Transfer_Learning_InceptionV3.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Transfer_Learning_InceptionV3.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yetqnMl0i9c9",
        "outputId": "b1944e91-03bf-4d99-f232-2e32d61cce69"
      },
      "source": [
        "!pwd"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WTT86N9GjJU8",
        "outputId": "4d7d3377-4967-4a7a-a6f4-67d69c23ec8e"
      },
      "source": [
        "#changing the working directory and entering to dataset directory for my google drive\n",
        "%cd drive/MyDrive/kaggle/image_classification/"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/kaggle/image_classification\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z-LYjiZWjLpU",
        "outputId": "0b2af3d6-f137-47c9-f69d-8a45a63ec404"
      },
      "source": [
        "%cd Cotton_Disease/"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/kaggle/image_classification/Cotton_Disease\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pPCyNYXMjNia",
        "outputId": "e9d68544-0f8d-4d34-ce45-fb1d803d94b0"
      },
      "source": [
        "!ls"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "AccVal_acc.png\tLossVal_loss.png  model_rcat_dog.h5  test  train  val\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZV1W8no7jPnk"
      },
      "source": [
        "from keras.layers import Input, Lambda, Dense, Flatten\n",
        "from keras.models import Model\n",
        "from keras.applications.inception_v3 import InceptionV3\n",
        "from keras.applications.inception_v3 import preprocess_input\n",
        "from keras.preprocessing import image\n",
        "from keras.preprocessing.image import ImageDataGenerator\n",
        "from keras.models import Sequential\n",
        "import numpy as np\n",
        "from glob import glob\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IfaeA-z8jchM"
      },
      "source": [
        "# re-size all the images to this\n",
        "IMAGE_SIZE = [224, 224]"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g4hb4DoPjgUr"
      },
      "source": [
        "train_path = 'train'\n",
        "valid_path = 'test'"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IvE_sm56jiJx",
        "outputId": "b9d7b9b1-a478-4175-d269-dbc51bba4925"
      },
      "source": [
        "# add preprocessing layer to the front of InceptionV3\n",
        "inception = InceptionV3(input_shape=IMAGE_SIZE + [3], weights='imagenet', include_top=False)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/inception_v3/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "87916544/87910968 [==============================] - 1s 0us/step\n",
            "87924736/87910968 [==============================] - 1s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CXy1jX80jpW2"
      },
      "source": [
        "# don't train existing weights\n",
        "for layer in inception.layers:\n",
        "  layer.trainable = False"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LD5pE9f0jvbm"
      },
      "source": [
        "# useful for getting number of classes\n",
        "folders = glob('train/*')"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UJcP_MQJjxwD"
      },
      "source": [
        "# our layers - you can add more if you want\n",
        "x = Flatten()(inception.output)\n",
        "# x = Dense(1000, activation='relu')(x)\n",
        "prediction = Dense(len(folders), activation='softmax')(x)"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M4qAcoUtj1x3"
      },
      "source": [
        "# create a model object\n",
        "model = Model(inputs=inception.input, outputs=prediction)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WIji4QUcj6ul",
        "outputId": "7abfcd90-68f5-4fbd-902f-6d5ed73aeb43"
      },
      "source": [
        "# view the structure of the model\n",
        "model.summary()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"model\"\n",
            "__________________________________________________________________________________________________\n",
            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            "input_1 (InputLayer)            [(None, 224, 224, 3) 0                                            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d (Conv2D)                 (None, 111, 111, 32) 864         input_1[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization (BatchNorma (None, 111, 111, 32) 96          conv2d[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "activation (Activation)         (None, 111, 111, 32) 0           batch_normalization[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_1 (Conv2D)               (None, 109, 109, 32) 9216        activation[0][0]                 \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_1 (BatchNor (None, 109, 109, 32) 96          conv2d_1[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_1 (Activation)       (None, 109, 109, 32) 0           batch_normalization_1[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_2 (Conv2D)               (None, 109, 109, 64) 18432       activation_1[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_2 (BatchNor (None, 109, 109, 64) 192         conv2d_2[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_2 (Activation)       (None, 109, 109, 64) 0           batch_normalization_2[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d (MaxPooling2D)    (None, 54, 54, 64)   0           activation_2[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_3 (Conv2D)               (None, 54, 54, 80)   5120        max_pooling2d[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_3 (BatchNor (None, 54, 54, 80)   240         conv2d_3[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_3 (Activation)       (None, 54, 54, 80)   0           batch_normalization_3[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_4 (Conv2D)               (None, 52, 52, 192)  138240      activation_3[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_4 (BatchNor (None, 52, 52, 192)  576         conv2d_4[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_4 (Activation)       (None, 52, 52, 192)  0           batch_normalization_4[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_1 (MaxPooling2D)  (None, 25, 25, 192)  0           activation_4[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_8 (Conv2D)               (None, 25, 25, 64)   12288       max_pooling2d_1[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_8 (BatchNor (None, 25, 25, 64)   192         conv2d_8[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_8 (Activation)       (None, 25, 25, 64)   0           batch_normalization_8[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_6 (Conv2D)               (None, 25, 25, 48)   9216        max_pooling2d_1[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_9 (Conv2D)               (None, 25, 25, 96)   55296       activation_8[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_6 (BatchNor (None, 25, 25, 48)   144         conv2d_6[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_9 (BatchNor (None, 25, 25, 96)   288         conv2d_9[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "activation_6 (Activation)       (None, 25, 25, 48)   0           batch_normalization_6[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "activation_9 (Activation)       (None, 25, 25, 96)   0           batch_normalization_9[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d (AveragePooli (None, 25, 25, 192)  0           max_pooling2d_1[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_5 (Conv2D)               (None, 25, 25, 64)   12288       max_pooling2d_1[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_7 (Conv2D)               (None, 25, 25, 64)   76800       activation_6[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_10 (Conv2D)              (None, 25, 25, 96)   82944       activation_9[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_11 (Conv2D)              (None, 25, 25, 32)   6144        average_pooling2d[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_5 (BatchNor (None, 25, 25, 64)   192         conv2d_5[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_7 (BatchNor (None, 25, 25, 64)   192         conv2d_7[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_10 (BatchNo (None, 25, 25, 96)   288         conv2d_10[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_11 (BatchNo (None, 25, 25, 32)   96          conv2d_11[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_5 (Activation)       (None, 25, 25, 64)   0           batch_normalization_5[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "activation_7 (Activation)       (None, 25, 25, 64)   0           batch_normalization_7[0][0]      \n",
            "__________________________________________________________________________________________________\n",
            "activation_10 (Activation)      (None, 25, 25, 96)   0           batch_normalization_10[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_11 (Activation)      (None, 25, 25, 32)   0           batch_normalization_11[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed0 (Concatenate)            (None, 25, 25, 256)  0           activation_5[0][0]               \n",
            "                                                                 activation_7[0][0]               \n",
            "                                                                 activation_10[0][0]              \n",
            "                                                                 activation_11[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_15 (Conv2D)              (None, 25, 25, 64)   16384       mixed0[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_15 (BatchNo (None, 25, 25, 64)   192         conv2d_15[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_15 (Activation)      (None, 25, 25, 64)   0           batch_normalization_15[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_13 (Conv2D)              (None, 25, 25, 48)   12288       mixed0[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_16 (Conv2D)              (None, 25, 25, 96)   55296       activation_15[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_13 (BatchNo (None, 25, 25, 48)   144         conv2d_13[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_16 (BatchNo (None, 25, 25, 96)   288         conv2d_16[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_13 (Activation)      (None, 25, 25, 48)   0           batch_normalization_13[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_16 (Activation)      (None, 25, 25, 96)   0           batch_normalization_16[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_1 (AveragePoo (None, 25, 25, 256)  0           mixed0[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_12 (Conv2D)              (None, 25, 25, 64)   16384       mixed0[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_14 (Conv2D)              (None, 25, 25, 64)   76800       activation_13[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_17 (Conv2D)              (None, 25, 25, 96)   82944       activation_16[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_18 (Conv2D)              (None, 25, 25, 64)   16384       average_pooling2d_1[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_12 (BatchNo (None, 25, 25, 64)   192         conv2d_12[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_14 (BatchNo (None, 25, 25, 64)   192         conv2d_14[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_17 (BatchNo (None, 25, 25, 96)   288         conv2d_17[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_18 (BatchNo (None, 25, 25, 64)   192         conv2d_18[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_12 (Activation)      (None, 25, 25, 64)   0           batch_normalization_12[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_14 (Activation)      (None, 25, 25, 64)   0           batch_normalization_14[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_17 (Activation)      (None, 25, 25, 96)   0           batch_normalization_17[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_18 (Activation)      (None, 25, 25, 64)   0           batch_normalization_18[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed1 (Concatenate)            (None, 25, 25, 288)  0           activation_12[0][0]              \n",
            "                                                                 activation_14[0][0]              \n",
            "                                                                 activation_17[0][0]              \n",
            "                                                                 activation_18[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_22 (Conv2D)              (None, 25, 25, 64)   18432       mixed1[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_22 (BatchNo (None, 25, 25, 64)   192         conv2d_22[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_22 (Activation)      (None, 25, 25, 64)   0           batch_normalization_22[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_20 (Conv2D)              (None, 25, 25, 48)   13824       mixed1[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_23 (Conv2D)              (None, 25, 25, 96)   55296       activation_22[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_20 (BatchNo (None, 25, 25, 48)   144         conv2d_20[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_23 (BatchNo (None, 25, 25, 96)   288         conv2d_23[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_20 (Activation)      (None, 25, 25, 48)   0           batch_normalization_20[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_23 (Activation)      (None, 25, 25, 96)   0           batch_normalization_23[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_2 (AveragePoo (None, 25, 25, 288)  0           mixed1[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_19 (Conv2D)              (None, 25, 25, 64)   18432       mixed1[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_21 (Conv2D)              (None, 25, 25, 64)   76800       activation_20[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_24 (Conv2D)              (None, 25, 25, 96)   82944       activation_23[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_25 (Conv2D)              (None, 25, 25, 64)   18432       average_pooling2d_2[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_19 (BatchNo (None, 25, 25, 64)   192         conv2d_19[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_21 (BatchNo (None, 25, 25, 64)   192         conv2d_21[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_24 (BatchNo (None, 25, 25, 96)   288         conv2d_24[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_25 (BatchNo (None, 25, 25, 64)   192         conv2d_25[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_19 (Activation)      (None, 25, 25, 64)   0           batch_normalization_19[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_21 (Activation)      (None, 25, 25, 64)   0           batch_normalization_21[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_24 (Activation)      (None, 25, 25, 96)   0           batch_normalization_24[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_25 (Activation)      (None, 25, 25, 64)   0           batch_normalization_25[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed2 (Concatenate)            (None, 25, 25, 288)  0           activation_19[0][0]              \n",
            "                                                                 activation_21[0][0]              \n",
            "                                                                 activation_24[0][0]              \n",
            "                                                                 activation_25[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_27 (Conv2D)              (None, 25, 25, 64)   18432       mixed2[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_27 (BatchNo (None, 25, 25, 64)   192         conv2d_27[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_27 (Activation)      (None, 25, 25, 64)   0           batch_normalization_27[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_28 (Conv2D)              (None, 25, 25, 96)   55296       activation_27[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_28 (BatchNo (None, 25, 25, 96)   288         conv2d_28[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_28 (Activation)      (None, 25, 25, 96)   0           batch_normalization_28[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_26 (Conv2D)              (None, 12, 12, 384)  995328      mixed2[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_29 (Conv2D)              (None, 12, 12, 96)   82944       activation_28[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_26 (BatchNo (None, 12, 12, 384)  1152        conv2d_26[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_29 (BatchNo (None, 12, 12, 96)   288         conv2d_29[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_26 (Activation)      (None, 12, 12, 384)  0           batch_normalization_26[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_29 (Activation)      (None, 12, 12, 96)   0           batch_normalization_29[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_2 (MaxPooling2D)  (None, 12, 12, 288)  0           mixed2[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "mixed3 (Concatenate)            (None, 12, 12, 768)  0           activation_26[0][0]              \n",
            "                                                                 activation_29[0][0]              \n",
            "                                                                 max_pooling2d_2[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_34 (Conv2D)              (None, 12, 12, 128)  98304       mixed3[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_34 (BatchNo (None, 12, 12, 128)  384         conv2d_34[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_34 (Activation)      (None, 12, 12, 128)  0           batch_normalization_34[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_35 (Conv2D)              (None, 12, 12, 128)  114688      activation_34[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_35 (BatchNo (None, 12, 12, 128)  384         conv2d_35[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_35 (Activation)      (None, 12, 12, 128)  0           batch_normalization_35[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_31 (Conv2D)              (None, 12, 12, 128)  98304       mixed3[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_36 (Conv2D)              (None, 12, 12, 128)  114688      activation_35[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_31 (BatchNo (None, 12, 12, 128)  384         conv2d_31[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_36 (BatchNo (None, 12, 12, 128)  384         conv2d_36[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_31 (Activation)      (None, 12, 12, 128)  0           batch_normalization_31[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_36 (Activation)      (None, 12, 12, 128)  0           batch_normalization_36[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_32 (Conv2D)              (None, 12, 12, 128)  114688      activation_31[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_37 (Conv2D)              (None, 12, 12, 128)  114688      activation_36[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_32 (BatchNo (None, 12, 12, 128)  384         conv2d_32[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_37 (BatchNo (None, 12, 12, 128)  384         conv2d_37[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_32 (Activation)      (None, 12, 12, 128)  0           batch_normalization_32[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_37 (Activation)      (None, 12, 12, 128)  0           batch_normalization_37[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_3 (AveragePoo (None, 12, 12, 768)  0           mixed3[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_30 (Conv2D)              (None, 12, 12, 192)  147456      mixed3[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_33 (Conv2D)              (None, 12, 12, 192)  172032      activation_32[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_38 (Conv2D)              (None, 12, 12, 192)  172032      activation_37[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_39 (Conv2D)              (None, 12, 12, 192)  147456      average_pooling2d_3[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_30 (BatchNo (None, 12, 12, 192)  576         conv2d_30[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_33 (BatchNo (None, 12, 12, 192)  576         conv2d_33[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_38 (BatchNo (None, 12, 12, 192)  576         conv2d_38[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_39 (BatchNo (None, 12, 12, 192)  576         conv2d_39[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_30 (Activation)      (None, 12, 12, 192)  0           batch_normalization_30[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_33 (Activation)      (None, 12, 12, 192)  0           batch_normalization_33[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_38 (Activation)      (None, 12, 12, 192)  0           batch_normalization_38[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_39 (Activation)      (None, 12, 12, 192)  0           batch_normalization_39[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed4 (Concatenate)            (None, 12, 12, 768)  0           activation_30[0][0]              \n",
            "                                                                 activation_33[0][0]              \n",
            "                                                                 activation_38[0][0]              \n",
            "                                                                 activation_39[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_44 (Conv2D)              (None, 12, 12, 160)  122880      mixed4[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_44 (BatchNo (None, 12, 12, 160)  480         conv2d_44[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_44 (Activation)      (None, 12, 12, 160)  0           batch_normalization_44[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_45 (Conv2D)              (None, 12, 12, 160)  179200      activation_44[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_45 (BatchNo (None, 12, 12, 160)  480         conv2d_45[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_45 (Activation)      (None, 12, 12, 160)  0           batch_normalization_45[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_41 (Conv2D)              (None, 12, 12, 160)  122880      mixed4[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_46 (Conv2D)              (None, 12, 12, 160)  179200      activation_45[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_41 (BatchNo (None, 12, 12, 160)  480         conv2d_41[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_46 (BatchNo (None, 12, 12, 160)  480         conv2d_46[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_41 (Activation)      (None, 12, 12, 160)  0           batch_normalization_41[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_46 (Activation)      (None, 12, 12, 160)  0           batch_normalization_46[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_42 (Conv2D)              (None, 12, 12, 160)  179200      activation_41[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_47 (Conv2D)              (None, 12, 12, 160)  179200      activation_46[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_42 (BatchNo (None, 12, 12, 160)  480         conv2d_42[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_47 (BatchNo (None, 12, 12, 160)  480         conv2d_47[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_42 (Activation)      (None, 12, 12, 160)  0           batch_normalization_42[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_47 (Activation)      (None, 12, 12, 160)  0           batch_normalization_47[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_4 (AveragePoo (None, 12, 12, 768)  0           mixed4[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_40 (Conv2D)              (None, 12, 12, 192)  147456      mixed4[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_43 (Conv2D)              (None, 12, 12, 192)  215040      activation_42[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_48 (Conv2D)              (None, 12, 12, 192)  215040      activation_47[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_49 (Conv2D)              (None, 12, 12, 192)  147456      average_pooling2d_4[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_40 (BatchNo (None, 12, 12, 192)  576         conv2d_40[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_43 (BatchNo (None, 12, 12, 192)  576         conv2d_43[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_48 (BatchNo (None, 12, 12, 192)  576         conv2d_48[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_49 (BatchNo (None, 12, 12, 192)  576         conv2d_49[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_40 (Activation)      (None, 12, 12, 192)  0           batch_normalization_40[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_43 (Activation)      (None, 12, 12, 192)  0           batch_normalization_43[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_48 (Activation)      (None, 12, 12, 192)  0           batch_normalization_48[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_49 (Activation)      (None, 12, 12, 192)  0           batch_normalization_49[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed5 (Concatenate)            (None, 12, 12, 768)  0           activation_40[0][0]              \n",
            "                                                                 activation_43[0][0]              \n",
            "                                                                 activation_48[0][0]              \n",
            "                                                                 activation_49[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_54 (Conv2D)              (None, 12, 12, 160)  122880      mixed5[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_54 (BatchNo (None, 12, 12, 160)  480         conv2d_54[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_54 (Activation)      (None, 12, 12, 160)  0           batch_normalization_54[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_55 (Conv2D)              (None, 12, 12, 160)  179200      activation_54[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_55 (BatchNo (None, 12, 12, 160)  480         conv2d_55[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_55 (Activation)      (None, 12, 12, 160)  0           batch_normalization_55[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_51 (Conv2D)              (None, 12, 12, 160)  122880      mixed5[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_56 (Conv2D)              (None, 12, 12, 160)  179200      activation_55[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_51 (BatchNo (None, 12, 12, 160)  480         conv2d_51[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_56 (BatchNo (None, 12, 12, 160)  480         conv2d_56[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_51 (Activation)      (None, 12, 12, 160)  0           batch_normalization_51[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_56 (Activation)      (None, 12, 12, 160)  0           batch_normalization_56[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_52 (Conv2D)              (None, 12, 12, 160)  179200      activation_51[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_57 (Conv2D)              (None, 12, 12, 160)  179200      activation_56[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_52 (BatchNo (None, 12, 12, 160)  480         conv2d_52[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_57 (BatchNo (None, 12, 12, 160)  480         conv2d_57[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_52 (Activation)      (None, 12, 12, 160)  0           batch_normalization_52[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_57 (Activation)      (None, 12, 12, 160)  0           batch_normalization_57[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_5 (AveragePoo (None, 12, 12, 768)  0           mixed5[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_50 (Conv2D)              (None, 12, 12, 192)  147456      mixed5[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_53 (Conv2D)              (None, 12, 12, 192)  215040      activation_52[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_58 (Conv2D)              (None, 12, 12, 192)  215040      activation_57[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_59 (Conv2D)              (None, 12, 12, 192)  147456      average_pooling2d_5[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_50 (BatchNo (None, 12, 12, 192)  576         conv2d_50[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_53 (BatchNo (None, 12, 12, 192)  576         conv2d_53[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_58 (BatchNo (None, 12, 12, 192)  576         conv2d_58[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_59 (BatchNo (None, 12, 12, 192)  576         conv2d_59[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_50 (Activation)      (None, 12, 12, 192)  0           batch_normalization_50[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_53 (Activation)      (None, 12, 12, 192)  0           batch_normalization_53[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_58 (Activation)      (None, 12, 12, 192)  0           batch_normalization_58[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_59 (Activation)      (None, 12, 12, 192)  0           batch_normalization_59[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed6 (Concatenate)            (None, 12, 12, 768)  0           activation_50[0][0]              \n",
            "                                                                 activation_53[0][0]              \n",
            "                                                                 activation_58[0][0]              \n",
            "                                                                 activation_59[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_64 (Conv2D)              (None, 12, 12, 192)  147456      mixed6[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_64 (BatchNo (None, 12, 12, 192)  576         conv2d_64[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_64 (Activation)      (None, 12, 12, 192)  0           batch_normalization_64[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_65 (Conv2D)              (None, 12, 12, 192)  258048      activation_64[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_65 (BatchNo (None, 12, 12, 192)  576         conv2d_65[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_65 (Activation)      (None, 12, 12, 192)  0           batch_normalization_65[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_61 (Conv2D)              (None, 12, 12, 192)  147456      mixed6[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_66 (Conv2D)              (None, 12, 12, 192)  258048      activation_65[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_61 (BatchNo (None, 12, 12, 192)  576         conv2d_61[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_66 (BatchNo (None, 12, 12, 192)  576         conv2d_66[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_61 (Activation)      (None, 12, 12, 192)  0           batch_normalization_61[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_66 (Activation)      (None, 12, 12, 192)  0           batch_normalization_66[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_62 (Conv2D)              (None, 12, 12, 192)  258048      activation_61[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_67 (Conv2D)              (None, 12, 12, 192)  258048      activation_66[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_62 (BatchNo (None, 12, 12, 192)  576         conv2d_62[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_67 (BatchNo (None, 12, 12, 192)  576         conv2d_67[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_62 (Activation)      (None, 12, 12, 192)  0           batch_normalization_62[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_67 (Activation)      (None, 12, 12, 192)  0           batch_normalization_67[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_6 (AveragePoo (None, 12, 12, 768)  0           mixed6[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_60 (Conv2D)              (None, 12, 12, 192)  147456      mixed6[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_63 (Conv2D)              (None, 12, 12, 192)  258048      activation_62[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_68 (Conv2D)              (None, 12, 12, 192)  258048      activation_67[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_69 (Conv2D)              (None, 12, 12, 192)  147456      average_pooling2d_6[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_60 (BatchNo (None, 12, 12, 192)  576         conv2d_60[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_63 (BatchNo (None, 12, 12, 192)  576         conv2d_63[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_68 (BatchNo (None, 12, 12, 192)  576         conv2d_68[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_69 (BatchNo (None, 12, 12, 192)  576         conv2d_69[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_60 (Activation)      (None, 12, 12, 192)  0           batch_normalization_60[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_63 (Activation)      (None, 12, 12, 192)  0           batch_normalization_63[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_68 (Activation)      (None, 12, 12, 192)  0           batch_normalization_68[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_69 (Activation)      (None, 12, 12, 192)  0           batch_normalization_69[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed7 (Concatenate)            (None, 12, 12, 768)  0           activation_60[0][0]              \n",
            "                                                                 activation_63[0][0]              \n",
            "                                                                 activation_68[0][0]              \n",
            "                                                                 activation_69[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_72 (Conv2D)              (None, 12, 12, 192)  147456      mixed7[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_72 (BatchNo (None, 12, 12, 192)  576         conv2d_72[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_72 (Activation)      (None, 12, 12, 192)  0           batch_normalization_72[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_73 (Conv2D)              (None, 12, 12, 192)  258048      activation_72[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_73 (BatchNo (None, 12, 12, 192)  576         conv2d_73[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_73 (Activation)      (None, 12, 12, 192)  0           batch_normalization_73[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_70 (Conv2D)              (None, 12, 12, 192)  147456      mixed7[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_74 (Conv2D)              (None, 12, 12, 192)  258048      activation_73[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_70 (BatchNo (None, 12, 12, 192)  576         conv2d_70[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_74 (BatchNo (None, 12, 12, 192)  576         conv2d_74[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_70 (Activation)      (None, 12, 12, 192)  0           batch_normalization_70[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_74 (Activation)      (None, 12, 12, 192)  0           batch_normalization_74[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_71 (Conv2D)              (None, 5, 5, 320)    552960      activation_70[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_75 (Conv2D)              (None, 5, 5, 192)    331776      activation_74[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_71 (BatchNo (None, 5, 5, 320)    960         conv2d_71[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_75 (BatchNo (None, 5, 5, 192)    576         conv2d_75[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_71 (Activation)      (None, 5, 5, 320)    0           batch_normalization_71[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_75 (Activation)      (None, 5, 5, 192)    0           batch_normalization_75[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_3 (MaxPooling2D)  (None, 5, 5, 768)    0           mixed7[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "mixed8 (Concatenate)            (None, 5, 5, 1280)   0           activation_71[0][0]              \n",
            "                                                                 activation_75[0][0]              \n",
            "                                                                 max_pooling2d_3[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_80 (Conv2D)              (None, 5, 5, 448)    573440      mixed8[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_80 (BatchNo (None, 5, 5, 448)    1344        conv2d_80[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_80 (Activation)      (None, 5, 5, 448)    0           batch_normalization_80[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_77 (Conv2D)              (None, 5, 5, 384)    491520      mixed8[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_81 (Conv2D)              (None, 5, 5, 384)    1548288     activation_80[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_77 (BatchNo (None, 5, 5, 384)    1152        conv2d_77[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_81 (BatchNo (None, 5, 5, 384)    1152        conv2d_81[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_77 (Activation)      (None, 5, 5, 384)    0           batch_normalization_77[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_81 (Activation)      (None, 5, 5, 384)    0           batch_normalization_81[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_78 (Conv2D)              (None, 5, 5, 384)    442368      activation_77[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_79 (Conv2D)              (None, 5, 5, 384)    442368      activation_77[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_82 (Conv2D)              (None, 5, 5, 384)    442368      activation_81[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_83 (Conv2D)              (None, 5, 5, 384)    442368      activation_81[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_7 (AveragePoo (None, 5, 5, 1280)   0           mixed8[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_76 (Conv2D)              (None, 5, 5, 320)    409600      mixed8[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_78 (BatchNo (None, 5, 5, 384)    1152        conv2d_78[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_79 (BatchNo (None, 5, 5, 384)    1152        conv2d_79[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_82 (BatchNo (None, 5, 5, 384)    1152        conv2d_82[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_83 (BatchNo (None, 5, 5, 384)    1152        conv2d_83[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_84 (Conv2D)              (None, 5, 5, 192)    245760      average_pooling2d_7[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_76 (BatchNo (None, 5, 5, 320)    960         conv2d_76[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_78 (Activation)      (None, 5, 5, 384)    0           batch_normalization_78[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_79 (Activation)      (None, 5, 5, 384)    0           batch_normalization_79[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_82 (Activation)      (None, 5, 5, 384)    0           batch_normalization_82[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_83 (Activation)      (None, 5, 5, 384)    0           batch_normalization_83[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_84 (BatchNo (None, 5, 5, 192)    576         conv2d_84[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_76 (Activation)      (None, 5, 5, 320)    0           batch_normalization_76[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed9_0 (Concatenate)          (None, 5, 5, 768)    0           activation_78[0][0]              \n",
            "                                                                 activation_79[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "concatenate (Concatenate)       (None, 5, 5, 768)    0           activation_82[0][0]              \n",
            "                                                                 activation_83[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "activation_84 (Activation)      (None, 5, 5, 192)    0           batch_normalization_84[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed9 (Concatenate)            (None, 5, 5, 2048)   0           activation_76[0][0]              \n",
            "                                                                 mixed9_0[0][0]                   \n",
            "                                                                 concatenate[0][0]                \n",
            "                                                                 activation_84[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_89 (Conv2D)              (None, 5, 5, 448)    917504      mixed9[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_89 (BatchNo (None, 5, 5, 448)    1344        conv2d_89[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_89 (Activation)      (None, 5, 5, 448)    0           batch_normalization_89[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_86 (Conv2D)              (None, 5, 5, 384)    786432      mixed9[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_90 (Conv2D)              (None, 5, 5, 384)    1548288     activation_89[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_86 (BatchNo (None, 5, 5, 384)    1152        conv2d_86[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_90 (BatchNo (None, 5, 5, 384)    1152        conv2d_90[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_86 (Activation)      (None, 5, 5, 384)    0           batch_normalization_86[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_90 (Activation)      (None, 5, 5, 384)    0           batch_normalization_90[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_87 (Conv2D)              (None, 5, 5, 384)    442368      activation_86[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_88 (Conv2D)              (None, 5, 5, 384)    442368      activation_86[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_91 (Conv2D)              (None, 5, 5, 384)    442368      activation_90[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_92 (Conv2D)              (None, 5, 5, 384)    442368      activation_90[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "average_pooling2d_8 (AveragePoo (None, 5, 5, 2048)   0           mixed9[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_85 (Conv2D)              (None, 5, 5, 320)    655360      mixed9[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_87 (BatchNo (None, 5, 5, 384)    1152        conv2d_87[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_88 (BatchNo (None, 5, 5, 384)    1152        conv2d_88[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_91 (BatchNo (None, 5, 5, 384)    1152        conv2d_91[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_92 (BatchNo (None, 5, 5, 384)    1152        conv2d_92[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "conv2d_93 (Conv2D)              (None, 5, 5, 192)    393216      average_pooling2d_8[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_85 (BatchNo (None, 5, 5, 320)    960         conv2d_85[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_87 (Activation)      (None, 5, 5, 384)    0           batch_normalization_87[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_88 (Activation)      (None, 5, 5, 384)    0           batch_normalization_88[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_91 (Activation)      (None, 5, 5, 384)    0           batch_normalization_91[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "activation_92 (Activation)      (None, 5, 5, 384)    0           batch_normalization_92[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "batch_normalization_93 (BatchNo (None, 5, 5, 192)    576         conv2d_93[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "activation_85 (Activation)      (None, 5, 5, 320)    0           batch_normalization_85[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed9_1 (Concatenate)          (None, 5, 5, 768)    0           activation_87[0][0]              \n",
            "                                                                 activation_88[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "concatenate_1 (Concatenate)     (None, 5, 5, 768)    0           activation_91[0][0]              \n",
            "                                                                 activation_92[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "activation_93 (Activation)      (None, 5, 5, 192)    0           batch_normalization_93[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "mixed10 (Concatenate)           (None, 5, 5, 2048)   0           activation_85[0][0]              \n",
            "                                                                 mixed9_1[0][0]                   \n",
            "                                                                 concatenate_1[0][0]              \n",
            "                                                                 activation_93[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "flatten (Flatten)               (None, 51200)        0           mixed10[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "dense (Dense)                   (None, 4)            204804      flatten[0][0]                    \n",
            "==================================================================================================\n",
            "Total params: 22,007,588\n",
            "Trainable params: 204,804\n",
            "Non-trainable params: 21,802,784\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xKM_0f0aj9p6"
      },
      "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": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g1-bkfMjkCHL"
      },
      "source": [
        "from 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": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e7JE8o06kFID",
        "outputId": "de6ea24b-5b7f-4d0f-9448-0b2d7e78a254"
      },
      "source": [
        "training_set = train_datagen.flow_from_directory('train',\n",
        "                                                 target_size = (224, 224),\n",
        "                                                 batch_size = 64,\n",
        "                                                 class_mode = 'categorical')"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 1951 images belonging to 4 classes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZWUWDRtskHuY",
        "outputId": "750cc1f4-552e-4dbf-8c08-62a334bf0004"
      },
      "source": [
        "test_set = test_datagen.flow_from_directory('test',\n",
        "                                            target_size = (224, 224),\n",
        "                                            batch_size = 64,\n",
        "                                            class_mode = 'categorical')"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 106 images belonging to 4 classes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8ALYCaMlkLFG",
        "outputId": "eb7f2a19-6d10-4b91-f7b0-c7390ecf7a13"
      },
      "source": [
        "# fit the model\n",
        "r = model.fit_generator(\n",
        "  training_set,\n",
        "  validation_data=test_set,\n",
        "  epochs=4,\n",
        "  steps_per_epoch=len(training_set),\n",
        "  validation_steps=len(test_set)\n",
        ")"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "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"
          ]
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/4\n",
            "31/31 [==============================] - 1164s 36s/step - loss: 3.6552 - accuracy: 0.6586 - val_loss: 0.9464 - val_accuracy: 0.8019\n",
            "Epoch 2/4\n",
            "31/31 [==============================] - 42s 1s/step - loss: 0.6198 - accuracy: 0.8852 - val_loss: 0.4086 - val_accuracy: 0.9057\n",
            "Epoch 3/4\n",
            "31/31 [==============================] - 42s 1s/step - loss: 0.3085 - accuracy: 0.9247 - val_loss: 0.2137 - val_accuracy: 0.9340\n",
            "Epoch 4/4\n",
            "31/31 [==============================] - 41s 1s/step - loss: 0.2613 - accuracy: 0.9354 - val_loss: 0.3822 - val_accuracy: 0.8962\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "BulkdPsLkOBW",
        "outputId": "7644a469-a53d-40d2-8ccb-ac4f8c21b9b6"
      },
      "source": [
        "# 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')"
      ],
      "execution_count": 19,
      "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": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "bG-pvWHZkRPZ",
        "outputId": "30f657a7-9674-461f-dc11-397f0f3ae5d1"
      },
      "source": [
        "# accuracies\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": 20,
      "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": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lfu6Q212kT-R"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}