: 1.0000\n"
     ]
    }
   ],
   "source": [
    "# fit the model\n",
    "# Run the cell. It will take some time to execute\n",
    "r = model.fit_generator(\n",
    "  training_set,\n",
    "  validation_data=test_set,\n",
    "  epochs=20,\n",
    "  steps_per_epoch=len(training_set),\n",
    "  validation_steps=len(test_set)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the loss\n",
    "plt.plot(r.history['loss'], label='train loss')\n",
    "plt.plot(r.history['val_loss'], label='val loss')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.savefig('LossVal_loss')\n",
    "\n",
    "# plot the accuracy\n",
    "plt.plot(r.history['accuracy'], label='train acc')\n",
    "plt.plot(r.history['val_accuracy'], label='val acc')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.savefig('AccVal_acc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save it as a h5 file\n",
    "\n",
    "\n",
    "from tensorflow.keras.models import load_model\n",
    "\n",
    "model.save('model_resnet152V2.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "y_pred = model.predict(test_set)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.3846088e-29, 2.2531559e-23, 1.0000000e+00, 0.0000000e+00],\n",
       "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
       "       [2.1657728e-08, 1.2172376e-20, 1.0000000e+00, 1.5230057e-28],\n",
       "       [4.8872598e-30, 0.0000000e+00, 1.0000000e+00, 0.0000000e+00],\n",
       "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
       "       [1.0000000e+00, 0.0000000e+00, 1.3303991e-33, 0.0000000e+00],\n",
       "       [4.5714924e-16, 8.6781859e-11, 1.3235285e-09, 1.0000000e+00],\n",
       "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
       "       [5.4839473e-28, 1.0000000e+00, 3.3122518e-22, 6.6293510e-21],\n",
       "       [1.0000000e+00, 5.0101860e-30, 0.0000000e+00, 0.0000000e+00],\n",
       "       [7.8975147e-36, 2.7945514e-23, 1.0478895e-18, 1.0000000e+00],\n",
       "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 1.2099686e-36],\n",
       "       [0.0000000e+00, 0.0000000e+00, 1.0000000e+00, 0.0000000e+00],\n",
       "       [5.2780553e-25, 1.6846226e-15, 1.0000000e+00, 1.5684442e-16],\n",
       "       [0.0000000e+00, 3.1915728e-17, 0.0000000e+00, 1.0000000e+00],\n",
       "       [3.0335591e-24, 0.0000000e+00, 1.0000000e+00, 9.1854229e-36],\n",
       "       [4.6160116e-12, 5.1804220e-14, 1.4135714e-14, 1.0000000e+00],\n",
       "       [1.1229754e-26, 1.5938108e-01, 2.6465597e-11, 8.4061897e-01]],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "y_pred = np.argmax(y_pred, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 1, 2, 2, 1, 0, 3, 1, 1, 0, 3, 1, 2, 2, 3, 2, 3, 3], dtype=int64)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.models import load_model\n",
    "from tensorflow.keras.preprocessing import image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=load_model('model_resnet50.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[[ 6.7060997e+01,  5.4221001e+01,  4.7320000e+01],\n",
       "         [ 6.9060997e+01,  5.6221001e+01,  4.9320000e+01],\n",
       "         [ 7.3060997e+01,  6.0221001e+01,  5.3320000e+01],\n",
       "         ...,\n",
       "         [ 7.4060997e+01,  5.6221001e+01,  4.6320000e+01],\n",
       "         [ 5.5060997e+01,  3.7221001e+01,  2.7320000e+01],\n",
       "         [ 4.1060997e+01,  2.3221001e+01,  1.3320000e+01]],\n",
       "\n",
       "        [[ 7.5060997e+01,  6.2221001e+01,  5.5320000e+01],\n",
       "         [ 7.8060997e+01,  6.5221001e+01,  5.8320000e+01],\n",
       "         [ 8.1060997e+01,  6.8221001e+01,  6.1320000e+01],\n",
       "         ...,\n",
       "         [ 9.7060997e+01,  7.9221001e+01,  6.9320000e+01],\n",
       "         [ 7.3060997e+01,  5.5221001e+01,  4.5320000e+01],\n",
       "         [ 4.9060997e+01,  3.1221001e+01,  2.1320000e+01]],\n",
       "\n",
       "        [[ 8.7060997e+01,  7.4221001e+01,  6.7320000e+01],\n",
       "         [ 9.0060997e+01,  7.7221001e+01,  7.0320000e+01],\n",
       "         [ 9.3060997e+01,  8.0221001e+01,  7.3320000e+01],\n",
       "         ...,\n",
       "         [ 1.0106100e+02,  8.3221001e+01,  7.3320000e+01],\n",
       "         [ 7.5060997e+01,  5.7221001e+01,  4.7320000e+01],\n",
       "         [ 5.0060997e+01,  3.2221001e+01,  2.2320000e+01]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 1.0406100e+02,  8.9221001e+01,  9.4320000e+01],\n",
       "         [ 1.0206100e+02,  8.7221001e+01,  9.2320000e+01],\n",
       "         [ 9.9060997e+01,  8.4221001e+01,  8.9320000e+01],\n",
       "         ...,\n",
       "         [-1.0939003e+01, -1.6778999e+01, -1.4680000e+01],\n",
       "         [-1.0939003e+01, -1.6778999e+01, -1.4680000e+01],\n",
       "         [-1.0939003e+01, -1.6778999e+01, -1.4680000e+01]],\n",
       "\n",
       "        [[ 1.0606100e+02,  9.1221001e+01,  9.6320000e+01],\n",
       "         [ 1.0406100e+02,  8.9221001e+01,  9.4320000e+01],\n",
       "         [ 1.0006100e+02,  8.5221001e+01,  9.0320000e+01],\n",
       "         ...,\n",
       "         [-5.9390030e+00, -1.1778999e+01, -9.6800003e+00],\n",
       "         [-5.9390030e+00, -1.1778999e+01, -9.6800003e+00],\n",
       "         [-5.9390030e+00, -1.1778999e+01, -9.6800003e+00]],\n",
       "\n",
       "        [[ 1.0806100e+02,  9.4221001e+01,  9.6320000e+01],\n",
       "         [ 1.0606100e+02,  9.2221001e+01,  9.4320000e+01],\n",
       "         [ 1.0206100e+02,  8.8221001e+01,  9.0320000e+01],\n",
       "         ...,\n",
       "         [ 6.0997009e-02, -5.7789993e+00, -3.6800003e+00],\n",
       "         [ 6.0997009e-02, -5.7789993e+00, -3.6800003e+00],\n",
       "         [ 6.0997009e-02, -5.7789993e+00, -3.6800003e+00]]]],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "img=image.load_img('Datasets/Test/Coffee/download (2).jpg',target_size=(224,224))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        ...,\n",
       "        [254., 254., 254.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]],\n",
       "\n",
       "       [[254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        ...,\n",
       "        [254., 254., 254.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]],\n",
       "\n",
       "       [[254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        [254., 254., 254.],\n",
       "        ...,\n",
       "        [254., 254., 254.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        ...,\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]],\n",
       "\n",
       "       [[255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        ...,\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]],\n",
       "\n",
       "       [[255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        ...,\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.],\n",
       "        [255., 255., 255.]]], dtype=float32)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=image.img_to_array(img)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(224, 224, 3)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=x/255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 224, 224, 3)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "x=np.expand_dims(x,axis=0)\n",
    "img_data=preprocess_input(x)\n",
    "img_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.9745471, 0.0254529]], dtype=float32)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(img_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=np.argmax(model.predict(img_data), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a==1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.2.0'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
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