Transfer Learning ResNet152V2.ipynb

{
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  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "Cotton Disease Classification.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e94A4ItzXkMa",
        "outputId": "3615b507-27c7-4103-ad55-d9fef0e00588"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "!ln -s /content/gdrive/My\\ Drive/ /mydrive\n",
        "!ls /mydrive"
      ],
      "execution_count": 1,
           "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n",
            " 19PW10\n",
            "'19PW10 '\n",
            "'19PW10_ DS.mp4'\n",
            " 19PW10.gdoc\n",
            " 19PW10_OOPS\n",
            "'19PW10 - OS 1.gdoc'\n",
            "'19PW10 - OS 1 - Line chart 1.gsheet'\n",
            " 19PW10.pdf\n",
            " 19PW10_Resume.gdoc\n",
            " 19PW10_Resume.pdf\n",
            " Address.gslides\n",
            "'ALL PAGES.zip'\n",
            "'Basic File and Directory Commands.docx'\n",
            " Broadcast.zip\n",
            "'Cellphone Applications'\n",
            "'Checklist - Shruthi.gsheet'\n",
            "'CN Assignment - IPv6.gdoc'\n",
            " CN__TCP_IP_Lab_scapy_based_prgs.gdoc\n",
            " CN__TCP_IP_Lab_scapy_based_prgs.odt\n",
            "'Code Review by tool - Gomathi.gdoc'\n",
            "'Code walkthrough.mp4'\n",
            "'CO_ GPU.mp4'\n",
            "'Colab Notebooks'\n",
            "'Computer Graphics Video.mp4'\n",
            " contfoot.html\n",
            "'Copy of CN 1.mp4'\n",
            "'Copy of CN 2.mp4'\n",
            "'Copy of CN 3.mp4'\n",
            "'Copy of TeleNDAletterofundertaking (1).gdoc'\n",
            "'Copy of TeleNDAletterofundertaking.gdoc'\n",
            "'Cover letter.gdoc'\n",
            " Datasets\n",
            "'DS PACKAGE'\n",
            " ERD.drawio\n",
            "'Error detection and correction.gdoc'\n",
            "'Exercise-2 Solns.docx'\n",
            "'final idhayathai - Gomathi Kasiviswanathan.mp3'\n",
            "'final idhayathai.mp3'\n",
            "'Final recording azhage - Gomathi Kasiviswanathan.mp3'\n",
            "'Final recording azhage.mp3'\n",
            "'flow diagram.drawio'\n",
            "'General presentation.gslides'\n",
            " GOMATHIF.CPP\n",
            " Gomathi_Resume.gdoc\n",
            "'HOD OOP PPT.gslides'\n",
            " images\n",
            " IMG_20200419_191945.jpg\n",
            " IMG_20200419_192045.jpg\n",
            " IMG_20200419_192129.jpg\n",
            " Linux_Win_Network_Commands_Lab_ss.docx\n",
            "'Manual Code Review - Gomathi.gdoc'\n",
            " Matplotlib.gslides\n",
            " mchr.gdoc\n",
            "'MD Assignment 1.gdoc'\n",
            " Meditation\n",
            "'My Drive'\n",
            "'Ocl Package.zip'\n",
            " OIDv4_ToolKit\n",
            "'OOAD ASSGN - 1.gdoc'\n",
            "'OOAD USE CASE DIAGRAMS .gdoc'\n",
            "'ORAL SWABBING PROTOCOL.gdoc'\n",
            "'ORAL SWAB REVIEW.gdoc'\n",
            "'OR Assignment 1.pdf'\n",
            "'OS assign1.gdoc'\n",
            "'OS Assignment 1 - Solutions.gdoc'\n",
            "'OS Introduction Part II PPT.pptx'\n",
            "'OS Introduction PPT.pptx'\n",
            "'OS LAB WS.gdoc'\n",
            "'OS SYNCHRO & DEADLOCKS.gdoc'\n",
            "'OS Worksheet.docx'\n",
            " package1.c\n",
            "'Package Abstract.docx'\n",
            " package.c\n",
            " PHASE-1_PAPER-1_FINAL_KP.doc\n",
            " PHASE-2_PAPER-2_FINAL_KP.doc\n",
            "'PPT voice over'\n",
            " PROBABILITY.mp4\n",
            "'Product images'\n",
            "'Product images.zip'\n",
            "'Project Wireframes.gslides'\n",
            " ps1_8.R\n",
            "'PS 5.gdoc'\n",
            " ps6_1.m\n",
            "'RATING SYSTEM.zip'\n",
            "'Regular Expressions with grep.docx'\n",
            "'Sample Sound files'\n",
            " Scapy.gdoc\n",
            " Screenrecorder-2020-05-14-21-41-00-734.mp4\n",
            "'Screenshot (23).png'\n",
            " simplewebrtc-messenger.zip\n",
            "'sjx-eram-wok - May 25, 2021.gjam'\n",
            " TeleNDAletterofundertaking.gdoc\n",
            "'Touchless Tech.gslides'\n",
            "'Untitled document (1).gdoc'\n",
            "'Untitled document (2).gdoc'\n",
            "'Untitled document (3).gdoc'\n",
            "'Untitled document (4).gdoc'\n",
            "'Untitled document (5).gdoc'\n",
            "'Untitled document (6).gdoc'\n",
            "'Untitled document.gdoc'\n",
            "'Untitled Jam.gjam'\n",
            "'WDL PACKAGE PPT.gslides'\n",
            "'Web Interactions.gdoc'\n",
            "'Web ppt.mp4'\n",
            " ws8_10.c\n",
            " WS8_10.c\n",
            " ws8_11.c\n",
            " WS8_11.c\n",
            " ws8_12.c\n",
            " WS8_12.c\n",
            " ws8_13.c\n",
            " WS8_13.c\n",
            " ws8_14.c\n",
            " WS8_14.c\n",
            " ws8_15.c\n",
            " WS8_15.c\n",
            " ws8_16.c\n",
            " WS8_16.c\n",
            " ws8_17.c\n",
            " WS8_17.c\n",
            " ws8_1.c\n",
            " WS8_1.c\n",
            " ws8_1.c.gdoc\n",
            " ws8_2.c\n",
            " WS8_2.c\n",
            " ws8_3.c\n",
            " WS8_3.c\n",
            " ws8_4.c\n",
            " WS8_4.c\n",
            " ws8_5.c\n",
            " WS8_5.c\n",
            " ws8_6.c\n",
            " WS8_6.c\n",
            " ws8_7.c\n",
            " WS8_7.c\n",
            " ws8_8.c\n",
            " WS8_8.c\n",
            " ws8_9.c\n",
            " WS8_9.c\n",
            " yolov3\n",
            " yolov4-tiny\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "82UZi40oX3tD"
      },
      "source": [
        "!cp -r '/mydrive/My Drive/Datasets' 'Datasets/'"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "orn7w9KhX3v5"
      },
      "source": [
        "from tensorflow.compat.v1 import ConfigProto\n",
        "from tensorflow.compat.v1 import InteractiveSession\n",
        "\n",
        "config = ConfigProto()\n",
        "config.gpu_options.per_process_gpu_memory_fraction = 0.2\n",
        "config.gpu_options.allow_growth = True\n",
        "session = InteractiveSession(config=config)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mAj_qVj9X3yj"
      },
      "source": [
        "# import the libraries as shown below\n",
        "\n",
        "from tensorflow.keras.layers import Input, Lambda, Dense, Flatten\n",
        "from tensorflow.keras.models import Model\n",
        "#from tensorflow.keras.applications.resnet152V2 import ResNet152V2\n",
        "#from keras.applications.vgg16 import VGG16\n",
        "from tensorflow.keras.applications.inception_v3 import preprocess_input\n",
        "from tensorflow.keras.preprocessing import image\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator,load_img\n",
        "from tensorflow.keras.models import Sequential\n",
        "import numpy as np\n",
        "from glob import glob\n",
        "#import matplotlib.pyplot as plt"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DfoOyQb2X31p"
      },
      "source": [
        "# re-size all the images to this\n",
        "IMAGE_SIZE = [224, 224]\n",
        "\n",
        "train_path = 'Datasets/train'\n",
        "valid_path = 'Datasets/test'"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qoZE0NNwX34d",
        "outputId": "5df799d0-ee74-46ce-a865-dc6741a5c05a"
      },
      "source": [
        "# Import the Vgg 16 library as shown below and add preprocessing layer to the front of VGG\n",
        "# Here we will be using imagenet weights\n",
        "import tensorflow\n",
        "resnet152V2 =tensorflow.keras.applications.ResNet152V2(input_shape=IMAGE_SIZE + [3], weights='imagenet', include_top=False)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet152v2_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "234553344/234545216 [==============================] - 8s 0us/step\n",
            "234561536/234545216 [==============================] - 8s 0us/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JpYtCYBVX368"
      },
      "source": [
        "# don't train existing weights\n",
        "for layer in resnet152V2.layers:\n",
        "    layer.trainable = False"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WZYFXehPX39u"
      },
      "source": [
        "# useful for getting number of output classes\n",
        "folders = glob('Datasets/train/*')"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o_EgZLpKX4AH"
      },
      "source": [
        "# our layers - you can add more if you want\n",
        "x = Flatten()(resnet152V2.output)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-R8xU-1hX4C3"
      },
      "source": [
        "prediction = Dense(len(folders), activation='softmax')(x)\n",
        "\n",
        "# create a model object\n",
        "model = Model(inputs=resnet152V2.input, outputs=prediction)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wtLHyanLX4Fw",
        "outputId": "bf109ae8-1cc4-49cc-95a3-a3b076f1feff"
      },
      "source": [
        "# view the structure of the model\n",
        "model.summary()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "__________________________________________________________________________________________________\n",
            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            "input_1 (InputLayer)            [(None, 224, 224, 3) 0                                            \n",
            "__________________________________________________________________________________________________\n",
            "conv1_pad (ZeroPadding2D)       (None, 230, 230, 3)  0           input_1[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "conv1_conv (Conv2D)             (None, 112, 112, 64) 9472        conv1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "pool1_pad (ZeroPadding2D)       (None, 114, 114, 64) 0           conv1_conv[0][0]                 \n",
            "__________________________________________________________________________________________________\n",
            "pool1_pool (MaxPooling2D)       (None, 56, 56, 64)   0           pool1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_preact_bn (BatchNo (None, 56, 56, 64)   256         pool1_pool[0][0]                 \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_preact_relu (Activ (None, 56, 56, 64)   0           conv2_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_conv (Conv2D)    (None, 56, 56, 64)   4096        conv2_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_relu (Activation (None, 56, 56, 64)   0           conv2_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_relu (Activation (None, 56, 56, 64)   0           conv2_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_0_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_out (Add)          (None, 56, 56, 256)  0           conv2_block1_0_conv[0][0]        \n",
            "                                                                 conv2_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_relu (Activation (None, 56, 56, 64)   0           conv2_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_relu (Activation (None, 56, 56, 64)   0           conv2_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_out (Add)          (None, 56, 56, 256)  0           conv2_block1_out[0][0]           \n",
            "                                                                 conv2_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_relu (Activation (None, 56, 56, 64)   0           conv2_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_conv (Conv2D)    (None, 28, 28, 64)   36864       conv2_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_bn (BatchNormali (None, 28, 28, 64)   256         conv2_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_relu (Activation (None, 28, 28, 64)   0           conv2_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d (MaxPooling2D)    (None, 28, 28, 256)  0           conv2_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_3_conv (Conv2D)    (None, 28, 28, 256)  16640       conv2_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_out (Add)          (None, 28, 28, 256)  0           max_pooling2d[0][0]              \n",
            "                                                                 conv2_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_preact_bn (BatchNo (None, 28, 28, 256)  1024        conv2_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_preact_relu (Activ (None, 28, 28, 256)  0           conv3_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_conv (Conv2D)    (None, 28, 28, 128)  32768       conv3_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_relu (Activation (None, 28, 28, 128)  0           conv3_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_relu (Activation (None, 28, 28, 128)  0           conv3_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_0_conv (Conv2D)    (None, 28, 28, 512)  131584      conv3_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_out (Add)          (None, 28, 28, 512)  0           conv3_block1_0_conv[0][0]        \n",
            "                                                                 conv3_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_relu (Activation (None, 28, 28, 128)  0           conv3_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_relu (Activation (None, 28, 28, 128)  0           conv3_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_out (Add)          (None, 28, 28, 512)  0           conv3_block1_out[0][0]           \n",
            "                                                                 conv3_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_relu (Activation (None, 28, 28, 128)  0           conv3_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_relu (Activation (None, 28, 28, 128)  0           conv3_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_out (Add)          (None, 28, 28, 512)  0           conv3_block2_out[0][0]           \n",
            "                                                                 conv3_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block4_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block4_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block4_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_relu (Activation (None, 28, 28, 128)  0           conv3_block4_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block4_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block4_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block4_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_relu (Activation (None, 28, 28, 128)  0           conv3_block4_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block4_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_out (Add)          (None, 28, 28, 512)  0           conv3_block3_out[0][0]           \n",
            "                                                                 conv3_block4_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block4_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block5_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block5_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block5_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_1_relu (Activation (None, 28, 28, 128)  0           conv3_block5_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block5_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block5_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block5_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_2_relu (Activation (None, 28, 28, 128)  0           conv3_block5_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block5_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block5_out (Add)          (None, 28, 28, 512)  0           conv3_block4_out[0][0]           \n",
            "                                                                 conv3_block5_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block5_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block6_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block6_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block6_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_1_relu (Activation (None, 28, 28, 128)  0           conv3_block6_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block6_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block6_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block6_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_2_relu (Activation (None, 28, 28, 128)  0           conv3_block6_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block6_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block6_out (Add)          (None, 28, 28, 512)  0           conv3_block5_out[0][0]           \n",
            "                                                                 conv3_block6_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block6_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block7_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block7_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block7_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_1_relu (Activation (None, 28, 28, 128)  0           conv3_block7_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block7_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block7_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block7_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_2_relu (Activation (None, 28, 28, 128)  0           conv3_block7_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block7_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block7_out (Add)          (None, 28, 28, 512)  0           conv3_block6_out[0][0]           \n",
            "                                                                 conv3_block7_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block7_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block8_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block8_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block8_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_1_relu (Activation (None, 28, 28, 128)  0           conv3_block8_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block8_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_2_conv (Conv2D)    (None, 14, 14, 128)  147456      conv3_block8_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_2_bn (BatchNormali (None, 14, 14, 128)  512         conv3_block8_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_2_relu (Activation (None, 14, 14, 128)  0           conv3_block8_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_1 (MaxPooling2D)  (None, 14, 14, 512)  0           conv3_block7_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_3_conv (Conv2D)    (None, 14, 14, 512)  66048       conv3_block8_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block8_out (Add)          (None, 14, 14, 512)  0           max_pooling2d_1[0][0]            \n",
            "                                                                 conv3_block8_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_preact_bn (BatchNo (None, 14, 14, 512)  2048        conv3_block8_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_preact_relu (Activ (None, 14, 14, 512)  0           conv4_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_conv (Conv2D)    (None, 14, 14, 256)  131072      conv4_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_relu (Activation (None, 14, 14, 256)  0           conv4_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_relu (Activation (None, 14, 14, 256)  0           conv4_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_0_conv (Conv2D)    (None, 14, 14, 1024) 525312      conv4_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_0_conv[0][0]        \n",
            "                                                                 conv4_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_relu (Activation (None, 14, 14, 256)  0           conv4_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_relu (Activation (None, 14, 14, 256)  0           conv4_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_out[0][0]           \n",
            "                                                                 conv4_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_relu (Activation (None, 14, 14, 256)  0           conv4_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_relu (Activation (None, 14, 14, 256)  0           conv4_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_out (Add)          (None, 14, 14, 1024) 0           conv4_block2_out[0][0]           \n",
            "                                                                 conv4_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block4_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block4_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_relu (Activation (None, 14, 14, 256)  0           conv4_block4_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block4_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block4_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_relu (Activation (None, 14, 14, 256)  0           conv4_block4_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block4_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_out (Add)          (None, 14, 14, 1024) 0           conv4_block3_out[0][0]           \n",
            "                                                                 conv4_block4_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block4_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block5_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block5_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_relu (Activation (None, 14, 14, 256)  0           conv4_block5_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block5_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block5_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_relu (Activation (None, 14, 14, 256)  0           conv4_block5_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block5_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_out (Add)          (None, 14, 14, 1024) 0           conv4_block4_out[0][0]           \n",
            "                                                                 conv4_block5_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block5_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block6_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block6_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block6_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_relu (Activation (None, 14, 14, 256)  0           conv4_block6_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block6_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block6_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block6_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_relu (Activation (None, 14, 14, 256)  0           conv4_block6_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block6_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_out (Add)          (None, 14, 14, 1024) 0           conv4_block5_out[0][0]           \n",
            "                                                                 conv4_block6_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block6_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block7_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block7_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block7_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_1_relu (Activation (None, 14, 14, 256)  0           conv4_block7_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block7_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block7_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block7_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_2_relu (Activation (None, 14, 14, 256)  0           conv4_block7_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block7_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block7_out (Add)          (None, 14, 14, 1024) 0           conv4_block6_out[0][0]           \n",
            "                                                                 conv4_block7_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block7_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block8_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block8_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block8_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_1_relu (Activation (None, 14, 14, 256)  0           conv4_block8_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block8_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block8_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block8_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_2_relu (Activation (None, 14, 14, 256)  0           conv4_block8_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block8_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block8_out (Add)          (None, 14, 14, 1024) 0           conv4_block7_out[0][0]           \n",
            "                                                                 conv4_block8_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block8_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block9_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block9_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block9_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_1_relu (Activation (None, 14, 14, 256)  0           conv4_block9_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block9_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block9_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block9_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_2_relu (Activation (None, 14, 14, 256)  0           conv4_block9_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block9_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block9_out (Add)          (None, 14, 14, 1024) 0           conv4_block8_out[0][0]           \n",
            "                                                                 conv4_block9_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block9_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block10_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block10_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block10_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block10_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block10_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block10_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block10_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block10_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block10_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block10_out (Add)         (None, 14, 14, 1024) 0           conv4_block9_out[0][0]           \n",
            "                                                                 conv4_block10_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block10_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block11_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block11_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block11_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block11_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block11_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block11_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block11_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block11_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block11_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block11_out (Add)         (None, 14, 14, 1024) 0           conv4_block10_out[0][0]          \n",
            "                                                                 conv4_block11_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block11_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block12_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block12_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block12_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block12_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block12_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block12_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block12_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block12_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block12_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block12_out (Add)         (None, 14, 14, 1024) 0           conv4_block11_out[0][0]          \n",
            "                                                                 conv4_block12_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block12_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block13_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block13_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block13_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block13_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block13_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block13_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block13_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block13_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block13_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block13_out (Add)         (None, 14, 14, 1024) 0           conv4_block12_out[0][0]          \n",
            "                                                                 conv4_block13_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block13_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block14_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block14_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block14_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block14_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block14_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block14_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block14_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block14_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block14_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block14_out (Add)         (None, 14, 14, 1024) 0           conv4_block13_out[0][0]          \n",
            "                                                                 conv4_block14_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block14_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block15_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block15_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block15_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block15_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block15_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block15_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block15_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block15_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block15_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block15_out (Add)         (None, 14, 14, 1024) 0           conv4_block14_out[0][0]          \n",
            "                                                                 conv4_block15_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block15_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block16_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block16_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block16_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block16_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block16_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block16_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block16_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block16_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block16_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block16_out (Add)         (None, 14, 14, 1024) 0           conv4_block15_out[0][0]          \n",
            "                                                                 conv4_block16_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block16_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block17_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block17_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block17_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block17_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block17_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block17_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block17_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block17_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block17_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block17_out (Add)         (None, 14, 14, 1024) 0           conv4_block16_out[0][0]          \n",
            "                                                                 conv4_block17_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block17_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block18_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block18_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block18_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block18_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block18_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block18_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block18_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block18_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block18_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block18_out (Add)         (None, 14, 14, 1024) 0           conv4_block17_out[0][0]          \n",
            "                                                                 conv4_block18_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block18_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block19_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block19_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block19_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block19_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block19_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block19_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block19_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block19_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block19_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block19_out (Add)         (None, 14, 14, 1024) 0           conv4_block18_out[0][0]          \n",
            "                                                                 conv4_block19_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block19_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block20_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block20_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block20_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block20_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block20_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block20_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block20_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block20_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block20_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block20_out (Add)         (None, 14, 14, 1024) 0           conv4_block19_out[0][0]          \n",
            "                                                                 conv4_block20_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block20_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block21_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block21_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block21_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block21_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block21_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block21_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block21_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block21_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block21_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block21_out (Add)         (None, 14, 14, 1024) 0           conv4_block20_out[0][0]          \n",
            "                                                                 conv4_block21_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block21_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block22_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block22_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block22_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block22_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block22_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block22_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block22_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block22_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block22_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block22_out (Add)         (None, 14, 14, 1024) 0           conv4_block21_out[0][0]          \n",
            "                                                                 conv4_block22_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block22_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block23_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block23_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block23_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block23_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block23_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block23_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block23_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block23_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block23_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block23_out (Add)         (None, 14, 14, 1024) 0           conv4_block22_out[0][0]          \n",
            "                                                                 conv4_block23_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block23_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block24_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block24_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block24_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block24_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block24_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block24_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block24_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block24_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block24_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block24_out (Add)         (None, 14, 14, 1024) 0           conv4_block23_out[0][0]          \n",
            "                                                                 conv4_block24_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block24_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block25_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block25_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block25_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block25_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block25_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block25_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block25_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block25_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block25_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block25_out (Add)         (None, 14, 14, 1024) 0           conv4_block24_out[0][0]          \n",
            "                                                                 conv4_block25_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block25_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block26_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block26_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block26_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block26_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block26_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block26_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block26_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block26_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block26_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block26_out (Add)         (None, 14, 14, 1024) 0           conv4_block25_out[0][0]          \n",
            "                                                                 conv4_block26_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block26_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block27_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block27_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block27_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block27_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block27_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block27_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block27_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block27_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block27_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block27_out (Add)         (None, 14, 14, 1024) 0           conv4_block26_out[0][0]          \n",
            "                                                                 conv4_block27_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block27_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block28_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block28_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block28_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block28_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block28_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block28_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block28_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block28_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block28_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block28_out (Add)         (None, 14, 14, 1024) 0           conv4_block27_out[0][0]          \n",
            "                                                                 conv4_block28_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block28_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block29_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block29_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block29_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block29_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block29_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block29_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block29_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block29_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block29_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block29_out (Add)         (None, 14, 14, 1024) 0           conv4_block28_out[0][0]          \n",
            "                                                                 conv4_block29_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block29_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block30_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block30_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block30_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block30_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block30_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block30_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block30_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block30_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block30_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block30_out (Add)         (None, 14, 14, 1024) 0           conv4_block29_out[0][0]          \n",
            "                                                                 conv4_block30_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block30_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block31_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block31_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block31_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block31_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block31_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block31_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block31_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block31_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block31_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block31_out (Add)         (None, 14, 14, 1024) 0           conv4_block30_out[0][0]          \n",
            "                                                                 conv4_block31_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block31_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block32_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block32_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block32_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block32_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block32_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block32_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block32_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block32_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block32_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block32_out (Add)         (None, 14, 14, 1024) 0           conv4_block31_out[0][0]          \n",
            "                                                                 conv4_block32_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block32_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block33_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block33_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block33_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block33_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block33_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block33_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block33_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block33_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block33_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block33_out (Add)         (None, 14, 14, 1024) 0           conv4_block32_out[0][0]          \n",
            "                                                                 conv4_block33_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block33_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block34_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block34_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block34_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block34_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block34_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block34_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block34_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block34_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block34_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block34_out (Add)         (None, 14, 14, 1024) 0           conv4_block33_out[0][0]          \n",
            "                                                                 conv4_block34_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block34_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block35_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block35_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block35_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block35_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block35_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_2_conv (Conv2D)   (None, 14, 14, 256)  589824      conv4_block35_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_2_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block35_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_2_relu (Activatio (None, 14, 14, 256)  0           conv4_block35_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_3_conv (Conv2D)   (None, 14, 14, 1024) 263168      conv4_block35_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block35_out (Add)         (None, 14, 14, 1024) 0           conv4_block34_out[0][0]          \n",
            "                                                                 conv4_block35_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_preact_bn (BatchN (None, 14, 14, 1024) 4096        conv4_block35_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_preact_relu (Acti (None, 14, 14, 1024) 0           conv4_block36_preact_bn[0][0]    \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_1_conv (Conv2D)   (None, 14, 14, 256)  262144      conv4_block36_preact_relu[0][0]  \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_1_bn (BatchNormal (None, 14, 14, 256)  1024        conv4_block36_1_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_1_relu (Activatio (None, 14, 14, 256)  0           conv4_block36_1_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_2_pad (ZeroPaddin (None, 16, 16, 256)  0           conv4_block36_1_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_2_conv (Conv2D)   (None, 7, 7, 256)    589824      conv4_block36_2_pad[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_2_bn (BatchNormal (None, 7, 7, 256)    1024        conv4_block36_2_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_2_relu (Activatio (None, 7, 7, 256)    0           conv4_block36_2_bn[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_2 (MaxPooling2D)  (None, 7, 7, 1024)   0           conv4_block35_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_3_conv (Conv2D)   (None, 7, 7, 1024)   263168      conv4_block36_2_relu[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block36_out (Add)         (None, 7, 7, 1024)   0           max_pooling2d_2[0][0]            \n",
            "                                                                 conv4_block36_3_conv[0][0]       \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_preact_bn (BatchNo (None, 7, 7, 1024)   4096        conv4_block36_out[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_preact_relu (Activ (None, 7, 7, 1024)   0           conv5_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_conv (Conv2D)    (None, 7, 7, 512)    524288      conv5_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_relu (Activation (None, 7, 7, 512)    0           conv5_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_relu (Activation (None, 7, 7, 512)    0           conv5_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_0_conv (Conv2D)    (None, 7, 7, 2048)   2099200     conv5_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_0_conv[0][0]        \n",
            "                                                                 conv5_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_relu (Activation (None, 7, 7, 512)    0           conv5_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_relu (Activation (None, 7, 7, 512)    0           conv5_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_out[0][0]           \n",
            "                                                                 conv5_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_relu (Activation (None, 7, 7, 512)    0           conv5_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_relu (Activation (None, 7, 7, 512)    0           conv5_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_out (Add)          (None, 7, 7, 2048)   0           conv5_block2_out[0][0]           \n",
            "                                                                 conv5_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "post_bn (BatchNormalization)    (None, 7, 7, 2048)   8192        conv5_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "post_relu (Activation)          (None, 7, 7, 2048)   0           post_bn[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "flatten (Flatten)               (None, 100352)       0           post_relu[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "dense (Dense)                   (None, 4)            401412      flatten[0][0]                    \n",
            "==================================================================================================\n",
            "Total params: 58,733,060\n",
            "Trainable params: 401,412\n",
            "Non-trainable params: 58,331,648\n",
            "__________________________________________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Q6ToOFVX4IR"
      },
      "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",
        ")"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k3Qns8mrX4LC"
      },
      "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)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sFXPhZpsX4No",
        "outputId": "256eeeab-2fe6-429c-bcec-02fdadf6b64d"
      },
      "source": [
        "# Make sure you provide the same target size as initialied for the image size\n",
        "training_set = train_datagen.flow_from_directory('Datasets/train',\n",
        "                                                 target_size = (224, 224),\n",
        "                                                 batch_size = 32,\n",
        "                                                 class_mode = 'categorical')"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 1952 images belonging to 4 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b6Bu5DfdX4QU",
        "outputId": "725c81f2-b0e7-4fce-93dd-4628432b206b"
      },
      "source": [
        "test_set = test_datagen.flow_from_directory('Datasets/test',\n",
        "                                            target_size = (224, 224),\n",
        "                                            batch_size = 32,\n",
        "                                            class_mode = 'categorical')"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 18 images belonging to 4 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7ea1w4ybX4TZ",
        "outputId": "2c00ce5b-6c78-483d-e7a0-9e093eb0ce2e"
      },
      "source": [
        "# fit the model\n",
        "# Run the cell. It will take some time to execute\n",
        "r = model.fit_generator(\n",
        "  training_set,\n",
        "  validation_data=test_set,\n",
        "  epochs=20,\n",
        "  steps_per_epoch=len(training_set),\n",
        "  validation_steps=len(test_set)\n",
        ")"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py:1972: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
            "  warnings.warn('`Model.fit_generator` is deprecated and '\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/20\n",
            "61/61 [==============================] - 92s 883ms/step - loss: 1.0642 - accuracy: 0.8417 - val_loss: 0.0465 - val_accuracy: 0.9444\n",
            "Epoch 2/20\n",
            "61/61 [==============================] - 49s 795ms/step - loss: 0.7162 - accuracy: 0.9155 - val_loss: 1.8061e-04 - val_accuracy: 1.0000\n",
            "Epoch 3/20\n",
            "61/61 [==============================] - 48s 790ms/step - loss: 0.4135 - accuracy: 0.9401 - val_loss: 0.3916 - val_accuracy: 0.9444\n",
            "Epoch 4/20\n",
            "61/61 [==============================] - 48s 790ms/step - loss: 0.3143 - accuracy: 0.9559 - val_loss: 0.4439 - val_accuracy: 0.9444\n",
            "Epoch 5/20\n",
            "61/61 [==============================] - 48s 790ms/step - loss: 0.2330 - accuracy: 0.9688 - val_loss: 4.0000e-06 - val_accuracy: 1.0000\n",
            "Epoch 6/20\n",
            "61/61 [==============================] - 49s 800ms/step - loss: 0.2241 - accuracy: 0.9667 - val_loss: 0.9722 - val_accuracy: 0.9444\n",
            "Epoch 7/20\n",
            "61/61 [==============================] - 49s 797ms/step - loss: 0.3270 - accuracy: 0.9647 - val_loss: 0.7420 - val_accuracy: 0.9444\n",
            "Epoch 8/20\n",
            "61/61 [==============================] - 49s 791ms/step - loss: 0.1984 - accuracy: 0.9744 - val_loss: 0.2224 - val_accuracy: 0.9444\n",
            "Epoch 9/20\n",
            "61/61 [==============================] - 49s 796ms/step - loss: 0.2552 - accuracy: 0.9672 - val_loss: 2.8020e-04 - val_accuracy: 1.0000\n",
            "Epoch 10/20\n",
            "61/61 [==============================] - 48s 791ms/step - loss: 0.1885 - accuracy: 0.9754 - val_loss: 6.3578e-07 - val_accuracy: 1.0000\n",
            "Epoch 11/20\n",
            "61/61 [==============================] - 49s 791ms/step - loss: 0.1822 - accuracy: 0.9795 - val_loss: 3.9736e-08 - val_accuracy: 1.0000\n",
            "Epoch 12/20\n",
            "61/61 [==============================] - 48s 791ms/step - loss: 0.1582 - accuracy: 0.9775 - val_loss: 0.0000e+00 - val_accuracy: 1.0000\n",
            "Epoch 13/20\n",
            "61/61 [==============================] - 48s 789ms/step - loss: 0.1560 - accuracy: 0.9754 - val_loss: 0.3835 - val_accuracy: 0.9444\n",
            "Epoch 14/20\n",
            "61/61 [==============================] - 49s 797ms/step - loss: 0.2102 - accuracy: 0.9780 - val_loss: 0.2553 - val_accuracy: 0.9444\n",
            "Epoch 15/20\n",
            "61/61 [==============================] - 49s 795ms/step - loss: 0.2086 - accuracy: 0.9810 - val_loss: 0.0584 - val_accuracy: 0.9444\n",
            "Epoch 16/20\n",
            "61/61 [==============================] - 49s 791ms/step - loss: 0.1861 - accuracy: 0.9780 - val_loss: 0.0000e+00 - val_accuracy: 1.0000\n",
            "Epoch 17/20\n",
            "61/61 [==============================] - 48s 786ms/step - loss: 0.1916 - accuracy: 0.9800 - val_loss: 1.8230 - val_accuracy: 0.8889\n",
            "Epoch 18/20\n",
            "61/61 [==============================] - 48s 787ms/step - loss: 0.2311 - accuracy: 0.9790 - val_loss: 6.4902e-07 - val_accuracy: 1.0000\n",
            "Epoch 19/20\n",
            "61/61 [==============================] - 49s 803ms/step - loss: 0.2255 - accuracy: 0.9775 - val_loss: 0.5318 - val_accuracy: 0.8889\n",
            "Epoch 20/20\n",
            "61/61 [==============================] - 49s 799ms/step - loss: 0.2706 - accuracy: 0.9785 - val_loss: 6.5132e-04 - val_accuracy: 1.0000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tyEdq1LOX4WE"
      },
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9f3zDWGCX4Yz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "outputId": "ef0831b2-9817-4859-a3c3-737d04b39dfe"
      },
      "source": [
        "# plot the loss\n",
        "plt.plot(r.history['loss'], label='train loss')\n",
        "plt.plot(r.history['val_loss'], label='val loss')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "plt.savefig('LossVal_loss')\n",
        "\n",
        "# plot the accuracy\n",
        "plt.plot(r.history['accuracy'], label='train acc')\n",
        "plt.plot(r.history['val_accuracy'], label='val acc')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "plt.savefig('AccVal_acc')"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "25yG3pNPX4b4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9eb25a0c-42f4-4331-c9e6-307802d04e7f"
      },
      "source": [
        "# save it as a h5 file\n",
        "\n",
        "from tensorflow.keras.models import load_model\n",
        "\n",
        "model.save('model_resnet152V2.h5')"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py:497: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
            "  category=CustomMaskWarning)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UHqLisq7X4en"
      },
      "source": [
        "y_pred = model.predict(test_set)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lYRuMuLfX4hV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eb387b39-6fd7-4b22-b94f-2f70a905777f"
      },
      "source": [
        "y_pred"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
              "       [7.2130537e-35, 1.0000000e+00, 3.6365067e-22, 1.0021673e-26],\n",
              "       [0.0000000e+00, 9.0385236e-38, 0.0000000e+00, 1.0000000e+00],\n",
              "       [1.8420771e-14, 0.0000000e+00, 1.0000000e+00, 7.6380984e-32],\n",
              "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
              "       [1.8145894e-38, 0.0000000e+00, 1.0000000e+00, 0.0000000e+00],\n",
              "       [0.0000000e+00, 0.0000000e+00, 1.0000000e+00, 0.0000000e+00],\n",
              "       [2.4655063e-30, 1.3106444e-12, 3.5922358e-29, 1.0000000e+00],\n",
              "       [0.0000000e+00, 1.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
              "       [1.0000000e+00, 3.0974743e-33, 2.1702527e-18, 1.4152504e-35],\n",
              "       [9.3051066e-24, 7.5047279e-23, 2.7773035e-15, 1.0000000e+00],\n",
              "       [3.1710393e-22, 2.8301028e-14, 1.1655330e-02, 9.8834467e-01],\n",
              "       [0.0000000e+00, 3.8457672e-38, 1.2338045e-29, 1.0000000e+00],\n",
              "       [2.3719363e-11, 0.0000000e+00, 1.0000000e+00, 2.1352742e-29],\n",
              "       [1.0000000e+00, 0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
              "       [1.8309077e-24, 1.0000000e+00, 1.6713913e-23, 1.0307780e-18],\n",
              "       [1.0000000e+00, 0.0000000e+00, 2.9549962e-35, 0.0000000e+00],\n",
              "       [7.3454537e-26, 6.2677994e-32, 1.0000000e+00, 1.6403184e-26]],\n",
              "      dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qWipybAdX4kT"
      },
      "source": [
        "import numpy as np\n",
        "y_pred = np.argmax(y_pred, axis=1)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9ONp-2UmX4mw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1714ca36-a5c3-4507-c5fc-0e912d9efb7e"
      },
      "source": [
        "y_pred"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 3, 2, 1, 2, 2, 3, 1, 0, 3, 3, 3, 2, 0, 1, 0, 2])"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zmHWKZZxX4p-"
      },
      "source": [
        "from tensorflow.keras.models import load_model\n",
        "from tensorflow.keras.preprocessing import image"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "alGKky9EYtrk"
      },
      "source": [
        "model=load_model('model_resnet152V2.h5')"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VHKOZkEgYul7"
      },
      "source": [
        "img=image.load_img('/content/Datasets/test/diseased cotton leaf/dis_leaf (248).jpg',target_size=(224,224))"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k5W8avXbYvA5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "edd4d986-bcff-4e5f-8252-368bec2d52e2"
      },
      "source": [
        "x=image.img_to_array(img)\n",
        "x"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[213., 180., 135.],\n",
              "        [212., 179., 134.],\n",
              "        [222., 190., 141.],\n",
              "        ...,\n",
              "        [154., 192.,  89.],\n",
              "        [220., 243., 155.],\n",
              "        [229., 250., 171.]],\n",
              "\n",
              "       [[228., 195., 150.],\n",
              "        [229., 196., 151.],\n",
              "        [220., 187., 142.],\n",
              "        ...,\n",
              "        [190., 225., 123.],\n",
              "        [227., 249., 167.],\n",
              "        [230., 251., 172.]],\n",
              "\n",
              "       [[217., 184., 139.],\n",
              "        [221., 189., 140.],\n",
              "        [215., 182., 137.],\n",
              "        ...,\n",
              "        [172., 210.,  99.],\n",
              "        [230., 251., 172.],\n",
              "        [229., 250., 171.]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[ 82., 151.,  62.],\n",
              "        [ 86., 154.,  69.],\n",
              "        [ 87., 155.,  70.],\n",
              "        ...,\n",
              "        [ 72.,  65.,  47.],\n",
              "        [ 79.,  72.,  54.],\n",
              "        [ 79.,  73.,  51.]],\n",
              "\n",
              "       [[ 81., 151.,  65.],\n",
              "        [ 79., 147.,  62.],\n",
              "        [ 80., 148.,  63.],\n",
              "        ...,\n",
              "        [ 79.,  73.,  51.],\n",
              "        [ 77.,  71.,  49.],\n",
              "        [ 70.,  64.,  42.]],\n",
              "\n",
              "       [[ 90., 154.,  70.],\n",
              "        [103., 171.,  86.],\n",
              "        [ 91., 155.,  71.],\n",
              "        ...,\n",
              "        [ 75.,  69.,  47.],\n",
              "        [ 77.,  71.,  49.],\n",
              "        [ 67.,  60.,  42.]]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mjIEuFRfYvW-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2ac68fe3-2d83-420f-bd35-252615ce26b2"
      },
      "source": [
        "x.shape"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(224, 224, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PjvxotECY9Hv"
      },
      "source": [
        "x=x/255"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9_DG3R1SY9eK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3d6e8dbf-bd3f-4f85-b6b5-39af7fecbebd"
      },
      "source": [
        "import numpy as np\n",
        "x=np.expand_dims(x,axis=0)\n",
        "img_data=preprocess_input(x)\n",
        "img_data.shape"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 224, 224, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Q09LAfwZAri",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "54037c88-98f2-4cc3-e28b-aa0e46c6a13e"
      },
      "source": [
        "model.predict(img_data)"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[9.249538e-01, 3.836454e-11, 8.826778e-07, 7.504525e-02]],\n",
              "      dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0x5aWzdAZBEW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "833676d4-d190-4976-ef7c-feb34d3be46f"
      },
      "source": [
        "a=np.argmax(model.predict(img_data), axis=1)\n",
        "a"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0])"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1c94WvqWZBUz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "83690cf5-07a4-4ffe-f988-dc5fecde7c65"
      },
      "source": [
        "if a==0:\n",
        "    a=\"The leaf is diseased cotton leaf\"\n",
        "elif a==1:\n",
        "    a=\"The leaf is diseased cotton plant\"\n",
        "elif a==2:\n",
        "    a=\"The leaf is fresh cotton leaf\"\n",
        "else:\n",
        "    a=\"The leaf is fresh cotton plant\"\n",
        "a"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'The leaf is diseased cotton leaf'"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f0z2qGghA5-q"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}