ResNet50.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ResNet50.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "G_KEXq52JAJY",
        "colab_type": "code",
        "outputId": "deb6b7a6-f8ac-45e8-afa3-84e7f0d8f1cf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "ae008a82-ea76-4eb3-cef1-24e69b6ae24c",
        "id": "zATkntP6AoXE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "\n",
        "\n",
        "#\n",
        "# **************************************************************************************************************************************************\n",
        "#\tLibraries\n",
        "# **************************************************************************************************************************************************\n",
        "#\n",
        "\n",
        "from keras import optimizers\n",
        "from keras import applications\n",
        "from keras.models import Model\n",
        "from keras.layers import Flatten, Dense\n",
        "from keras.preprocessing.image import ImageDataGenerator\n",
        "from keras.utils.np_utils import to_categorical\n",
        "from keras.callbacks import EarlyStopping, ModelCheckpoint\n",
        "from math import ceil\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import datetime\n",
        "import json\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "#\n",
        "# **************************************************************************************************************************************************\n",
        "#\tGlobal Variables\n",
        "# **************************************************************************************************************************************************\n",
        "#\n",
        "\n",
        "# dimensions of architecture\n",
        "img_width, img_height = 224, 224\n",
        "\n",
        "# saved filename of model\n",
        "model_filename = '/content/drive/My Drive/Colab Notebooks/model.h5'\n",
        "\n",
        "# saved filename of model weights\n",
        "weights_filename = '/content/drive/My Drive/Colab Notebooks/weights.h5'\n",
        "modelcheckpoint_filename = '/content/drive/My Drive/Colab Notebooks/model_checkpoint.h5'\n",
        "\n",
        "# savae filename of results csv\n",
        "results_filename = '/content/drive/My Drive/Colab Notebooks/results.csv'\n",
        "\n",
        "# datasets' directories\n",
        "train_data_dir = '/content/drive/My Drive/Colab Notebooks/train/'\n",
        "# validation_data_dir = '/content/drive/My Drive/Colab Notebooks/validation/'\n",
        "test_data_dir = '/content/drive/My Drive/Colab Notebooks/test/'\n",
        "\n",
        "# number of channels for the architecture\n",
        "channels = 3\n",
        "\n",
        "# number of epochs\n",
        "epochs = 500\n",
        "\n",
        "# batch size \n",
        "train_batch_size = 2\n",
        "validation_batch_size = 2\n",
        "\n",
        "# learning rate\n",
        "learning_rate = 0.0001\n",
        "\n",
        "# class mode\n",
        "class_mode = 'categorical'\n",
        "\n",
        "# total number of classes\n",
        "total_classes = 2\n",
        "\n",
        "#\n",
        "# **************************************************************************************************************************************************\n",
        "#\tFunctions\n",
        "# **************************************************************************************************************************************************\n",
        "#\n",
        "def summary():\n",
        "\t# model summary\n",
        "\tresnet50.summary()\n",
        "\n",
        "\t# graphing our training and validation\n",
        "\tacc = history.history['acc']\n",
        "\tval_acc = history.history['val_acc']\n",
        "\tloss = history.history['loss']\n",
        "\tval_loss = history.history['val_loss']\n",
        "\tepochs = range(len(acc))\n",
        "\tplt.plot(epochs, acc, 'r', label='Training Acc')\n",
        "\tplt.plot(epochs, val_acc, 'b', label='Validation Acc')\n",
        "\tplt.title('Training and Validation Accuracy')\n",
        "\tplt.ylabel('Accuracy')\n",
        "\tplt.xlabel('Epoch')\n",
        "\tplt.legend()\n",
        "\tplt.figure()\n",
        "\tplt.plot(epochs, loss, 'r', label='Training Loss')\n",
        "\tplt.plot(epochs, val_loss, 'b', label='Validation Loss')\n",
        "\tplt.title('Training and Validation Loss')\n",
        "\tplt.ylabel('loss')\n",
        "\tplt.xlabel('Epoch')\n",
        "\tplt.legend()\n",
        "\tplt.show()\n",
        " \n",
        "def saveModel():\n",
        "  model.save(model_filename)\n",
        "  model.save_weights(weights_filename)\n",
        "\n",
        "  model_json = model.to_json()\n",
        "  with open(\"model_in_json.json\",\"w\") as json_file:\n",
        "    json.dump(model_json, json_file)\n",
        "\n",
        "\n",
        "#\n",
        "# **************************************************************************************************************************************************\n",
        "#\tMain Code\n",
        "# **************************************************************************************************************************************************\n",
        "#\n",
        "\n",
        "# loading resnet50 model\n",
        "model = applications.ResNet50(include_top = False, weights = 'imagenet', classes = total_classes, input_shape=(img_width, img_height, channels))\n",
        "flat = Flatten()(model.layers[-1].output)\n",
        "output = Dense(total_classes, activation='softmax')(flat)\n",
        "resnet50 = Model(input=model.inputs,outputs = output)\n",
        "\n",
        "train_datagen = ImageDataGenerator(rescale = 1. / 255,\n",
        "                                    rotation_range = 90,\n",
        "                                    brightness_range = [0.2, 1.0],\n",
        "                                    shear_range = 0.2,\n",
        "                                    zoom_range = 0.3,\n",
        "                                    width_shift_range = 1.0,\n",
        "                                    height_shift_range = 1.0,\n",
        "                                    horizontal_flip = True,\n",
        "                                    vertical_flip = True,\n",
        "                                    validation_split = 0.4)\n",
        "\n",
        "validation_datagen = ImageDataGenerator(rescale=1. / 255)\n",
        "\n",
        "# current time\n",
        "start = datetime.datetime.now()\n",
        "\n",
        "training_set = train_datagen.flow_from_directory(\n",
        "                                \t\ttrain_data_dir,\n",
        "                                \t\ttarget_size = (img_width, img_height),\n",
        "                                \t\tbatch_size = train_batch_size,\n",
        "                                \t\tclass_mode=class_mode,\n",
        "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsubset = \"training\",\n",
        "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tseed = 42,\n",
        "                                \t\tshuffle = True)\n",
        "\n",
        "nb_train_samples = len(training_set.filenames)\n",
        "\n",
        "# validation data\n",
        "validation_set = train_datagen.flow_from_directory(\n",
        "                                  \t\ttrain_data_dir,\n",
        "                                  \t\ttarget_size=(img_width, img_height),\n",
        "                                  \t\tbatch_size=validation_batch_size,\n",
        "                                  \t\tclass_mode=class_mode,\n",
        "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsubset = \"validation\",\n",
        "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tseed = 42,\n",
        "                                  \t\tshuffle=True)\n",
        "\n",
        "nb_validation_samples = len(validation_set.filenames)\n",
        "\n",
        "resnet50.compile(loss = 'categorical_crossentropy',\n",
        "                 optimizer = optimizers.Adam(lr = learning_rate),\n",
        "                 metrics = ['acc'])\n",
        "\n",
        "es = EarlyStopping(monitor = 'val_loss',\n",
        "                    min_delta = 1e-5,\n",
        "                    patience = 5,\n",
        "                    verbose = 1,\n",
        "                    mode = 'min',\n",
        "                    restore_best_weights = True)\n",
        "\n",
        "mc = ModelCheckpoint(modelcheckpoint_filename,\n",
        "                        monitor = 'val_loss',\n",
        "                        mode = 'min',\n",
        "                        save_weights_only = True,\n",
        "                        save_best_only = True)\n",
        "\n",
        "history = resnet50.fit_generator(training_set,\n",
        "                         steps_per_epoch = nb_train_samples / train_batch_size,\n",
        "                         epochs = epochs,\n",
        "\t\t\t\t\t\t\t\t\t\t\t\t callbacks = [es,mc],\n",
        "                         validation_data = validation_set,\n",
        "                         validation_steps = nb_validation_samples / validation_batch_size)\n",
        "\n",
        "summary()\n",
        "saveModel()\n",
        "\n",
        "(eval_loss, eval_accuracy) = resnet50.evaluate_generator(\n",
        " validation_set, steps = nb_validation_samples, verbose = 1)\n",
        "\n",
        "print(\"[INFO] Accuracy: {:.2f}%\".format(eval_accuracy * 100))\n",
        "print(\"[INFO] Loss: {}\".format(eval_loss))\n",
        "end = datetime.datetime.now()\n",
        "elapsed = end - start\n",
        "print('[INFO] Time Elapsed: ', elapsed)\n",
        "\n",
        "# # test data\n",
        "# test_datagen = ImageDataGenerator()\n",
        "# test_set = test_datagen.flow_from_directory(\n",
        "#                                   \t\ttest_data_dir,\n",
        "#                                   \t\ttarget_size = (img_width, img_height),\n",
        "#                                   \t\tbatch_size = 1,\n",
        "#                                   \t\tclass_mode = class_mode,\n",
        "# \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tseed = 42,\n",
        "#                                   \t\tshuffle = True)\n",
        "\n",
        "# step_size_test = test_set.n // test_set.batch_size\n",
        "# test_set.reset()\n",
        "\n",
        "# pred = resnet50.predict_generator(test_set,\n",
        "#                                 steps = step_size_test,\n",
        "#                                 verbose = 1)\n",
        "\n",
        "# predicted_class_indices = np.argmax(pred, axis = 1)\n",
        "# labels = (test_set.class_indices)\n",
        "\n",
        "# labels = dict((v, k) for k, v in labels.items())\n",
        "# predictions = [labels[k] for k in predicted_class_indices]\n",
        "\n",
        "# filenames = test_set.filenames\n",
        "# results = pd.DataFrame({\"Filename\": filenames,\n",
        "#                       \"Prediction\": predictions})\n",
        "# results.to_csv(results_filename, index = False)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/keras_applications/resnet50.py:265: UserWarning: The output shape of `ResNet50(include_top=False)` has been changed since Keras 2.2.0.\n",
            "  warnings.warn('The output shape of `ResNet50(include_top=False)` '\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:109: UserWarning: Update your `Model` call to the Keras 2 API: `Model(outputs=Tensor(\"de..., inputs=[<tf.Tenso...)`\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Found 352 images belonging to 2 classes.\n",
            "Found 232 images belonging to 2 classes.\n",
            "Epoch 1/500\n",
            "176/176 [==============================] - 41s 235ms/step - loss: 2.5250 - acc: 0.5540 - val_loss: 3.9016 - val_acc: 0.5690\n",
            "Epoch 2/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 3.4782 - acc: 0.5341 - val_loss: 2.7676 - val_acc: 0.5302\n",
            "Epoch 3/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 2.6748 - acc: 0.6108 - val_loss: 4.4566 - val_acc: 0.5086\n",
            "Epoch 4/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 1.7771 - acc: 0.5881 - val_loss: 3.1346 - val_acc: 0.4914\n",
            "Epoch 5/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 1.3155 - acc: 0.6080 - val_loss: 2.4457 - val_acc: 0.5043\n",
            "Epoch 6/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 1.0929 - acc: 0.6648 - val_loss: 2.6192 - val_acc: 0.5043\n",
            "Epoch 7/500\n",
            "176/176 [==============================] - 19s 107ms/step - loss: 1.0811 - acc: 0.6222 - val_loss: 1.4988 - val_acc: 0.5733\n",
            "Epoch 8/500\n",
            "176/176 [==============================] - 19s 109ms/step - loss: 0.9497 - acc: 0.6847 - val_loss: 1.4626 - val_acc: 0.5388\n",
            "Epoch 9/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 0.9010 - acc: 0.6477 - val_loss: 1.8927 - val_acc: 0.5690\n",
            "Epoch 10/500\n",
            "176/176 [==============================] - 19s 107ms/step - loss: 0.7139 - acc: 0.6875 - val_loss: 1.0608 - val_acc: 0.5690\n",
            "Epoch 11/500\n",
            "176/176 [==============================] - 19s 107ms/step - loss: 0.7932 - acc: 0.6875 - val_loss: 1.4463 - val_acc: 0.5560\n",
            "Epoch 12/500\n",
            "176/176 [==============================] - 19s 107ms/step - loss: 0.8439 - acc: 0.6648 - val_loss: 2.1244 - val_acc: 0.4871\n",
            "Epoch 13/500\n",
            "176/176 [==============================] - 19s 107ms/step - loss: 0.7154 - acc: 0.7159 - val_loss: 0.9495 - val_acc: 0.6207\n",
            "Epoch 14/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 0.6620 - acc: 0.7472 - val_loss: 1.4555 - val_acc: 0.5431\n",
            "Epoch 15/500\n",
            "176/176 [==============================] - 19s 106ms/step - loss: 0.8107 - acc: 0.6761 - val_loss: 1.2120 - val_acc: 0.5560\n",
            "Epoch 16/500\n",
            "176/176 [==============================] - 19s 108ms/step - loss: 0.7560 - acc: 0.6847 - val_loss: 1.4305 - val_acc: 0.5259\n",
            "Epoch 17/500\n",
            "176/176 [==============================] - 19s 106ms/step - loss: 0.5746 - acc: 0.7443 - val_loss: 1.6269 - val_acc: 0.5517\n",
            "Epoch 18/500\n",
            "176/176 [==============================] - 19s 106ms/step - loss: 0.6694 - acc: 0.7188 - val_loss: 1.3834 - val_acc: 0.5905\n",
            "Restoring model weights from the end of the best epoch\n",
            "Epoch 00018: early stopping\n",
            "Model: \"model_5\"\n",
            "__________________________________________________________________________________________________\n",
            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            "input_5 (InputLayer)            (None, 224, 224, 3)  0                                            \n",
            "__________________________________________________________________________________________________\n",
            "conv1_pad (ZeroPadding2D)       (None, 230, 230, 3)  0           input_5[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "conv1 (Conv2D)                  (None, 112, 112, 64) 9472        conv1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "bn_conv1 (BatchNormalization)   (None, 112, 112, 64) 256         conv1[0][0]                      \n",
            "__________________________________________________________________________________________________\n",
            "activation_197 (Activation)     (None, 112, 112, 64) 0           bn_conv1[0][0]                   \n",
            "__________________________________________________________________________________________________\n",
            "pool1_pad (ZeroPadding2D)       (None, 114, 114, 64) 0           activation_197[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_5 (MaxPooling2D)  (None, 56, 56, 64)   0           pool1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "res2a_branch2a (Conv2D)         (None, 56, 56, 64)   4160        max_pooling2d_5[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "bn2a_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2a_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_198 (Activation)     (None, 56, 56, 64)   0           bn2a_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2a_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_198[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2a_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2a_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_199 (Activation)     (None, 56, 56, 64)   0           bn2a_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2a_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_199[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "res2a_branch1 (Conv2D)          (None, 56, 56, 256)  16640       max_pooling2d_5[0][0]            \n",
            "__________________________________________________________________________________________________\n",
            "bn2a_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2a_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2a_branch1 (BatchNormalizatio (None, 56, 56, 256)  1024        res2a_branch1[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "add_65 (Add)                    (None, 56, 56, 256)  0           bn2a_branch2c[0][0]              \n",
            "                                                                 bn2a_branch1[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "activation_200 (Activation)     (None, 56, 56, 256)  0           add_65[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res2b_branch2a (Conv2D)         (None, 56, 56, 64)   16448       activation_200[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2b_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2b_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_201 (Activation)     (None, 56, 56, 64)   0           bn2b_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2b_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_201[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2b_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2b_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_202 (Activation)     (None, 56, 56, 64)   0           bn2b_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2b_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_202[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2b_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2b_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_66 (Add)                    (None, 56, 56, 256)  0           bn2b_branch2c[0][0]              \n",
            "                                                                 activation_200[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_203 (Activation)     (None, 56, 56, 256)  0           add_66[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res2c_branch2a (Conv2D)         (None, 56, 56, 64)   16448       activation_203[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2c_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2c_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_204 (Activation)     (None, 56, 56, 64)   0           bn2c_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2c_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_204[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2c_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2c_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_205 (Activation)     (None, 56, 56, 64)   0           bn2c_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res2c_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_205[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn2c_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2c_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_67 (Add)                    (None, 56, 56, 256)  0           bn2c_branch2c[0][0]              \n",
            "                                                                 activation_203[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_206 (Activation)     (None, 56, 56, 256)  0           add_67[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res3a_branch2a (Conv2D)         (None, 28, 28, 128)  32896       activation_206[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3a_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_207 (Activation)     (None, 28, 28, 128)  0           bn3a_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3a_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_207[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3a_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_208 (Activation)     (None, 28, 28, 128)  0           bn3a_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3a_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_208[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "res3a_branch1 (Conv2D)          (None, 28, 28, 512)  131584      activation_206[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3a_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3a_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3a_branch1 (BatchNormalizatio (None, 28, 28, 512)  2048        res3a_branch1[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "add_68 (Add)                    (None, 28, 28, 512)  0           bn3a_branch2c[0][0]              \n",
            "                                                                 bn3a_branch1[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "activation_209 (Activation)     (None, 28, 28, 512)  0           add_68[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res3b_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_209[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3b_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_210 (Activation)     (None, 28, 28, 128)  0           bn3b_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3b_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_210[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3b_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_211 (Activation)     (None, 28, 28, 128)  0           bn3b_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3b_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_211[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3b_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3b_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_69 (Add)                    (None, 28, 28, 512)  0           bn3b_branch2c[0][0]              \n",
            "                                                                 activation_209[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_212 (Activation)     (None, 28, 28, 512)  0           add_69[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res3c_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_212[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3c_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_213 (Activation)     (None, 28, 28, 128)  0           bn3c_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3c_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_213[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3c_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_214 (Activation)     (None, 28, 28, 128)  0           bn3c_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3c_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_214[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3c_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3c_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_70 (Add)                    (None, 28, 28, 512)  0           bn3c_branch2c[0][0]              \n",
            "                                                                 activation_212[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_215 (Activation)     (None, 28, 28, 512)  0           add_70[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res3d_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_215[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3d_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_216 (Activation)     (None, 28, 28, 128)  0           bn3d_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3d_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_216[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3d_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_217 (Activation)     (None, 28, 28, 128)  0           bn3d_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res3d_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_217[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn3d_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3d_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_71 (Add)                    (None, 28, 28, 512)  0           bn3d_branch2c[0][0]              \n",
            "                                                                 activation_215[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_218 (Activation)     (None, 28, 28, 512)  0           add_71[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4a_branch2a (Conv2D)         (None, 14, 14, 256)  131328      activation_218[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4a_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_219 (Activation)     (None, 14, 14, 256)  0           bn4a_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4a_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_219[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4a_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_220 (Activation)     (None, 14, 14, 256)  0           bn4a_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4a_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_220[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "res4a_branch1 (Conv2D)          (None, 14, 14, 1024) 525312      activation_218[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4a_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4a_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4a_branch1 (BatchNormalizatio (None, 14, 14, 1024) 4096        res4a_branch1[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "add_72 (Add)                    (None, 14, 14, 1024) 0           bn4a_branch2c[0][0]              \n",
            "                                                                 bn4a_branch1[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "activation_221 (Activation)     (None, 14, 14, 1024) 0           add_72[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4b_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_221[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4b_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_222 (Activation)     (None, 14, 14, 256)  0           bn4b_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4b_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_222[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4b_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_223 (Activation)     (None, 14, 14, 256)  0           bn4b_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4b_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_223[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4b_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4b_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_73 (Add)                    (None, 14, 14, 1024) 0           bn4b_branch2c[0][0]              \n",
            "                                                                 activation_221[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_224 (Activation)     (None, 14, 14, 1024) 0           add_73[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4c_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_224[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4c_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_225 (Activation)     (None, 14, 14, 256)  0           bn4c_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4c_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_225[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4c_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_226 (Activation)     (None, 14, 14, 256)  0           bn4c_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4c_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_226[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4c_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4c_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_74 (Add)                    (None, 14, 14, 1024) 0           bn4c_branch2c[0][0]              \n",
            "                                                                 activation_224[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_227 (Activation)     (None, 14, 14, 1024) 0           add_74[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4d_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_227[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4d_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_228 (Activation)     (None, 14, 14, 256)  0           bn4d_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4d_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_228[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4d_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_229 (Activation)     (None, 14, 14, 256)  0           bn4d_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4d_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_229[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4d_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4d_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_75 (Add)                    (None, 14, 14, 1024) 0           bn4d_branch2c[0][0]              \n",
            "                                                                 activation_227[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_230 (Activation)     (None, 14, 14, 1024) 0           add_75[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4e_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_230[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4e_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_231 (Activation)     (None, 14, 14, 256)  0           bn4e_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4e_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_231[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4e_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_232 (Activation)     (None, 14, 14, 256)  0           bn4e_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4e_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_232[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4e_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4e_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_76 (Add)                    (None, 14, 14, 1024) 0           bn4e_branch2c[0][0]              \n",
            "                                                                 activation_230[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_233 (Activation)     (None, 14, 14, 1024) 0           add_76[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res4f_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_233[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4f_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_234 (Activation)     (None, 14, 14, 256)  0           bn4f_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4f_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_234[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4f_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_235 (Activation)     (None, 14, 14, 256)  0           bn4f_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res4f_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_235[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn4f_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4f_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_77 (Add)                    (None, 14, 14, 1024) 0           bn4f_branch2c[0][0]              \n",
            "                                                                 activation_233[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_236 (Activation)     (None, 14, 14, 1024) 0           add_77[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res5a_branch2a (Conv2D)         (None, 7, 7, 512)    524800      activation_236[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5a_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_237 (Activation)     (None, 7, 7, 512)    0           bn5a_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5a_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_237[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5a_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_238 (Activation)     (None, 7, 7, 512)    0           bn5a_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5a_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_238[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "res5a_branch1 (Conv2D)          (None, 7, 7, 2048)   2099200     activation_236[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5a_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5a_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5a_branch1 (BatchNormalizatio (None, 7, 7, 2048)   8192        res5a_branch1[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "add_78 (Add)                    (None, 7, 7, 2048)   0           bn5a_branch2c[0][0]              \n",
            "                                                                 bn5a_branch1[0][0]               \n",
            "__________________________________________________________________________________________________\n",
            "activation_239 (Activation)     (None, 7, 7, 2048)   0           add_78[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res5b_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_239[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5b_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_240 (Activation)     (None, 7, 7, 512)    0           bn5b_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5b_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_240[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5b_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_241 (Activation)     (None, 7, 7, 512)    0           bn5b_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5b_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_241[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5b_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5b_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_79 (Add)                    (None, 7, 7, 2048)   0           bn5b_branch2c[0][0]              \n",
            "                                                                 activation_239[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_242 (Activation)     (None, 7, 7, 2048)   0           add_79[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "res5c_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_242[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5c_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2a[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_243 (Activation)     (None, 7, 7, 512)    0           bn5c_branch2a[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5c_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_243[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5c_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2b[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_244 (Activation)     (None, 7, 7, 512)    0           bn5c_branch2b[0][0]              \n",
            "__________________________________________________________________________________________________\n",
            "res5c_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_244[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "bn5c_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5c_branch2c[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "add_80 (Add)                    (None, 7, 7, 2048)   0           bn5c_branch2c[0][0]              \n",
            "                                                                 activation_242[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "activation_245 (Activation)     (None, 7, 7, 2048)   0           add_80[0][0]                     \n",
            "__________________________________________________________________________________________________\n",
            "flatten_5 (Flatten)             (None, 100352)       0           activation_245[0][0]             \n",
            "__________________________________________________________________________________________________\n",
            "dense_5 (Dense)                 (None, 2)            200706      flatten_5[0][0]                  \n",
            "==================================================================================================\n",
            "Total params: 23,788,418\n",
            "Trainable params: 23,735,298\n",
            "Non-trainable params: 53,120\n",
            "__________________________________________________________________________________________________\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WLdThyJaUFNW6dVXPP1912TLVokVV+/ePvBw7dqhWqaJ63nkmk1/MmGGfsVkz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\nThpmZlabk4aZmdXmpGFmZrX9C/Hubknb1LvRAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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++y1uvnDHcUo4sSwTqqoatIKnBZacZXT6AeMC6xOBHiKxLLJZACtXwmefwYUX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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "232/232 [==============================] - 9s 41ms/step\n",
            "[INFO] Accuracy: 58.41%\n",
            "[INFO] Loss: 0.962648857412895\n",
            "[INFO] Time Elapsed:  0:09:51.124082\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}