Resnet152V2_Model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "DQbTJfH2AxCa"
      },
      "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 keras.applications.resnet50 import ResNet50\n",
        "from tensorflow.keras.applications.vgg16 import VGG16\n",
        "from tensorflow.keras.applications.resnet_v2 import ResNet152V2\n",
        "from tensorflow.keras.applications.vgg16 import preprocess_input\n",
        "from tensorflow.keras.preprocessing import image\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\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",
      "source": [
        "# re-size all the images to this\n",
        "IMAGE_SIZE = [224, 224]\n",
        "\n",
        "train_path = '/content/drive/MyDrive/X-Ray-Based-Lungs-Disease-Detection-main/Splitted Dataset/train'\n",
        "valid_path = '/content/drive/MyDrive/X-Ray-Based-Lungs-Disease-Detection-main/Splitted Dataset/test'"
      ],
      "metadata": {
        "id": "1B0joJoZhgh2"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "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",
        "\n",
        "res152V2 = ResNet152V2(input_shape=IMAGE_SIZE + [3], weights='imagenet', include_top=False)"
      ],
      "metadata": {
        "id": "Eva9_StCiThR"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# don't train existing weights\n",
        "for layer in res152V2.layers:\n",
        "    layer.trainable = False"
      ],
      "metadata": {
        "id": "qwfYPbE4iV4f"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# useful for getting number of output classes\n",
        "folders = glob('/content/drive/MyDrive/X-Ray-Based-Lungs-Disease-Detection-main/Splitted Dataset/train/*')"
      ],
      "metadata": {
        "id": "-tFi6tuzibmj"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# our layers - you can add more if you want\n",
        "x = Flatten()(res152V2.output)\n",
        "prediction = Dense(len(folders), activation='softmax')(x)"
      ],
      "metadata": {
        "id": "RwJtizp-jBrX"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# create a model object\n",
        "model = Model(inputs=res152V2.input, outputs=prediction)"
      ],
      "metadata": {
        "id": "ueJL9IMUjK2q"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# view the structure of the model\n",
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JSPdrThEjMqj",
        "outputId": "62e2aaef-2507-491d-f9a5-bf5feeee8d0f"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"model_1\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                   Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            " input_2 (InputLayer)           [(None, 224, 224, 3  0           []                               \n",
            "                                )]                                                                \n",
            "                                                                                                  \n",
            " conv1_pad (ZeroPadding2D)      (None, 230, 230, 3)  0           ['input_2[0][0]']                \n",
            "                                                                                                  \n",
            " conv1_conv (Conv2D)            (None, 112, 112, 64  9472        ['conv1_pad[0][0]']              \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " pool1_pad (ZeroPadding2D)      (None, 114, 114, 64  0           ['conv1_conv[0][0]']             \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " pool1_pool (MaxPooling2D)      (None, 56, 56, 64)   0           ['pool1_pad[0][0]']              \n",
            "                                                                                                  \n",
            " conv2_block1_preact_bn (BatchN  (None, 56, 56, 64)  256         ['pool1_pool[0][0]']             \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv2_block1_preact_relu (Acti  (None, 56, 56, 64)  0           ['conv2_block1_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv2_block1_1_conv (Conv2D)   (None, 56, 56, 64)   4096        ['conv2_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv2_block1_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block1_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block1_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block1_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_2_pad (ZeroPaddin  (None, 58, 58, 64)  0           ['conv2_block1_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv2_block1_2_conv (Conv2D)   (None, 56, 56, 64)   36864       ['conv2_block1_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv2_block1_2_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block1_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block1_2_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block1_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_0_conv (Conv2D)   (None, 56, 56, 256)  16640       ['conv2_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \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 (BatchN  (None, 56, 56, 256)  1024       ['conv2_block1_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv2_block2_preact_relu (Acti  (None, 56, 56, 256)  0          ['conv2_block2_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv2_block2_1_conv (Conv2D)   (None, 56, 56, 64)   16384       ['conv2_block2_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv2_block2_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block2_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block2_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block2_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block2_2_pad (ZeroPaddin  (None, 58, 58, 64)  0           ['conv2_block2_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv2_block2_2_conv (Conv2D)   (None, 56, 56, 64)   36864       ['conv2_block2_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv2_block2_2_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block2_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block2_2_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block2_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 56, 56, 256)  1024       ['conv2_block2_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv2_block3_preact_relu (Acti  (None, 56, 56, 256)  0          ['conv2_block3_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv2_block3_1_conv (Conv2D)   (None, 56, 56, 64)   16384       ['conv2_block3_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv2_block3_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block3_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block3_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block3_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block3_2_pad (ZeroPaddin  (None, 58, 58, 64)  0           ['conv2_block3_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv2_block3_2_conv (Conv2D)   (None, 28, 28, 64)   36864       ['conv2_block3_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv2_block3_2_bn (BatchNormal  (None, 28, 28, 64)  256         ['conv2_block3_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv2_block3_2_relu (Activatio  (None, 28, 28, 64)  0           ['conv2_block3_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " max_pooling2d_3 (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_3[0][0]',        \n",
            "                                                                  'conv2_block3_3_conv[0][0]']    \n",
            "                                                                                                  \n",
            " conv3_block1_preact_bn (BatchN  (None, 28, 28, 256)  1024       ['conv2_block3_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block1_preact_relu (Acti  (None, 28, 28, 256)  0          ['conv3_block1_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block1_1_conv (Conv2D)   (None, 28, 28, 128)  32768       ['conv3_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block1_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block1_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block1_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block1_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block1_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block1_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block1_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block1_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block1_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block1_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block1_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_0_conv (Conv2D)   (None, 28, 28, 512)  131584      ['conv3_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block1_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block2_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block2_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block2_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block2_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block2_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block2_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block2_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block2_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block2_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block2_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block2_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block2_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block2_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block2_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block2_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block2_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block2_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block3_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block3_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block3_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block3_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block3_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block3_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block3_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block3_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block3_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block3_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block3_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block3_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block3_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block3_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block3_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block3_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block3_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block4_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block4_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block4_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block4_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block4_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block4_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block4_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block4_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block4_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block4_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block4_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block4_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block4_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block4_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block4_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block4_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block4_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block5_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block5_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block5_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block5_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block5_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block5_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block5_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block5_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block5_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block5_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block5_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block5_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block5_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block5_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block5_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block5_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block5_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block6_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block6_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block6_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block6_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block6_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block6_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block6_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block6_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block6_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block6_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block6_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block6_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block6_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block6_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block6_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block6_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block6_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block7_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block7_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block7_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block7_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block7_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block7_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block7_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block7_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block7_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block7_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block7_2_conv (Conv2D)   (None, 28, 28, 128)  147456      ['conv3_block7_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block7_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block7_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block7_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block7_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 28, 28, 512)  2048       ['conv3_block7_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv3_block8_preact_relu (Acti  (None, 28, 28, 512)  0          ['conv3_block8_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv3_block8_1_conv (Conv2D)   (None, 28, 28, 128)  65536       ['conv3_block8_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv3_block8_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block8_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block8_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block8_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block8_2_pad (ZeroPaddin  (None, 30, 30, 128)  0          ['conv3_block8_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv3_block8_2_conv (Conv2D)   (None, 14, 14, 128)  147456      ['conv3_block8_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv3_block8_2_bn (BatchNormal  (None, 14, 14, 128)  512        ['conv3_block8_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv3_block8_2_relu (Activatio  (None, 14, 14, 128)  0          ['conv3_block8_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " max_pooling2d_4 (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_4[0][0]',        \n",
            "                                                                  'conv3_block8_3_conv[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block1_preact_bn (BatchN  (None, 14, 14, 512)  2048       ['conv3_block8_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv4_block1_preact_relu (Acti  (None, 14, 14, 512)  0          ['conv4_block1_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv4_block1_1_conv (Conv2D)   (None, 14, 14, 256)  131072      ['conv4_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block1_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block1_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block1_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block1_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block1_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block1_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block1_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block1_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block1_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block1_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block1_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_0_conv (Conv2D)   (None, 14, 14, 1024  525312      ['conv4_block1_preact_relu[0][0]'\n",
            "                                )                                ]                                \n",
            "                                                                                                  \n",
            " conv4_block1_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block1_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block1_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block2_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block2_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block2_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block2_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block2_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block2_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block2_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block2_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block2_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block2_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block2_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block2_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block2_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block2_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block2_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block2_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block2_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block2_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block2_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block3_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block3_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block3_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block3_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block3_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block3_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block3_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block3_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block3_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block3_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block3_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block3_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block3_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block3_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block3_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block3_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block3_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block3_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block3_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block4_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block4_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block4_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block4_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block4_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block4_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block4_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block4_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block4_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block4_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block4_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block4_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block4_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block4_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block4_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block4_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block4_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block4_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block4_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block5_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block5_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block5_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block5_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block5_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block5_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block5_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block5_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block5_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block5_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block5_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block5_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block5_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block5_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block5_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block5_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block5_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block5_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block5_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block6_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block6_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block6_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block6_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block6_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block6_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block6_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block6_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block6_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block6_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block6_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block6_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block6_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block6_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block6_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block6_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block6_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block6_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block6_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block7_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block7_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block7_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block7_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block7_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block7_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block7_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block7_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block7_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block7_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block7_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block7_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block7_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block7_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block7_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block7_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block7_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block7_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block7_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block8_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block8_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block8_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block8_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block8_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block8_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block8_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block8_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block8_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block8_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block8_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block8_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block8_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block8_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block8_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block8_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block8_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block8_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (BatchN  (None, 14, 14, 1024  4096       ['conv4_block8_out[0][0]']       \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block9_preact_relu (Acti  (None, 14, 14, 1024  0          ['conv4_block9_preact_bn[0][0]'] \n",
            " vation)                        )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block9_1_conv (Conv2D)   (None, 14, 14, 256)  262144      ['conv4_block9_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv4_block9_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block9_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block9_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block9_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block9_2_pad (ZeroPaddin  (None, 16, 16, 256)  0          ['conv4_block9_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv4_block9_2_conv (Conv2D)   (None, 14, 14, 256)  589824      ['conv4_block9_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv4_block9_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block9_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv4_block9_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block9_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block9_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block9_2_relu[0][0]']    \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block9_out[0][0]']       \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block10_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block10_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block10_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block10_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block10_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block10_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block10_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block10_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block10_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block10_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block10_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block10_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block10_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block10_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block10_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block10_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block10_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block10_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block10_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block11_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block11_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block11_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block11_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block11_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block11_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block11_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block11_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block11_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block11_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block11_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block11_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block11_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block11_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block11_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block11_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block11_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block11_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block11_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block12_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block12_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block12_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block12_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block12_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block12_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block12_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block12_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block12_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block12_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block12_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block12_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block12_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block12_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block12_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block12_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block12_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block12_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block12_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block13_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block13_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block13_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block13_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block13_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block13_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block13_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block13_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block13_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block13_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block13_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block13_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block13_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block13_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block13_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block13_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block13_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block13_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block13_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block14_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block14_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block14_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block14_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block14_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block14_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block14_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block14_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block14_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block14_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block14_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block14_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block14_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block14_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block14_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block14_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block14_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block14_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block14_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block15_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block15_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block15_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block15_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block15_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block15_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block15_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block15_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block15_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block15_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block15_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block15_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block15_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block15_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block15_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block15_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block15_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block15_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block15_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block16_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block16_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block16_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block16_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block16_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block16_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block16_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block16_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block16_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block16_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block16_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block16_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block16_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block16_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block16_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block16_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block16_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block16_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block16_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block17_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block17_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block17_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block17_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block17_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block17_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block17_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block17_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block17_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block17_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block17_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block17_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block17_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block17_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block17_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block17_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block17_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block17_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block17_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block18_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block18_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block18_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block18_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block18_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block18_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block18_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block18_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block18_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block18_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block18_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block18_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block18_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block18_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block18_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block18_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block18_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block18_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block18_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block19_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block19_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block19_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block19_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block19_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block19_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block19_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block19_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block19_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block19_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block19_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block19_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block19_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block19_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block19_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block19_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block19_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block19_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block19_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block20_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block20_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block20_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block20_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block20_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block20_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block20_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block20_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block20_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block20_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block20_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block20_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block20_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block20_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block20_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block20_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block20_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block20_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block20_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block21_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block21_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block21_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block21_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block21_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block21_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block21_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block21_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block21_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block21_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block21_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block21_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block21_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block21_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block21_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block21_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block21_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block21_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block21_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block22_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block22_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block22_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block22_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block22_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block22_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block22_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block22_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block22_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block22_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block22_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block22_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block22_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block22_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block22_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block22_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block22_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block22_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block22_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block23_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block23_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block23_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block23_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block23_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block23_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block23_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block23_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block23_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block23_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block23_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block23_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block23_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block23_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block23_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block23_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block23_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block23_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block23_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block24_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block24_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block24_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block24_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block24_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block24_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block24_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block24_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block24_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block24_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block24_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block24_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block24_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block24_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block24_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block24_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block24_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block24_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block24_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block25_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block25_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block25_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block25_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block25_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block25_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block25_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block25_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block25_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block25_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block25_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block25_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block25_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block25_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block25_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block25_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block25_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block25_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block25_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block26_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block26_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block26_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block26_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block26_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block26_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block26_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block26_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block26_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block26_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block26_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block26_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block26_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block26_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block26_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block26_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block26_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block26_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block26_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block27_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block27_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block27_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block27_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block27_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block27_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block27_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block27_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block27_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block27_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block27_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block27_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block27_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block27_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block27_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block27_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block27_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block27_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block27_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block28_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block28_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block28_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block28_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block28_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block28_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block28_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block28_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block28_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block28_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block28_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block28_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block28_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block28_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block28_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block28_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block28_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block28_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block28_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block29_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block29_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block29_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block29_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block29_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block29_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block29_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block29_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block29_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block29_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block29_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block29_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block29_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block29_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block29_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block29_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block29_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block29_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block29_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block30_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block30_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block30_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block30_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block30_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block30_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block30_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block30_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block30_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block30_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block30_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block30_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block30_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block30_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block30_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block30_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block30_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block30_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block30_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block31_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block31_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block31_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block31_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block31_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block31_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block31_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block31_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block31_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block31_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block31_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block31_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block31_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block31_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block31_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block31_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block31_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block31_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block31_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block32_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block32_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block32_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block32_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block32_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block32_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block32_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block32_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block32_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block32_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block32_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block32_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block32_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block32_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block32_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block32_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block32_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block32_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block32_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block33_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block33_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block33_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block33_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block33_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block33_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block33_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block33_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block33_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block33_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block33_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block33_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block33_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block33_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block33_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block33_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block33_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block33_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block33_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block34_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block34_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block34_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block34_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block34_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block34_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block34_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block34_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block34_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block34_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block34_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block34_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block34_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block34_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block34_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block34_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block34_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block34_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block34_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block35_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block35_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block35_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block35_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block35_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block35_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block35_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block35_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block35_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block35_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block35_2_conv (Conv2D)  (None, 14, 14, 256)  589824      ['conv4_block35_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block35_2_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block35_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block35_2_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block35_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block35_3_conv (Conv2D)  (None, 14, 14, 1024  263168      ['conv4_block35_2_relu[0][0]']   \n",
            "                                )                                                                 \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 (Batch  (None, 14, 14, 1024  4096       ['conv4_block35_out[0][0]']      \n",
            " Normalization)                 )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block36_preact_relu (Act  (None, 14, 14, 1024  0          ['conv4_block36_preact_bn[0][0]']\n",
            " ivation)                       )                                                                 \n",
            "                                                                                                  \n",
            " conv4_block36_1_conv (Conv2D)  (None, 14, 14, 256)  262144      ['conv4_block36_preact_relu[0][0]\n",
            "                                                                 ']                               \n",
            "                                                                                                  \n",
            " conv4_block36_1_bn (BatchNorma  (None, 14, 14, 256)  1024       ['conv4_block36_1_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block36_1_relu (Activati  (None, 14, 14, 256)  0          ['conv4_block36_1_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block36_2_pad (ZeroPaddi  (None, 16, 16, 256)  0          ['conv4_block36_1_relu[0][0]']   \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv4_block36_2_conv (Conv2D)  (None, 7, 7, 256)    589824      ['conv4_block36_2_pad[0][0]']    \n",
            "                                                                                                  \n",
            " conv4_block36_2_bn (BatchNorma  (None, 7, 7, 256)   1024        ['conv4_block36_2_conv[0][0]']   \n",
            " lization)                                                                                        \n",
            "                                                                                                  \n",
            " conv4_block36_2_relu (Activati  (None, 7, 7, 256)   0           ['conv4_block36_2_bn[0][0]']     \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " max_pooling2d_5 (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_5[0][0]',        \n",
            "                                                                  'conv4_block36_3_conv[0][0]']   \n",
            "                                                                                                  \n",
            " conv5_block1_preact_bn (BatchN  (None, 7, 7, 1024)  4096        ['conv4_block36_out[0][0]']      \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv5_block1_preact_relu (Acti  (None, 7, 7, 1024)  0           ['conv5_block1_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv5_block1_1_conv (Conv2D)   (None, 7, 7, 512)    524288      ['conv5_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv5_block1_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block1_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block1_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block1_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_2_pad (ZeroPaddin  (None, 9, 9, 512)   0           ['conv5_block1_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv5_block1_2_conv (Conv2D)   (None, 7, 7, 512)    2359296     ['conv5_block1_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv5_block1_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block1_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block1_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block1_2_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_0_conv (Conv2D)   (None, 7, 7, 2048)   2099200     ['conv5_block1_preact_relu[0][0]'\n",
            "                                                                 ]                                \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 (BatchN  (None, 7, 7, 2048)  8192        ['conv5_block1_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv5_block2_preact_relu (Acti  (None, 7, 7, 2048)  0           ['conv5_block2_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv5_block2_1_conv (Conv2D)   (None, 7, 7, 512)    1048576     ['conv5_block2_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv5_block2_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block2_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block2_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block2_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block2_2_pad (ZeroPaddin  (None, 9, 9, 512)   0           ['conv5_block2_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv5_block2_2_conv (Conv2D)   (None, 7, 7, 512)    2359296     ['conv5_block2_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv5_block2_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block2_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block2_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block2_2_bn[0][0]']      \n",
            " n)                                                                                               \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 (BatchN  (None, 7, 7, 2048)  8192        ['conv5_block2_out[0][0]']       \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " conv5_block3_preact_relu (Acti  (None, 7, 7, 2048)  0           ['conv5_block3_preact_bn[0][0]'] \n",
            " vation)                                                                                          \n",
            "                                                                                                  \n",
            " conv5_block3_1_conv (Conv2D)   (None, 7, 7, 512)    1048576     ['conv5_block3_preact_relu[0][0]'\n",
            "                                                                 ]                                \n",
            "                                                                                                  \n",
            " conv5_block3_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block3_1_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block3_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block3_1_bn[0][0]']      \n",
            " n)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block3_2_pad (ZeroPaddin  (None, 9, 9, 512)   0           ['conv5_block3_1_relu[0][0]']    \n",
            " g2D)                                                                                             \n",
            "                                                                                                  \n",
            " conv5_block3_2_conv (Conv2D)   (None, 7, 7, 512)    2359296     ['conv5_block3_2_pad[0][0]']     \n",
            "                                                                                                  \n",
            " conv5_block3_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block3_2_conv[0][0]']    \n",
            " ization)                                                                                         \n",
            "                                                                                                  \n",
            " conv5_block3_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block3_2_bn[0][0]']      \n",
            " n)                                                                                               \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_1 (Flatten)            (None, 100352)       0           ['post_relu[0][0]']              \n",
            "                                                                                                  \n",
            " dense_1 (Dense)                (None, 5)            501765      ['flatten_1[0][0]']              \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 58,833,413\n",
            "Trainable params: 501,765\n",
            "Non-trainable params: 58,331,648\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "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",
        ")"
      ],
      "metadata": {
        "id": "RdZBqGmVjP6f"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "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)"
      ],
      "metadata": {
        "id": "MRjaXbRqjkoA"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Make sure you provide the same target size as initialied for the image size\n",
        "training_set = train_datagen.flow_from_directory('/content/drive/MyDrive/X-Ray-Based-Lungs-Disease-Detection-main/Splitted Dataset/train',\n",
        "                                                 target_size = (224, 224),\n",
        "                                                 batch_size = 64,\n",
        "                                                 class_mode = 'categorical')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ISFzNQ4PjnjP",
        "outputId": "23730d07-9947-47ad-cc3b-c9fb8db30e13"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 6073 images belonging to 5 classes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_set = test_datagen.flow_from_directory('/content/drive/MyDrive/X-Ray-Based-Lungs-Disease-Detection-main/Splitted Dataset/test',\n",
        "                                            target_size = (224, 224),\n",
        "                                            batch_size = 64,\n",
        "                                            class_mode = 'categorical')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZB4slRHnlIos",
        "outputId": "dcee512a-db85-4ced-ab4f-ab9500c34c36"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 2025 images belonging to 5 classes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "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=25,\n",
        "    steps_per_epoch=len(training_set),\n",
        "    validation_steps=len(test_set)\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Koh3FrI5ll9_",
        "outputId": "a15ea79a-258d-4679-c061-ac0522a80d32"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-29-3c92dd699ccc>:3: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
            "  r = model.fit_generator(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/25\n",
            "95/95 [==============================] - 1981s 21s/step - loss: 2.7707 - accuracy: 0.7235 - val_loss: 1.6995 - val_accuracy: 0.8094\n",
            "Epoch 2/25\n",
            "95/95 [==============================] - 208s 2s/step - loss: 1.6614 - accuracy: 0.8080 - val_loss: 1.7796 - val_accuracy: 0.8188\n",
            "Epoch 3/25\n",
            "95/95 [==============================] - 210s 2s/step - loss: 1.4101 - accuracy: 0.8434 - val_loss: 1.8760 - val_accuracy: 0.8114\n",
            "Epoch 4/25\n",
            "95/95 [==============================] - 203s 2s/step - loss: 1.2850 - accuracy: 0.8566 - val_loss: 2.2121 - val_accuracy: 0.8148\n",
            "Epoch 5/25\n",
            "95/95 [==============================] - 209s 2s/step - loss: 1.4637 - accuracy: 0.8599 - val_loss: 3.0551 - val_accuracy: 0.7965\n",
            "Epoch 6/25\n",
            "95/95 [==============================] - 203s 2s/step - loss: 1.2705 - accuracy: 0.8753 - val_loss: 3.1468 - val_accuracy: 0.8138\n",
            "Epoch 7/25\n",
            "95/95 [==============================] - 205s 2s/step - loss: 1.1775 - accuracy: 0.8841 - val_loss: 2.2446 - val_accuracy: 0.8346\n",
            "Epoch 8/25\n",
            "95/95 [==============================] - 208s 2s/step - loss: 1.2303 - accuracy: 0.8836 - val_loss: 3.0498 - val_accuracy: 0.8277\n",
            "Epoch 9/25\n",
            "95/95 [==============================] - 207s 2s/step - loss: 1.2081 - accuracy: 0.8869 - val_loss: 2.3855 - val_accuracy: 0.8410\n",
            "Epoch 10/25\n",
            "95/95 [==============================] - 204s 2s/step - loss: 1.2509 - accuracy: 0.8885 - val_loss: 3.2698 - val_accuracy: 0.8316\n",
            "Epoch 11/25\n",
            "95/95 [==============================] - 208s 2s/step - loss: 1.2776 - accuracy: 0.8875 - val_loss: 4.2200 - val_accuracy: 0.8005\n",
            "Epoch 12/25\n",
            "95/95 [==============================] - 206s 2s/step - loss: 1.4137 - accuracy: 0.8902 - val_loss: 3.6751 - val_accuracy: 0.8212\n",
            "Epoch 13/25\n",
            "95/95 [==============================] - 205s 2s/step - loss: 1.2500 - accuracy: 0.8981 - val_loss: 3.2326 - val_accuracy: 0.8326\n",
            "Epoch 14/25\n",
            "95/95 [==============================] - 201s 2s/step - loss: 1.1749 - accuracy: 0.9009 - val_loss: 3.5066 - val_accuracy: 0.8341\n",
            "Epoch 15/25\n",
            "95/95 [==============================] - 202s 2s/step - loss: 0.8781 - accuracy: 0.9223 - val_loss: 2.6436 - val_accuracy: 0.8484\n",
            "Epoch 16/25\n",
            "95/95 [==============================] - 211s 2s/step - loss: 0.9433 - accuracy: 0.9145 - val_loss: 3.5278 - val_accuracy: 0.8153\n",
            "Epoch 17/25\n",
            "95/95 [==============================] - 226s 2s/step - loss: 0.9355 - accuracy: 0.9159 - val_loss: 3.0862 - val_accuracy: 0.8400\n",
            "Epoch 18/25\n",
            "95/95 [==============================] - 212s 2s/step - loss: 0.7813 - accuracy: 0.9243 - val_loss: 2.8748 - val_accuracy: 0.8519\n",
            "Epoch 19/25\n",
            "95/95 [==============================] - 209s 2s/step - loss: 0.8974 - accuracy: 0.9228 - val_loss: 3.0989 - val_accuracy: 0.8528\n",
            "Epoch 20/25\n",
            "95/95 [==============================] - 201s 2s/step - loss: 0.8734 - accuracy: 0.9226 - val_loss: 3.5004 - val_accuracy: 0.8410\n",
            "Epoch 21/25\n",
            "95/95 [==============================] - 200s 2s/step - loss: 1.0353 - accuracy: 0.9211 - val_loss: 3.0149 - val_accuracy: 0.8469\n",
            "Epoch 22/25\n",
            "95/95 [==============================] - 201s 2s/step - loss: 0.8930 - accuracy: 0.9247 - val_loss: 5.0586 - val_accuracy: 0.8247\n",
            "Epoch 23/25\n",
            "95/95 [==============================] - 200s 2s/step - loss: 1.1119 - accuracy: 0.9208 - val_loss: 3.3368 - val_accuracy: 0.8533\n",
            "Epoch 24/25\n",
            "95/95 [==============================] - 202s 2s/step - loss: 0.8270 - accuracy: 0.9290 - val_loss: 3.4910 - val_accuracy: 0.8509\n",
            "Epoch 25/25\n",
            "95/95 [==============================] - 213s 2s/step - loss: 0.8711 - accuracy: 0.9274 - val_loss: 3.8794 - val_accuracy: 0.8435\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "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('vgg16_LossVal_loss')\n",
        "\n",
        "# plot the accuracy\n",
        "plt.plot(r.history['accuracy'], label='train accuracy')\n",
        "plt.plot(r.history['val_accuracy'], label='val accuracy')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "plt.savefig('vgg16_AccVal_acc1.0.jpeg')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 860
        },
        "id": "QAhnajGglzRG",
        "outputId": "793864a8-ef0a-467c-8f75-bba4afd08dc2"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# save it as a h5 file\n",
        "\n",
        "import tensorflow as tf\n",
        "\n",
        "from tensorflow.keras.models import load_model\n",
        "\n",
        "model.save('model_res152V2new.h5')"
      ],
      "metadata": {
        "id": "PIJPfYmoB9Xi"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "y9_Bt4R7Cs02"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}