naiveCV.ipynb

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  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "naiveCV.ipynb",
      "provenance": [],
      "mount_file_id": "1LBbK1O1lpwvChSHthdbAe43w00nYiDkF",
      "authorship_tag": "ABX9TyPuqgVu1/SjrR3ohPkOy0eA",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Y2Data/DLwP-keras/blob/main/naiveCV.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "id": "v1nzVauULxn1",
        "outputId": "cc25c93f-1d69-47ee-bb11-46749ca0f349"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-eb4b2825-8f01-41b3-a84d-dd1b0ca6e1ef\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-eb4b2825-8f01-41b3-a84d-dd1b0ca6e1ef\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving kaggle.json to kaggle.json\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'kaggle.json': b'{\"username\":\"tim2dai\",\"key\":\"b7f3915dd9459a3ac01eec0e475bdbf1\"}'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JeiZHO10MjQR"
      },
      "source": [
        "!mkdir ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/ \n",
        "!chmod 600 ~/.kaggle/kaggle.json"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Bx4yPlCE8nq",
        "outputId": "607c7c67-a0ab-4c9c-d9ae-96cd50ead1de"
      },
      "source": [
        "!kaggle competitions download -c dogs-vs-cats"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Warning: Looks like you're using an outdated API Version, please consider updating (server 1.5.12 / client 1.5.4)\n",
            "Downloading test1.zip to /content\n",
            " 96% 260M/271M [00:01<00:00, 187MB/s]\n",
            "100% 271M/271M [00:01<00:00, 170MB/s]\n",
            "Downloading train.zip to /content\n",
            " 96% 524M/543M [00:03<00:00, 171MB/s]\n",
            "100% 543M/543M [00:03<00:00, 166MB/s]\n",
            "Downloading sampleSubmission.csv to /content\n",
            "  0% 0.00/86.8k [00:00<?, ?B/s]\n",
            "100% 86.8k/86.8k [00:00<00:00, 88.6MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9DvaC95CLvRZ"
      },
      "source": [
        "!unzip -qq train.zip"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "griNaLXcaV2D"
      },
      "source": [
        "!mkdir ../content/cats_vs_dogs_small"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NiEtxhbeN7j2"
      },
      "source": [
        "import os, shutil\n",
        "from pathlib import Path\n",
        "\n",
        "ORIGIN = Path('../content/train')\n",
        "NEW = Path('../content/cats_vs_dogs_small')\n",
        "\n",
        "def make_subnet(SUB, start, end):\n",
        "    for category in (\"cat\", \"dog\"):\n",
        "        DIR = NEW / SUB / category\n",
        "        os.makedirs(DIR)\n",
        "        fnames = [f\"{category}.{i}.jpg\" for i in range(start, end)]\n",
        "        for fname in fnames:\n",
        "            shutil.copyfile(src = ORIGIN / fname,\n",
        "                            dst = DIR / fname)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-pR9Qx_NP3Z-"
      },
      "source": [
        "make_subnet(\"train\", 0, 1000)\n",
        "make_subnet(\"validation\", 1000, 1500)\n",
        "make_subnet(\"test\", 1500, 2500)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zUBCd0p8QDc9"
      },
      "source": [
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GxEERhvHQz94"
      },
      "source": [
        "inputs = keras.Input(shape=(180, 180, 3))\n",
        "x = layers.experimental.preprocessing.Rescaling(1./255)(inputs)\n",
        "x = layers.Conv2D(filters=32, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=64, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=128, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.Flatten()(x)\n",
        "outputs = layers.Dense(1, activation=\"sigmoid\")(x)\n",
        "model = keras.Model(inputs=inputs, outputs=outputs)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TyG7Xhu8Rk-L",
        "outputId": "ef97bdd2-50de-40a8-99de-638ab3523f38"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_1 (InputLayer)         [(None, 180, 180, 3)]     0         \n",
            "_________________________________________________________________\n",
            "rescaling (Rescaling)        (None, 180, 180, 3)       0         \n",
            "_________________________________________________________________\n",
            "conv2d (Conv2D)              (None, 178, 178, 32)      896       \n",
            "_________________________________________________________________\n",
            "max_pooling2d (MaxPooling2D) (None, 89, 89, 32)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_1 (Conv2D)            (None, 87, 87, 64)        18496     \n",
            "_________________________________________________________________\n",
            "max_pooling2d_1 (MaxPooling2 (None, 43, 43, 64)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_2 (Conv2D)            (None, 41, 41, 128)       73856     \n",
            "_________________________________________________________________\n",
            "max_pooling2d_2 (MaxPooling2 (None, 20, 20, 128)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_3 (Conv2D)            (None, 18, 18, 256)       295168    \n",
            "_________________________________________________________________\n",
            "max_pooling2d_3 (MaxPooling2 (None, 9, 9, 256)         0         \n",
            "_________________________________________________________________\n",
            "conv2d_4 (Conv2D)            (None, 7, 7, 256)         590080    \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 12544)             0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 12545     \n",
            "=================================================================\n",
            "Total params: 991,041\n",
            "Trainable params: 991,041\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v0X3Raw7R9DL"
      },
      "source": [
        "model.compile(optimizer=\"rmsprop\",\n",
        "              loss=\"binary_crossentropy\",\n",
        "              metrics=[\"accuracy\"])"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K1mtPcjWSp4J",
        "outputId": "a0d1fd2e-4626-42fc-c822-db7324fa3d4f"
      },
      "source": [
        "from tensorflow.keras.preprocessing import image_dataset_from_directory\n",
        "\n",
        "train_dataset = image_dataset_from_directory(\n",
        "    NEW / \"train\",\n",
        "    image_size=(180, 180),\n",
        "    batch_size=32)\n",
        "test_dataset = image_dataset_from_directory(\n",
        "    NEW / \"test\",\n",
        "    image_size=(180, 180),\n",
        "    batch_size=32)\n",
        "val_dataset = image_dataset_from_directory(\n",
        "    NEW / \"validation\",\n",
        "    image_size=(180, 180),\n",
        "    batch_size=32)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 2000 files belonging to 2 classes.\n",
            "Found 2000 files belonging to 2 classes.\n",
            "Found 1000 files belonging to 2 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TmQ1Qs5raIv0"
      },
      "source": [
        "callbacks = [\n",
        "    keras.callbacks.ModelCheckpoint(\n",
        "        filepath=\"naiveCV.keras\",\n",
        "        save_best_only=True,\n",
        "        monitor=\"val_loss\"\n",
        "    )\n",
        "]"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wY17FqLSbqw5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b19bf15e-32f5-48d3-d33d-3d8cddb3af81"
      },
      "source": [
        "history = model.fit(\n",
        "    train_dataset,\n",
        "    epochs=30,\n",
        "    callbacks=callbacks,\n",
        "    validation_data=val_dataset\n",
        ")"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/30\n",
            "63/63 [==============================] - 21s 77ms/step - loss: 0.7265 - accuracy: 0.5185 - val_loss: 0.6945 - val_accuracy: 0.5010\n",
            "Epoch 2/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.7187 - accuracy: 0.5505 - val_loss: 0.6797 - val_accuracy: 0.5330\n",
            "Epoch 3/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.6582 - accuracy: 0.6100 - val_loss: 0.6792 - val_accuracy: 0.5710\n",
            "Epoch 4/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.6631 - accuracy: 0.6220 - val_loss: 0.6604 - val_accuracy: 0.6180\n",
            "Epoch 5/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.6152 - accuracy: 0.6785 - val_loss: 0.6211 - val_accuracy: 0.6760\n",
            "Epoch 6/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.5751 - accuracy: 0.7065 - val_loss: 0.6186 - val_accuracy: 0.6780\n",
            "Epoch 7/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.5152 - accuracy: 0.7375 - val_loss: 0.6932 - val_accuracy: 0.6940\n",
            "Epoch 8/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.4843 - accuracy: 0.7825 - val_loss: 0.6180 - val_accuracy: 0.7030\n",
            "Epoch 9/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.4287 - accuracy: 0.7990 - val_loss: 0.6229 - val_accuracy: 0.7410\n",
            "Epoch 10/30\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.3636 - accuracy: 0.8440 - val_loss: 0.6864 - val_accuracy: 0.6840\n",
            "Epoch 11/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.2946 - accuracy: 0.8730 - val_loss: 1.1015 - val_accuracy: 0.6730\n",
            "Epoch 12/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.2427 - accuracy: 0.9020 - val_loss: 0.8512 - val_accuracy: 0.7080\n",
            "Epoch 13/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.1895 - accuracy: 0.9240 - val_loss: 1.1098 - val_accuracy: 0.7100\n",
            "Epoch 14/30\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.1410 - accuracy: 0.9485 - val_loss: 1.0228 - val_accuracy: 0.7420\n",
            "Epoch 15/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.1326 - accuracy: 0.9510 - val_loss: 1.1285 - val_accuracy: 0.7210\n",
            "Epoch 16/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0828 - accuracy: 0.9650 - val_loss: 1.3199 - val_accuracy: 0.7290\n",
            "Epoch 17/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0790 - accuracy: 0.9735 - val_loss: 1.7944 - val_accuracy: 0.6750\n",
            "Epoch 18/30\n",
            "63/63 [==============================] - 5s 69ms/step - loss: 0.0717 - accuracy: 0.9745 - val_loss: 1.7143 - val_accuracy: 0.7160\n",
            "Epoch 19/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0609 - accuracy: 0.9780 - val_loss: 1.5924 - val_accuracy: 0.7310\n",
            "Epoch 20/30\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.0564 - accuracy: 0.9815 - val_loss: 1.6753 - val_accuracy: 0.7490\n",
            "Epoch 21/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0481 - accuracy: 0.9865 - val_loss: 2.0254 - val_accuracy: 0.7410\n",
            "Epoch 22/30\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.0741 - accuracy: 0.9750 - val_loss: 1.5440 - val_accuracy: 0.7170\n",
            "Epoch 23/30\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.0374 - accuracy: 0.9895 - val_loss: 2.1163 - val_accuracy: 0.7320\n",
            "Epoch 24/30\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.0500 - accuracy: 0.9835 - val_loss: 2.1645 - val_accuracy: 0.7040\n",
            "Epoch 25/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0611 - accuracy: 0.9845 - val_loss: 1.9189 - val_accuracy: 0.7110\n",
            "Epoch 26/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0427 - accuracy: 0.9890 - val_loss: 2.4990 - val_accuracy: 0.7120\n",
            "Epoch 27/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0528 - accuracy: 0.9840 - val_loss: 2.3665 - val_accuracy: 0.7240\n",
            "Epoch 28/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0669 - accuracy: 0.9860 - val_loss: 2.0215 - val_accuracy: 0.7270\n",
            "Epoch 29/30\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.0291 - accuracy: 0.9885 - val_loss: 2.2939 - val_accuracy: 0.7140\n",
            "Epoch 30/30\n",
            "63/63 [==============================] - 5s 70ms/step - loss: 0.0369 - accuracy: 0.9905 - val_loss: 2.6006 - val_accuracy: 0.7190\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dqID8XgTb1--",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "cfe1af43-76a0-4daf-8d3d-8ac7b7b91fda"
      },
      "source": [
        "# plotting loss & accuracy\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('seaborn-pastel')\n",
        "\n",
        "loss = history.history[\"loss\"] \n",
        "val_loss = history.history[\"val_loss\"] \n",
        "acc = history.history[\"accuracy\"] \n",
        "val_acc = history.history[\"val_accuracy\"] \n",
        "epochs = range(1, len(loss) + 1) \n",
        "\n",
        "fig, ax1 = plt.subplots()\n",
        "ax2 = ax1.twinx()\n",
        "\n",
        "ax1.plot(epochs, loss, \"bo\", label=\"Train loss\", alpha=0.5) \n",
        "ax1.plot(epochs, val_loss, \"b\", label=\"Val loss\", alpha=0.5) \n",
        "ax1.tick_params(axis='y', labelcolor='tab:blue')\n",
        "ax1.set_xlabel(\"Epochs\") \n",
        "ax1.set_ylabel(\"Loss\") \n",
        "\n",
        "ax2.set_ylabel(\"Accuracy\")\n",
        "ax2.set_ylim(top=1.0)\n",
        "ax2.plot(epochs, acc, \"go\", label=\"Train acc\", alpha=0.5) \n",
        "ax2.plot(epochs, val_acc, \"g\", label=\"Val acc\", alpha=0.5) \n",
        "ax2.tick_params(axis='y', labelcolor='tab:green')\n",
        "\n",
        "fig.tight_layout()\n",
        "# fig.legend(loc='upper left')\n",
        "plt.show()\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bi_O66TMeHk6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4dd4af02-0a96-4676-8b6d-839809d328c0"
      },
      "source": [
        "test_model = keras.models.load_model(\"naiveCV.keras\")\n",
        "test_loss, test_acc = test_model.evaluate(test_dataset)\n",
        "print(\"Test loss: {}\\n accuracy: {:.4f}\".format(test_loss, test_acc))"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "63/63 [==============================] - 3s 37ms/step - loss: 0.6590 - accuracy: 0.6670\n",
            "Test loss: 0.6589857339859009\n",
            " accuracy: 0.6670\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wyiqfq8pepf-"
      },
      "source": [
        "data_aug = keras.Sequential([\n",
        "    layers.experimental.preprocessing.RandomFlip(\"horizontal\"),\n",
        "    layers.experimental.preprocessing.RandomRotation(0.1),\n",
        "    layers.experimental.preprocessing.RandomZoom(0.2)\n",
        "])"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 629
        },
        "id": "XX4BgI1HfUKL",
        "outputId": "375cb4bd-a7e6-48f5-b9c5-6d734671ae9b"
      },
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "for images, _ in train_dataset.take(42):\n",
        "    for i in range(9):\n",
        "        augmented_images = data_aug(images)\n",
        "        ax = plt.subplot(3, 3, i+1)\n",
        "        plt.imshow(augmented_images[0].numpy().astype('uint8'))\n",
        "        plt.axis(\"off\")"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
            "  \"\"\"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 9 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hQD4YqywhNmx"
      },
      "source": [
        "inputs = keras.Input(shape=(180, 180, 3))\n",
        "x = data_aug(inputs)\n",
        "x = layers.experimental.preprocessing.Rescaling(1./255)(x)\n",
        "x = layers.Conv2D(filters=32, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=64, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=128, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.MaxPooling2D(pool_size=2)(x)\n",
        "x = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\n",
        "x = layers.Flatten()(x)\n",
        "x = layers.Dropout(0.5)(x)\n",
        "outputs = layers.Dense(1, activation=\"sigmoid\")(x)\n",
        "new_model = keras.Model(inputs=inputs, outputs=outputs)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3HJWor30ipTe"
      },
      "source": [
        "new_model.compile(optimizer=\"rmsprop\",\n",
        "              loss=\"binary_crossentropy\",\n",
        "              metrics=[\"accuracy\"])\n",
        "new_callbacks = [\n",
        "    keras.callbacks.ModelCheckpoint(\n",
        "        filepath=\"naiveCVwithDataAug.keras\",\n",
        "        save_best_only=True,\n",
        "        monitor=\"val_loss\"\n",
        "    )\n",
        "]"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RowkAmsvipl9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2962145a-9c38-4f99-a35f-8638aab71ff9"
      },
      "source": [
        "history = new_model.fit(\n",
        "    train_dataset,\n",
        "    epochs=100,\n",
        "    validation_data=val_dataset,\n",
        "    callbacks=new_callbacks\n",
        ")"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/100\n",
            "63/63 [==============================] - 6s 75ms/step - loss: 0.7006 - accuracy: 0.4905 - val_loss: 0.6922 - val_accuracy: 0.5560\n",
            "Epoch 2/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.7334 - accuracy: 0.5135 - val_loss: 0.7058 - val_accuracy: 0.5020\n",
            "Epoch 3/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.7011 - accuracy: 0.5670 - val_loss: 0.6824 - val_accuracy: 0.5340\n",
            "Epoch 4/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.6723 - accuracy: 0.5950 - val_loss: 0.6698 - val_accuracy: 0.5940\n",
            "Epoch 5/100\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.6628 - accuracy: 0.6270 - val_loss: 0.6248 - val_accuracy: 0.6410\n",
            "Epoch 6/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.6151 - accuracy: 0.6595 - val_loss: 0.6321 - val_accuracy: 0.6260\n",
            "Epoch 7/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.6297 - accuracy: 0.6645 - val_loss: 0.6529 - val_accuracy: 0.6120\n",
            "Epoch 8/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.6032 - accuracy: 0.6770 - val_loss: 0.6101 - val_accuracy: 0.6440\n",
            "Epoch 9/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.6137 - accuracy: 0.6960 - val_loss: 0.5891 - val_accuracy: 0.6760\n",
            "Epoch 10/100\n",
            "63/63 [==============================] - 5s 71ms/step - loss: 0.5813 - accuracy: 0.7005 - val_loss: 0.6168 - val_accuracy: 0.6810\n",
            "Epoch 11/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.5852 - accuracy: 0.7025 - val_loss: 0.5299 - val_accuracy: 0.7290\n",
            "Epoch 12/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.5770 - accuracy: 0.7050 - val_loss: 0.5525 - val_accuracy: 0.7170\n",
            "Epoch 13/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.5717 - accuracy: 0.7060 - val_loss: 0.5243 - val_accuracy: 0.7240\n",
            "Epoch 14/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.5469 - accuracy: 0.7200 - val_loss: 0.5457 - val_accuracy: 0.7220\n",
            "Epoch 15/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.5322 - accuracy: 0.7380 - val_loss: 0.5168 - val_accuracy: 0.7370\n",
            "Epoch 16/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.5215 - accuracy: 0.7495 - val_loss: 0.4829 - val_accuracy: 0.7700\n",
            "Epoch 17/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.5085 - accuracy: 0.7570 - val_loss: 0.5372 - val_accuracy: 0.7290\n",
            "Epoch 18/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.5008 - accuracy: 0.7565 - val_loss: 0.7167 - val_accuracy: 0.6770\n",
            "Epoch 19/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.4949 - accuracy: 0.7580 - val_loss: 0.5775 - val_accuracy: 0.7010\n",
            "Epoch 20/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.4848 - accuracy: 0.7645 - val_loss: 0.5710 - val_accuracy: 0.7560\n",
            "Epoch 21/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.4770 - accuracy: 0.7750 - val_loss: 0.5005 - val_accuracy: 0.7770\n",
            "Epoch 22/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4626 - accuracy: 0.7795 - val_loss: 0.5880 - val_accuracy: 0.7200\n",
            "Epoch 23/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.4651 - accuracy: 0.7850 - val_loss: 0.5009 - val_accuracy: 0.7620\n",
            "Epoch 24/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.4443 - accuracy: 0.8010 - val_loss: 0.4748 - val_accuracy: 0.7750\n",
            "Epoch 25/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4446 - accuracy: 0.7925 - val_loss: 0.4690 - val_accuracy: 0.7720\n",
            "Epoch 26/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4349 - accuracy: 0.8115 - val_loss: 0.5301 - val_accuracy: 0.7770\n",
            "Epoch 27/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4255 - accuracy: 0.7970 - val_loss: 0.5257 - val_accuracy: 0.7740\n",
            "Epoch 28/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.4555 - accuracy: 0.7945 - val_loss: 0.6348 - val_accuracy: 0.7180\n",
            "Epoch 29/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4188 - accuracy: 0.8125 - val_loss: 0.6954 - val_accuracy: 0.7230\n",
            "Epoch 30/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.3915 - accuracy: 0.8240 - val_loss: 0.5303 - val_accuracy: 0.7550\n",
            "Epoch 31/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.4043 - accuracy: 0.8155 - val_loss: 0.5492 - val_accuracy: 0.7750\n",
            "Epoch 32/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.4014 - accuracy: 0.8215 - val_loss: 0.5238 - val_accuracy: 0.7940\n",
            "Epoch 33/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3913 - accuracy: 0.8280 - val_loss: 0.5532 - val_accuracy: 0.7560\n",
            "Epoch 34/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.3824 - accuracy: 0.8370 - val_loss: 0.4780 - val_accuracy: 0.7820\n",
            "Epoch 35/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.3899 - accuracy: 0.8375 - val_loss: 0.4637 - val_accuracy: 0.7850\n",
            "Epoch 36/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.3606 - accuracy: 0.8375 - val_loss: 0.6477 - val_accuracy: 0.7620\n",
            "Epoch 37/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3483 - accuracy: 0.8520 - val_loss: 0.4759 - val_accuracy: 0.8040\n",
            "Epoch 38/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.3573 - accuracy: 0.8520 - val_loss: 0.9132 - val_accuracy: 0.7410\n",
            "Epoch 39/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.3492 - accuracy: 0.8440 - val_loss: 0.5526 - val_accuracy: 0.7680\n",
            "Epoch 40/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3407 - accuracy: 0.8485 - val_loss: 0.4724 - val_accuracy: 0.8130\n",
            "Epoch 41/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.3426 - accuracy: 0.8520 - val_loss: 0.5069 - val_accuracy: 0.8000\n",
            "Epoch 42/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3347 - accuracy: 0.8590 - val_loss: 0.7088 - val_accuracy: 0.7470\n",
            "Epoch 43/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3335 - accuracy: 0.8555 - val_loss: 0.5750 - val_accuracy: 0.7750\n",
            "Epoch 44/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.3191 - accuracy: 0.8595 - val_loss: 0.6460 - val_accuracy: 0.7900\n",
            "Epoch 45/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3360 - accuracy: 0.8565 - val_loss: 0.4600 - val_accuracy: 0.8160\n",
            "Epoch 46/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.3140 - accuracy: 0.8575 - val_loss: 0.6967 - val_accuracy: 0.7350\n",
            "Epoch 47/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.3032 - accuracy: 0.8715 - val_loss: 0.5310 - val_accuracy: 0.7960\n",
            "Epoch 48/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2941 - accuracy: 0.8805 - val_loss: 0.7381 - val_accuracy: 0.8050\n",
            "Epoch 49/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2969 - accuracy: 0.8740 - val_loss: 0.6819 - val_accuracy: 0.7750\n",
            "Epoch 50/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3014 - accuracy: 0.8695 - val_loss: 0.4752 - val_accuracy: 0.8150\n",
            "Epoch 51/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2951 - accuracy: 0.8830 - val_loss: 0.6032 - val_accuracy: 0.8150\n",
            "Epoch 52/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.3118 - accuracy: 0.8695 - val_loss: 0.6061 - val_accuracy: 0.7960\n",
            "Epoch 53/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2717 - accuracy: 0.8885 - val_loss: 0.5120 - val_accuracy: 0.8230\n",
            "Epoch 54/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.2659 - accuracy: 0.8875 - val_loss: 0.4888 - val_accuracy: 0.8170\n",
            "Epoch 55/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2752 - accuracy: 0.8895 - val_loss: 0.7777 - val_accuracy: 0.8100\n",
            "Epoch 56/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2898 - accuracy: 0.8840 - val_loss: 0.5423 - val_accuracy: 0.8000\n",
            "Epoch 57/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2710 - accuracy: 0.8900 - val_loss: 0.5676 - val_accuracy: 0.8200\n",
            "Epoch 58/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2548 - accuracy: 0.8990 - val_loss: 0.4999 - val_accuracy: 0.8350\n",
            "Epoch 59/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2815 - accuracy: 0.8830 - val_loss: 0.7257 - val_accuracy: 0.7830\n",
            "Epoch 60/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2581 - accuracy: 0.9005 - val_loss: 0.7036 - val_accuracy: 0.8140\n",
            "Epoch 61/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2290 - accuracy: 0.9055 - val_loss: 0.9284 - val_accuracy: 0.7960\n",
            "Epoch 62/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2621 - accuracy: 0.8965 - val_loss: 0.6559 - val_accuracy: 0.8100\n",
            "Epoch 63/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2427 - accuracy: 0.9035 - val_loss: 0.7485 - val_accuracy: 0.8310\n",
            "Epoch 64/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2423 - accuracy: 0.9050 - val_loss: 0.6565 - val_accuracy: 0.8010\n",
            "Epoch 65/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2372 - accuracy: 0.9165 - val_loss: 0.5316 - val_accuracy: 0.7970\n",
            "Epoch 66/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.2354 - accuracy: 0.9105 - val_loss: 0.5092 - val_accuracy: 0.8180\n",
            "Epoch 67/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2215 - accuracy: 0.9110 - val_loss: 0.6335 - val_accuracy: 0.8000\n",
            "Epoch 68/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2690 - accuracy: 0.8890 - val_loss: 0.4874 - val_accuracy: 0.8470\n",
            "Epoch 69/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2488 - accuracy: 0.9055 - val_loss: 0.5040 - val_accuracy: 0.8380\n",
            "Epoch 70/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2432 - accuracy: 0.9070 - val_loss: 0.6106 - val_accuracy: 0.7970\n",
            "Epoch 71/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2383 - accuracy: 0.9120 - val_loss: 0.6836 - val_accuracy: 0.7860\n",
            "Epoch 72/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.1996 - accuracy: 0.9200 - val_loss: 0.8851 - val_accuracy: 0.8060\n",
            "Epoch 73/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2300 - accuracy: 0.9195 - val_loss: 0.6259 - val_accuracy: 0.8480\n",
            "Epoch 74/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2227 - accuracy: 0.9140 - val_loss: 0.6391 - val_accuracy: 0.7940\n",
            "Epoch 75/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2151 - accuracy: 0.9170 - val_loss: 0.6184 - val_accuracy: 0.8070\n",
            "Epoch 76/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2252 - accuracy: 0.9150 - val_loss: 1.4912 - val_accuracy: 0.7690\n",
            "Epoch 77/100\n",
            "63/63 [==============================] - 5s 76ms/step - loss: 0.2282 - accuracy: 0.9145 - val_loss: 0.6432 - val_accuracy: 0.8030\n",
            "Epoch 78/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2116 - accuracy: 0.9220 - val_loss: 0.5530 - val_accuracy: 0.8330\n",
            "Epoch 79/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2280 - accuracy: 0.9080 - val_loss: 0.5177 - val_accuracy: 0.8320\n",
            "Epoch 80/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2262 - accuracy: 0.9150 - val_loss: 0.5438 - val_accuracy: 0.8180\n",
            "Epoch 81/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2211 - accuracy: 0.9165 - val_loss: 0.5242 - val_accuracy: 0.8490\n",
            "Epoch 82/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2479 - accuracy: 0.9215 - val_loss: 0.5753 - val_accuracy: 0.8220\n",
            "Epoch 83/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.1965 - accuracy: 0.9235 - val_loss: 1.2647 - val_accuracy: 0.7770\n",
            "Epoch 84/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2256 - accuracy: 0.9150 - val_loss: 0.6280 - val_accuracy: 0.8210\n",
            "Epoch 85/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2320 - accuracy: 0.9250 - val_loss: 0.6139 - val_accuracy: 0.8430\n",
            "Epoch 86/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2242 - accuracy: 0.9255 - val_loss: 0.6725 - val_accuracy: 0.8350\n",
            "Epoch 87/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2066 - accuracy: 0.9270 - val_loss: 0.5853 - val_accuracy: 0.8490\n",
            "Epoch 88/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.1879 - accuracy: 0.9350 - val_loss: 0.7507 - val_accuracy: 0.8090\n",
            "Epoch 89/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2059 - accuracy: 0.9250 - val_loss: 0.7385 - val_accuracy: 0.8420\n",
            "Epoch 90/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2022 - accuracy: 0.9305 - val_loss: 0.7081 - val_accuracy: 0.8260\n",
            "Epoch 91/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.1947 - accuracy: 0.9320 - val_loss: 0.6178 - val_accuracy: 0.8290\n",
            "Epoch 92/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2318 - accuracy: 0.9155 - val_loss: 0.6349 - val_accuracy: 0.8170\n",
            "Epoch 93/100\n",
            "63/63 [==============================] - 5s 73ms/step - loss: 0.2012 - accuracy: 0.9235 - val_loss: 0.7152 - val_accuracy: 0.8340\n",
            "Epoch 94/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.1957 - accuracy: 0.9300 - val_loss: 0.7437 - val_accuracy: 0.8400\n",
            "Epoch 95/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2296 - accuracy: 0.9235 - val_loss: 0.6074 - val_accuracy: 0.8280\n",
            "Epoch 96/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2300 - accuracy: 0.9155 - val_loss: 1.0542 - val_accuracy: 0.8060\n",
            "Epoch 97/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.2121 - accuracy: 0.9220 - val_loss: 0.6274 - val_accuracy: 0.8240\n",
            "Epoch 98/100\n",
            "63/63 [==============================] - 5s 74ms/step - loss: 0.1863 - accuracy: 0.9310 - val_loss: 0.7032 - val_accuracy: 0.8120\n",
            "Epoch 99/100\n",
            "63/63 [==============================] - 5s 75ms/step - loss: 0.2199 - accuracy: 0.9170 - val_loss: 0.7383 - val_accuracy: 0.8250\n",
            "Epoch 100/100\n",
            "63/63 [==============================] - 5s 72ms/step - loss: 0.2109 - accuracy: 0.9290 - val_loss: 0.5925 - val_accuracy: 0.8440\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w2lkg0i3jAuv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f9963622-d9a4-45f6-e35d-bdb3c120029e"
      },
      "source": [
        "test_model = keras.models.load_model(\"naiveCVwithDataAug.keras\")\n",
        "test_loss, test_acc = test_model.evaluate(test_dataset)\n",
        "print(\"Test loss: {}\\n accuracy: {:.4f}\".format(test_loss, test_acc))"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "63/63 [==============================] - 3s 38ms/step - loss: 0.5267 - accuracy: 0.8000\n",
            "Test loss: 0.5267313718795776\n",
            " accuracy: 0.8000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pzBrkYc6koIQ"
      },
      "source": [
        "plt.style.use('seaborn-pastel')\n",
        "\n",
        "def plot_loss_acc(history):\n",
        "    loss = history.history[\"loss\"] \n",
        "    val_loss = history.history[\"val_loss\"] \n",
        "    acc = history.history[\"accuracy\"] \n",
        "    val_acc = history.history[\"val_accuracy\"] \n",
        "    epochs = range(1, len(loss) + 1) \n",
        "\n",
        "    fig, ax1 = plt.subplots()\n",
        "    ax2 = ax1.twinx()\n",
        "\n",
        "    ax1.plot(epochs, loss, \"bo\", label=\"Train loss\", alpha=0.5) \n",
        "    ax1.plot(epochs, val_loss, \"b\", label=\"Val loss\", alpha=0.5) \n",
        "    ax1.tick_params(axis='y', labelcolor='tab:blue')\n",
        "    ax1.set_xlabel(\"Epochs\") \n",
        "    ax1.set_ylabel(\"Loss\") \n",
        "\n",
        "    ax2.set_ylabel(\"Accuracy\")\n",
        "    ax2.set_ylim(top=1.0)\n",
        "    ax2.plot(epochs, acc, \"go\", label=\"Train acc\", alpha=0.5) \n",
        "    ax2.plot(epochs, val_acc, \"g\", label=\"Val acc\", alpha=0.5) \n",
        "    ax2.tick_params(axis='y', labelcolor='tab:green')\n",
        "\n",
        "    fig.tight_layout()\n",
        "    # fig.legend(loc='upper left')\n",
        "    plt.show()\n",
        "\n",
        "def plot_loss(history):\n",
        "    loss = history.history[\"loss\"] \n",
        "    val_loss = history.history[\"val_loss\"] \n",
        "    epochs = range(1, len(loss) + 1) \n",
        "    plt.plot(epochs, loss, \"bo\", label=\"Training loss\") \n",
        "    plt.plot(epochs, val_loss, \"b\", label=\"Validation loss\") \n",
        "    plt.title(\"Training and validation loss\") \n",
        "    plt.xlabel(\"Epochs\") \n",
        "    plt.ylabel(\"Loss\") \n",
        "    plt.legend() \n",
        "    plt.show()\n",
        "\n",
        "def plot_acc(history):\n",
        "    plt.clf() \n",
        "    acc = history.history[\"accuracy\"] \n",
        "    val_acc = history.history[\"val_accuracy\"] \n",
        "    epochs = range(1, len(acc) + 1) \n",
        "    plt.plot(epochs, acc, \"bo\", label=\"Training accuracy\") \n",
        "    plt.plot(epochs, val_acc, \"b\", label=\"Validation accuracy\") \n",
        "    plt.title(\"Training and validation accuracy\") \n",
        "    plt.xlabel(\"Epochs\") \n",
        "    plt.ylabel(\"Accuracy\") \n",
        "    plt.legend() \n",
        "    plt.show()"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qg9O8O6preVO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b884342f-68ab-4647-e180-4604c7857085"
      },
      "source": [
        "vgg16_base = keras.applications.vgg16.VGG16(\n",
        "    weights=\"imagenet\",\n",
        "    include_top=False,\n",
        "    input_shape=(180, 180, 3)\n",
        ")"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "58892288/58889256 [==============================] - 1s 0us/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pld0N2Z7_8Hg",
        "outputId": "6c5c2561-9da2-4bf0-ceba-f32925726eb3"
      },
      "source": [
        "vgg16_base.summary()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"vgg16\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_3 (InputLayer)         [(None, 180, 180, 3)]     0         \n",
            "_________________________________________________________________\n",
            "block1_conv1 (Conv2D)        (None, 180, 180, 64)      1792      \n",
            "_________________________________________________________________\n",
            "block1_conv2 (Conv2D)        (None, 180, 180, 64)      36928     \n",
            "_________________________________________________________________\n",
            "block1_pool (MaxPooling2D)   (None, 90, 90, 64)        0         \n",
            "_________________________________________________________________\n",
            "block2_conv1 (Conv2D)        (None, 90, 90, 128)       73856     \n",
            "_________________________________________________________________\n",
            "block2_conv2 (Conv2D)        (None, 90, 90, 128)       147584    \n",
            "_________________________________________________________________\n",
            "block2_pool (MaxPooling2D)   (None, 45, 45, 128)       0         \n",
            "_________________________________________________________________\n",
            "block3_conv1 (Conv2D)        (None, 45, 45, 256)       295168    \n",
            "_________________________________________________________________\n",
            "block3_conv2 (Conv2D)        (None, 45, 45, 256)       590080    \n",
            "_________________________________________________________________\n",
            "block3_conv3 (Conv2D)        (None, 45, 45, 256)       590080    \n",
            "_________________________________________________________________\n",
            "block3_pool (MaxPooling2D)   (None, 22, 22, 256)       0         \n",
            "_________________________________________________________________\n",
            "block4_conv1 (Conv2D)        (None, 22, 22, 512)       1180160   \n",
            "_________________________________________________________________\n",
            "block4_conv2 (Conv2D)        (None, 22, 22, 512)       2359808   \n",
            "_________________________________________________________________\n",
            "block4_conv3 (Conv2D)        (None, 22, 22, 512)       2359808   \n",
            "_________________________________________________________________\n",
            "block4_pool (MaxPooling2D)   (None, 11, 11, 512)       0         \n",
            "_________________________________________________________________\n",
            "block5_conv1 (Conv2D)        (None, 11, 11, 512)       2359808   \n",
            "_________________________________________________________________\n",
            "block5_conv2 (Conv2D)        (None, 11, 11, 512)       2359808   \n",
            "_________________________________________________________________\n",
            "block5_conv3 (Conv2D)        (None, 11, 11, 512)       2359808   \n",
            "_________________________________________________________________\n",
            "block5_pool (MaxPooling2D)   (None, 5, 5, 512)         0         \n",
            "=================================================================\n",
            "Total params: 14,714,688\n",
            "Trainable params: 14,714,688\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pkfhwzXF_9XD"
      },
      "source": [
        "import numpy as np\n",
        "def get_all_features_and_labels(dataset):\n",
        "    all_features, all_labels = [], []\n",
        "    for images, labels in dataset:\n",
        "        preprocessed_images = keras.applications.vgg16.preprocess_input(images)\n",
        "        features = vgg16_base.predict(preprocessed_images)\n",
        "        all_features.append(features)\n",
        "        all_labels.append(labels)\n",
        "    return np.concatenate(all_features), np.concatenate(all_labels)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o8RblSnx_9nt"
      },
      "source": [
        "inputs = layers.Input(shape=(5, 5, 512))\n",
        "x = layers.Flatten()(inputs)\n",
        "x = layers.Dense(256)(x)\n",
        "x = layers.Dropout(0.5)(x)\n",
        "outputs = layers.Dense(1, activation=\"sigmoid\")(x)\n",
        "model = keras.Model(inputs, outputs)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DoYrtIaF_-uj"
      },
      "source": [
        "model.compile(optimizer=\"rmsprop\", loss=\"binary_crossentropy\",\n",
        "              metrics=[\"accuracy\"])\n",
        "callbacks = [keras.callbacks.ModelCheckpoint(\n",
        "    filepath=\"feature_extraction.keras\",\n",
        "    save_best_only=True,\n",
        "    monitor=\"val_loss\"\n",
        ")]"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AumkFHobAURf"
      },
      "source": [
        "train_features, train_labels =  get_all_features_and_labels(train_dataset) \n",
        "val_features, val_labels =  get_all_features_and_labels(val_dataset) \n",
        "test_features, test_labels =  get_all_features_and_labels(test_dataset)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lSRqArdu__pY",
        "outputId": "d69975ab-2003-47a4-f3a6-0b01ddbf1aa6"
      },
      "source": [
        "history = model.fit(\n",
        "    train_features, train_labels,\n",
        "    epochs=20,\n",
        "    validation_data=(val_features, val_labels),\n",
        "    callbacks=callbacks\n",
        ")"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/20\n",
            "63/63 [==============================] - 1s 6ms/step - loss: 15.5623 - accuracy: 0.9215 - val_loss: 3.3773 - val_accuracy: 0.9720\n",
            "Epoch 2/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 3.7040 - accuracy: 0.9775 - val_loss: 5.6300 - val_accuracy: 0.9670\n",
            "Epoch 3/20\n",
            "63/63 [==============================] - 0s 6ms/step - loss: 3.2099 - accuracy: 0.9790 - val_loss: 4.5292 - val_accuracy: 0.9730\n",
            "Epoch 4/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 1.8542 - accuracy: 0.9880 - val_loss: 4.2530 - val_accuracy: 0.9780\n",
            "Epoch 5/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.9376 - accuracy: 0.9945 - val_loss: 6.3414 - val_accuracy: 0.9740\n",
            "Epoch 6/20\n",
            "63/63 [==============================] - 0s 5ms/step - loss: 1.3486 - accuracy: 0.9905 - val_loss: 8.3835 - val_accuracy: 0.9590\n",
            "Epoch 7/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.4526 - accuracy: 0.9935 - val_loss: 6.2775 - val_accuracy: 0.9730\n",
            "Epoch 8/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.3105 - accuracy: 0.9970 - val_loss: 5.3049 - val_accuracy: 0.9750\n",
            "Epoch 9/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.2115 - accuracy: 0.9960 - val_loss: 5.0405 - val_accuracy: 0.9740\n",
            "Epoch 10/20\n",
            "63/63 [==============================] - 0s 6ms/step - loss: 0.4232 - accuracy: 0.9965 - val_loss: 5.1050 - val_accuracy: 0.9740\n",
            "Epoch 11/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.5670 - accuracy: 0.9955 - val_loss: 5.4701 - val_accuracy: 0.9750\n",
            "Epoch 12/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.0829 - accuracy: 0.9985 - val_loss: 5.1909 - val_accuracy: 0.9760\n",
            "Epoch 13/20\n",
            "63/63 [==============================] - 0s 5ms/step - loss: 0.3357 - accuracy: 0.9970 - val_loss: 7.7338 - val_accuracy: 0.9630\n",
            "Epoch 14/20\n",
            "63/63 [==============================] - 0s 5ms/step - loss: 0.2959 - accuracy: 0.9960 - val_loss: 8.6040 - val_accuracy: 0.9640\n",
            "Epoch 15/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.1036 - accuracy: 0.9990 - val_loss: 4.1939 - val_accuracy: 0.9760\n",
            "Epoch 16/20\n",
            "63/63 [==============================] - 0s 5ms/step - loss: 7.5904e-05 - accuracy: 1.0000 - val_loss: 3.8249 - val_accuracy: 0.9790\n",
            "Epoch 17/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.0779 - accuracy: 0.9990 - val_loss: 3.8521 - val_accuracy: 0.9780\n",
            "Epoch 18/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 0.0523 - accuracy: 0.9990 - val_loss: 2.8375 - val_accuracy: 0.9800\n",
            "Epoch 19/20\n",
            "63/63 [==============================] - 0s 5ms/step - loss: 0.1883 - accuracy: 0.9975 - val_loss: 2.8406 - val_accuracy: 0.9800\n",
            "Epoch 20/20\n",
            "63/63 [==============================] - 0s 4ms/step - loss: 5.3603e-17 - accuracy: 1.0000 - val_loss: 2.8406 - val_accuracy: 0.9800\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e4kEMtBeAroZ"
      },
      "source": [
        "vgg16_frozen = keras.applications.vgg16.VGG16(\n",
        "    weights=\"imagenet\",\n",
        "    include_top=False)\n",
        "vgg16_frozen.trainable = False"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B76iYqKUB2iF"
      },
      "source": [
        "data_aug = keras.Sequential([\n",
        "    layers.experimental.preprocessing.RandomFlip('horizontal'),\n",
        "    layers.experimental.preprocessing.RandomRotation(0.1),\n",
        "    layers.experimental.preprocessing.RandomZoom(0.2)])"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ESpmmCBsCQuc"
      },
      "source": [
        "inputs = layers.Input(shape=(180, 180, 3))\n",
        "x = data_aug(inputs)\n",
        "x = vgg16_frozen(x)\n",
        "x = layers.Flatten()(x)\n",
        "x = layers.Dense(256)(x)\n",
        "x = layers.Dropout(0.5)(x)\n",
        "outputs = layers.Dense(1, activation=\"sigmoid\")(x)\n",
        "model = keras.Model(inputs, outputs)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FvHRsMebChh0"
      },
      "source": [
        "model.compile(optimizer=\"rmsprop\", loss=\"binary_crossentropy\",\n",
        "              metrics=[\"accuracy\"])\n",
        "callbacks = [keras.callbacks.ModelCheckpoint(\n",
        "    filepath=\"feature_extraction_with_data_aug.keras\",\n",
        "    save_best_only=True,\n",
        "    monitor=\"val_loss\"\n",
        ")]"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mf8AiWIcCqSQ",
        "outputId": "3dfe007f-7067-4324-ed0e-69a835d0835f"
      },
      "source": [
        "history = model.fit(\n",
        "    train_dataset,\n",
        "    epochs=50,\n",
        "    validation_data=val_dataset,\n",
        "    callbacks=callbacks\n",
        ")"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "63/63 [==============================] - 9s 114ms/step - loss: 26.6074 - accuracy: 0.8535 - val_loss: 23.1340 - val_accuracy: 0.8930\n",
            "Epoch 2/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 15.1188 - accuracy: 0.9010 - val_loss: 5.9117 - val_accuracy: 0.9530\n",
            "Epoch 3/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 11.6297 - accuracy: 0.9215 - val_loss: 7.3397 - val_accuracy: 0.9480\n",
            "Epoch 4/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 6.9439 - accuracy: 0.9370 - val_loss: 5.0533 - val_accuracy: 0.9560\n",
            "Epoch 5/50\n",
            "63/63 [==============================] - 7s 114ms/step - loss: 7.2974 - accuracy: 0.9355 - val_loss: 7.1139 - val_accuracy: 0.9500\n",
            "Epoch 6/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 6.0101 - accuracy: 0.9405 - val_loss: 7.0905 - val_accuracy: 0.9460\n",
            "Epoch 7/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 5.3390 - accuracy: 0.9410 - val_loss: 7.7873 - val_accuracy: 0.9460\n",
            "Epoch 8/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 4.4155 - accuracy: 0.9510 - val_loss: 6.8121 - val_accuracy: 0.9410\n",
            "Epoch 9/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 4.6193 - accuracy: 0.9400 - val_loss: 4.3289 - val_accuracy: 0.9570\n",
            "Epoch 10/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 3.1831 - accuracy: 0.9525 - val_loss: 5.0265 - val_accuracy: 0.9510\n",
            "Epoch 11/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 2.6048 - accuracy: 0.9535 - val_loss: 7.8944 - val_accuracy: 0.9300\n",
            "Epoch 12/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 2.6193 - accuracy: 0.9555 - val_loss: 4.1974 - val_accuracy: 0.9540\n",
            "Epoch 13/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 2.1992 - accuracy: 0.9585 - val_loss: 5.0298 - val_accuracy: 0.9480\n",
            "Epoch 14/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 2.4459 - accuracy: 0.9595 - val_loss: 3.4375 - val_accuracy: 0.9540\n",
            "Epoch 15/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 1.9207 - accuracy: 0.9640 - val_loss: 3.3204 - val_accuracy: 0.9560\n",
            "Epoch 16/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 1.9544 - accuracy: 0.9600 - val_loss: 2.9634 - val_accuracy: 0.9550\n",
            "Epoch 17/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 1.5516 - accuracy: 0.9550 - val_loss: 2.9601 - val_accuracy: 0.9460\n",
            "Epoch 18/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 1.2807 - accuracy: 0.9635 - val_loss: 2.1650 - val_accuracy: 0.9600\n",
            "Epoch 19/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 1.4772 - accuracy: 0.9575 - val_loss: 1.7904 - val_accuracy: 0.9580\n",
            "Epoch 20/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 1.2196 - accuracy: 0.9565 - val_loss: 1.8950 - val_accuracy: 0.9580\n",
            "Epoch 21/50\n",
            "63/63 [==============================] - 7s 111ms/step - loss: 0.8335 - accuracy: 0.9660 - val_loss: 1.8657 - val_accuracy: 0.9550\n",
            "Epoch 22/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.8789 - accuracy: 0.9640 - val_loss: 3.0707 - val_accuracy: 0.9450\n",
            "Epoch 23/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.9968 - accuracy: 0.9590 - val_loss: 1.8714 - val_accuracy: 0.9540\n",
            "Epoch 24/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 1.1005 - accuracy: 0.9585 - val_loss: 2.0947 - val_accuracy: 0.9500\n",
            "Epoch 25/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.8143 - accuracy: 0.9615 - val_loss: 1.3634 - val_accuracy: 0.9580\n",
            "Epoch 26/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.9028 - accuracy: 0.9610 - val_loss: 1.2930 - val_accuracy: 0.9540\n",
            "Epoch 27/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.5475 - accuracy: 0.9665 - val_loss: 1.2405 - val_accuracy: 0.9550\n",
            "Epoch 28/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.9265 - accuracy: 0.9590 - val_loss: 4.1544 - val_accuracy: 0.9110\n",
            "Epoch 29/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.8592 - accuracy: 0.9565 - val_loss: 1.3018 - val_accuracy: 0.9560\n",
            "Epoch 30/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.4493 - accuracy: 0.9690 - val_loss: 1.2629 - val_accuracy: 0.9570\n",
            "Epoch 31/50\n",
            "63/63 [==============================] - 7s 114ms/step - loss: 0.6700 - accuracy: 0.9645 - val_loss: 1.2725 - val_accuracy: 0.9640\n",
            "Epoch 32/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.6557 - accuracy: 0.9695 - val_loss: 1.3286 - val_accuracy: 0.9580\n",
            "Epoch 33/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.6449 - accuracy: 0.9695 - val_loss: 1.7265 - val_accuracy: 0.9600\n",
            "Epoch 34/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.7273 - accuracy: 0.9615 - val_loss: 1.1710 - val_accuracy: 0.9610\n",
            "Epoch 35/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.6835 - accuracy: 0.9655 - val_loss: 1.5814 - val_accuracy: 0.9590\n",
            "Epoch 36/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.5079 - accuracy: 0.9700 - val_loss: 1.6980 - val_accuracy: 0.9590\n",
            "Epoch 37/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.6322 - accuracy: 0.9670 - val_loss: 3.0502 - val_accuracy: 0.9380\n",
            "Epoch 38/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.9391 - accuracy: 0.9625 - val_loss: 1.9234 - val_accuracy: 0.9570\n",
            "Epoch 39/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.4683 - accuracy: 0.9755 - val_loss: 1.7960 - val_accuracy: 0.9600\n",
            "Epoch 40/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.6708 - accuracy: 0.9660 - val_loss: 1.8019 - val_accuracy: 0.9550\n",
            "Epoch 41/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 0.7431 - accuracy: 0.9670 - val_loss: 1.8810 - val_accuracy: 0.9550\n",
            "Epoch 42/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.6295 - accuracy: 0.9685 - val_loss: 2.2299 - val_accuracy: 0.9520\n",
            "Epoch 43/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.7455 - accuracy: 0.9740 - val_loss: 1.9087 - val_accuracy: 0.9540\n",
            "Epoch 44/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.5578 - accuracy: 0.9750 - val_loss: 2.0504 - val_accuracy: 0.9600\n",
            "Epoch 45/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.9013 - accuracy: 0.9640 - val_loss: 2.5018 - val_accuracy: 0.9590\n",
            "Epoch 46/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.5374 - accuracy: 0.9770 - val_loss: 2.0952 - val_accuracy: 0.9560\n",
            "Epoch 47/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.7680 - accuracy: 0.9695 - val_loss: 2.6350 - val_accuracy: 0.9610\n",
            "Epoch 48/50\n",
            "63/63 [==============================] - 7s 113ms/step - loss: 1.0955 - accuracy: 0.9680 - val_loss: 1.9552 - val_accuracy: 0.9580\n",
            "Epoch 49/50\n",
            "63/63 [==============================] - 7s 112ms/step - loss: 0.7047 - accuracy: 0.9700 - val_loss: 1.8356 - val_accuracy: 0.9570\n",
            "Epoch 50/50\n",
            "63/63 [==============================] - 7s 111ms/step - loss: 0.4678 - accuracy: 0.9775 - val_loss: 2.0908 - val_accuracy: 0.9590\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JD1_l60JCxyR",
        "outputId": "0afecec7-0a47-48d8-8233-845c8497cf67"
      },
      "source": [
        "test_model = keras.models.load_model(\"feature_extraction_with_data_aug.keras\")\n",
        "test_loss, test_acc = test_model.evaluate(test_dataset)\n",
        "print(\"Test loss: {}, test accuracy: {:.4f}\".format(test_loss, test_acc))"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "63/63 [==============================] - 5s 72ms/step - loss: 1.4112 - accuracy: 0.9690\n",
            "Test loss: 1.4112329483032227, test accuracy: 0.9690\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "pOTfTXdADwH_",
        "outputId": "609a3618-044f-46b3-a34f-1348c90607de"
      },
      "source": [
        "plot_loss(history)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "Aomw_H-2EPrI",
        "outputId": "c6ba825a-f4d9-4246-88ad-acd81940fcb6"
      },
      "source": [
        "plot_acc(history)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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a+6p2Ol91lcvXoIHqrbeqbtwYv7qFIpICjCUIXaxDaePxJj16tFMC334b/Pjdd7vrzppVMX3ePNVBg7TMNZafr/r006qrVweXy/eb9uyp+uab7o34wIHKn0NVIMuWqR53nCurc2fVrVsP7Xqx8txzFevdooXqBRc4y2rp0ujq9+23qocd5iy4n39WffFFp8Rbt1b94IOqyVVSorppU9XOVa3eCqKdnxJ4BCgEmnvn7vDcU3WBV4FrwpVnFkTiiGdUzKooldJS1XbtVAcOdIqiTh1X/pAhqtnZqQkfEa4Bj0VxhJL5UH3xX3/t7tPNN4fOs3eva3A7dFDduVN10SLVYcPKG78HHlDdvbvyeYH1e+459znyyNDPBKgOHRqd7MH4179cQ9qqlerf/65ar57quedW/S0+VjZuVD38cPe2v26d6tSp7ln0/51OPll17drQ19i9W/WEE9y9/f778vSlS93vUKeO6h//GH2dDh5UfeUVZ4mcdlrVFXC1dTEF5G8CFHrbJwMf+R27EngiXHmmIBJHPKNiVuXNeMkSl+/pp93+ihWq/fpVLrdePecyeewx93nyyUOzNMJZO5Ea8A8/rFx2LC6jQx3eO3iwarNmkfsYPvvMXfOYY9z1DzvMuXB27IiuHH/273dDau+/v/Knf383tPbAgdiuuW+f6o03Otn8XTFPPOHS7rsvdjmrwsUXO+v1m28qH1u92j1vTZs6i+uddyrnKS1VveIKd6+DHd+1S/Wyy1ydhgxR/fzz0PeqtFT1jTdUe/Rw+bt2VX3ppZqnIOoCq4HOfp3U3QPytATqeNuTgInedoaXv5W3/yxwQ7jyTEEkjnjHuonVt/7gg+7a69eXp8Xi62/TpmrWRTglEK4BX7TIbR91VNV9y5EUULh7+O67Lu+DD0ZX1u23u7fz8eNVt22rmryRmDLFyRRL38G6dap9+7rzAjtzS0tVr7zS1f/tt+Mvrz+vveZk+OMfw+f79ltnIYio3nuvc/34ePxxd42JE0OfX1rqFE29ei5v06bOSnroofI+j9mzVfv0KX++nn++YjlVISUKwpXLucC33mim8V7aRGCot30RsNLL80+ggd+5Z+OGvy4BpgD1w5WV7griq6/cwxTNqJRwxNrXkIwRRgMHqnbvXjEtnNJ68knVRo0qptWr59wCsRDO2gl3Ty6+WLVJE/c59ljXWRwrkVxYgccaNVIdN071zjudyygnx7mQoqG0NPY3+1hZuNDJ+eKL0eVfv161ZUvXSL78cvA8e/aonniic/34u2ziybZtqkcc4d7WoxlttGePs2JB9ZxzVLdscVZavXqq550XnftoyxZX57Fj3fMT+DLWsaPqP/8Zv9FPKVMQyfxUBwVRWlq1xiAe/OY37tccObLq1wjVKFV1hbHSUmeS79wZffmBymbPHmfa//a3FfOGa6BDHWvUSLWoKPZ7EmouR7B78sADLu8dd6h+8olL695ddfPm2MoNV3Y46ykjw/nC/Ye1Vgf27XON5O9/H13+yZNdfb78Mny+lSudK61XL9fpG2+uvtrd0/nzoz+ntFT1f/5HtX59p6zbtXP9M1W1zjZscL/9mDHOtRat4o8WUxBJ4u673aiRefOSX3bv3q5sqLrJHU9L4eOPnd/Zv9G6807V995zjX4goRrc3/3Obb/7bnT5w8VWAtWjj3Zvs/Eg2D254gonh08hzJnjfO+5ufEbdROuftEq41SQm6v6y19Gl3f0aNXmzaPzq7/xhqv7NdccmnyB+Fx1d9xRtfMLCpwl17Ch6oIF8ZUtnpiCSAJbtzqXAjizd9++5JW9Y4cbATFunOuw6tixag1FPOIeffGFM619vv8HHnC+7VNOKe/Url/fKY9PPy0/L5RyatrUvfkHezuM9Q27TRvVtm3dH/bf/479/kRi5Ur3OwRaO7Nnuzr37q26fXvFY/v2OWV6333ONRYNNXG2sapzvRxxRHR5e/Z0rsVo8U08GzbMKenAz6RJsblkdu1yjfsxxxyaZbJzZ+LcX/HCFEQSuPdedzd9M1fvvz95Zc+a5cqcM8c1uiJu5Ec44jWvwceCBaq/+pXL37Kl6yANtBR27nSy/u53rqE4/vjyN8Rwb8WDBsV2P8JZFxs3unK7dIlt1Ec0ea++2rnDfvih8rG33nIulr59nevpT39yitRfzsaNo69f/frB61ed+dvfnKyRRpb9/LOzhmN5cy8pccNOjzyy8icnx5Uby4S0W25x53zySfQy1FRMQSSYHTucOXz++W7/kkvcH3jp0uSUP26ca3x8DfLNN7sG95NPYhuTX9W+hhkzXN7mzd2bWjTWyzPPlCs11fB+9Ycfjv2ehHOJ+UbUfPRRdNeaNs1ZH599FjrP99+7Ri2cYn7ttYpDg7t3V73pJtXXX3eNIQSfdxAMX0eovwuwujNnjpN39uzw+f7v/1y+V1+NX9nTprlnOdKEtLVrVa+91j03N9wQv/KrM6YgqshHH7kx95H44x/dnSwocPubNrnJMKeccuhD0KLhlFPcvAAfPvO4bdvKo3kizep94YXyRqxFi8gNz+bNzmI46aTK7pNw/PyzO883eSqY0vK9JS9fHvMtCcvu3W68/5VXRs578KBz24E7J1T/0tixTkmvWxf+el9+6casB75FP/usK2P16qiqoHff7dxZyXi+4sVPP7k6PvBA+Hy+IaGR7mWsLF3qfstgE9I2bHAKoX599zvecEP0yrqmYwqiiuTkuBEI4UYm7d7tGrpzz62YPnWqu7uPPBI/eUKN8qlb11kR/vg62GL5iLhGHtyfpGnTyH/Syy93eZcsib0+48e7MletCl6/vDzXnxKvGD/+jBnj+iIiKbV33nH3449/dOEdmjev3OFYWOgaltGjqy6Pz034+efR5b/uOvc2XNPIznbPTDhGjnR1S8TvvnOn6qWXuns9ZIh7Afx//889CxkZznoINxu6NmIKooo0buzu0Omnh+7geughlyfQ/VBa6mazZmbGp5MqlFvI55oIjKejGruC6NTJ1cOn2DIz3djtUH/UN990eSdMqFqdNmxwyu3WWysf27/fvbFfe23Vrh2JggIn+z/+ET7f4MHOvbR3r/sdO3RwFpi/QrzlFte4fPfdocszc2Z0+c8/3/Wl1DSGDHGhIcLRvbt77hJFaanqo4+WT0irU8e57HwvKumGKYgqsH+/uzs9e7rvwJEpqqrFxa6z9ayzgl9j3To3sunssw/9bSiUj75ZM/eABwuNkJ0d/JxwaxM8/bTbX7XKxbwB578NZMcOt87A8ccf2oitESOcIgjst/jkE427H9qf0lI37LJXr9B5vvmmsgJcudJZla1bO9fXxo3u7fNQ5p+ouolh4Mb/R0O/fqpnnnloZaaC8eOdMi0uDn581y73PN97b+Jl+fxzp9zj7cKsaZiCqAKbN7u789hjqtdf77YDZ3T64uN/+GHo6/zjHy7PM88cmjzhRvmEqnq40S6hOnF/+1vX4JWUuE/fvk6hBE70GjPG/ZG/+OLQ6uXrkHzssYrpvoYk1oltseD7/UJNgvL5pAP7C775pnzI7IgR7j5E01cVjn37nCzRjn47+mgXu6em8fLLrp6h+nI+/tgdf+ut5MqVzpiCqALffuvuztSp7s978snOGvDFktm7172h/+IX4a2Dgwedi6p5c9U1a6ouTygLQsTNog6Fr/Mz2tEu557r3qx9fP21M8X9G6O5czWkVVUV+vZ1w079Ow3z8tywxESybZsblhpstEpRkXMxhlov4euvXd8TOCURD5o3jzw82cdhh4WP1Fpd8f2v/vnP4Mf/+ld3PBnh3A1HOAVha1KHYPt293344VC/Prz8MjRqBBdeCLt2wfPPQ2Eh3H23W+M3FHXqwD//6bbPPBM2bKiaPMHWvm3QwDX9p58e+rxRo+CEE+Dcc2HNGsjPD1/OsmXQrVv5fvfuro7Tp8Mbb0BxMVx7LRx5JEycWLW6BHLzzbByJbzzjtv/6Sf46iv45S/jc/1QHH44XHQRvPAC/PxzxWPPPAN79jjZgtG9O7z/PgweDPfdFx952rSBTZsi59u7F3budPlrGkcdBY0bw8KFwY8XFECHDjWzbrWSUJqjpn3ibUH4Rq/4z/adM8e5Ey66yI1o6dMn+r6FL75wo4KOOSb4RKpoCHQLXXyxkzFSgL4rr3T9BZHYvdtdLzDi5L59Lkplu3bOtQRVX9wkGPv2OXfNOee4/RdfdGUcqvsqGnzWkH8gv5IS9/sm2oIJ5PTT3QzzSKxb52R+6qmEi5QQTjnFrV8QjKOPDr4CnpE4MAsidoqK3Hfz5uVpZ54Jf/oTvPIKfP893HVXeOvBnz594O23nQUxcCBs3hy7TPn5zgooLXXfO3bA8cdDVlb483JzXbk//RQ+34oV7tvfggBnQT39NGzcCP/9386COOOM2OUPRf36cP318O67sHy5sySysqB37/iVEYr+/d1brc/KA3jrLff73nJL4sv3p3Xr6CwIX57WrRMrT6Lo0QMWLXLWrz/bt8OqVXDSSamRy6iMKYgQ+LuY/Pnd72DkSNfIDxkS2zVPPRX+8x/X+AwcCFu3Vl2+khL49NPw7iUfPXq470WLwudbtsx9ByoIcH/aCROcQnrwwZhEjYrrrnMus0cecYri7LMhIyP+5QQiAtdcAx995Nxc4GTo0AGGD098+f5E62LyvVzUVAWRm+tcZGvWVEz/6iv3nZeXdJGMEJiCCEEoBSECU6a4Rixa68Gf/v2dL//bb10j6CsnVhYscD7y/v0j583Ndd+h/L4+li+HunXh6KODH7/7bli8GJo1i03WaGjVCi6/3L3Jb9yY+P4Hf0aOdMromWdc/ebOhRtucPcimbRp456H/fvD56vpCsL3whL4PBYUuG9TENWHJP8Fag5FRe6NtmHD4Merohx8DBwIr78O55/vGsJ77gl+vZNPDu0++ugj933aaZHLa9kS2rePzoLo0gXq1Qud51DqHYlbboFnn3Xb55yTuHICadcOzjvPKf6NG91ghGuvTV75PnwN/pYt7vcKRU1XEMcf756jRYsqWmkFBc7dF/hSZqQOUxAh2L49sQ/q4MFuZNSFF8KvfhU8z1FHuT+Nfz+Ij48/do1527bRlZebG50F0b17dNdLBLm5Tnnu2OEa7WRyzTXOspsyBUaPhhYtkls+lI/c2bQpsoLIzIQmTZIjV7xp3BiOOaby8zhvHvTrlxqZjOCYgghBohUEwNChrj/ixx8rH1u7FkaMgF//GmbOdMNlfZSWwiefuCGa0dKjh3OL7dvnLKNA9u93HYQXXxx7PeLJ66+7/pVkc+65Ttn++GPooa2JxqcgIg1g2Ly55loPPnJz4csvy/c3b4Z161J3743gmIIIQVFR8Df3eJOd7T6BnHRSeWP15z/DnXeWH1uyxMkXTQe1j9xc1/AuWwY9e1Y+vnIlHDwIxx0Xex3iSareiuvWdXNNli1LnRXla/QjdVRv2lTzFUSPHjBjRvn/zNf/YCOYqhfWSR2CZFgQkbjxRtdxe9dd8N575ekff+y+Y1EQkUYyhRvBlC5cdVViRmhFi7+LKRy1xYIANygAnIIQCf7yYqQOUxAhSJYFEQ4RmDzZvdGOGOFMcHAd1J06uU+0HHWU81uH6odYtsyVd+yxhy63UTWaNHG/UTq4mAJHMs2b56zXpk1TJ5NRGVMQIUilBTFtGuTkuH6H7t3dMMwDB1yfw969zoKIxXoAN4zzxBNDWxDLl0Pnzm4Ej5E6Ik2WU3UKoqaHomjb1o2u802YKyiw4a3VEVMQQSgtdRZEohWEvyLIyXH706a5UTRr17o/ztq1cO+9cPXV7i3r/PPdMMhYFQSUj2QKnMEKlWMwGakh0mS5oiLXl1TTLQgRZ0UsXOhm+W/caP0P1ZGEKggRGSQiK0RklYiMC3K8k4jMEZHFIvKhiGQHHD9MRApF5PFEyhnI7t1OSSTSxRRMEYwe7eYCFBdXzFtc7Eb3jBsHs2e7NH8FEUzRBKNHD9fArF9fMb2kxE3cS3UHteEURDgXU02fA+FPbi4sXQqff+72zYKofiRMQYhIBvAEMBjoBowQkcB31IeA51X1RGAi8KeA4/cDHydKxlCEmkUdT8aPD64IQoXfWLcO7g+0X9oAACAASURBVL/fzRPo3NnNgYDQiiaYkgg1o/r7793wV7MgUk8kF1NNj8PkT48e7rmbNs2NIvM9n0b1IZEWRB9glaquVtX9wHRgWECebsAH3vZc/+Mi0htoA7ybQBmDkgwF4etwjpaOHd2faNYsF7PGN6M5lKIZP77yNU44oXwGqz/Ll7tvsyBST5s2zoVYWhr8eG2zIMAFRzz+eOv/qo4kUkG0B/ydGYVemj+LgAu87eFAUxHJEpE6wF+B28IVICKjRaRARAq2bNkSJ7GDR3KNNx07Bk/Pyqq87kNmphujDy4Mhr/iCqVogqU3aeLiLAVaEL4hrqYgUk+bNm4+yrZtwY/XJgXRtauL5HvwoPU/VFdS3Ul9G9BfRBYA/YENwEHgemCWqhaGO1lVJ6tqnqrmtWrVKm5CJcOCCLYAUGamiyQ6ebIbwirividPDr3QTyhFEyrdF2rZn+XLXWiHww6LrQ5G/Ik0WW7zZvdctGyZPJkSRb165ZMSrf+hepJIBbEB6OC3n+2llaGqP6jqBaraExjvpRUBpwA3isgaXD/Fr0XkzwmUtQJVsSCi7Sj2kZ8fWhEErvsQbhW4UIrGZ3EEkpsL333nwi37sBFM1YdIk+U2b3ZWZrIjzSYK33wIsyCqJ4lUEPOALiLSWUTqA5cBb/hnEJGWnjsJ4A7gGQBVzVfVjqqag7MynlfVSqOgEkWsFkQsHcX+xKIIwl0jFovD94dcssR9l5Y6C8LcS9WDSPGYasMkOX+GDXPK4fjjUy2JEYyEKQhVLQFuBGYDy4EZqrpURCaKyFAv2wBghYh8i+uQDvHem1y2b3eWQLSzOiN1FMdqXcRKLIomcCRTYaFbV8IsiOpBJBdTbYjD5M+wYS5oX7gQ80bqSKihqqqzgFkBaff4bb8CvBLhGlOAKQkQLyRFRW5RnDpRqs9wHcU+68KnQHzWBVTNYjhU2rd3LgpfP4R1UFcvDj/cuY/CuZh8VqBhJJpUd1JXS2INsxGuoziWYajJQKTi2hC+Ia5mQVQP6tRxFkK6uJiM6o0piCDEqiDCdRTHMgw1WfTo4fogfOG/W7WqHaNiaguhJsvt3++s25oeh8moOZiCCEKskVzDdRTHOgw1GeTmuqB/K1daB3V1JFQ8Jt9UH7MgjGRhCiIIVYnkGqqjONZhqMnAP9SyDXGtfoSKx1SbJskZNQNTEEGI51oQsQ5DTQZdu7pRI+++65ShWRDVC5+LKTDqbm2Kw2TUDGrJdJv4Eu+1IHyT36oL9eu7Gayvveb2zYKoXrRp41yAu3ZVnN1uFoSRbMyCCGDvXvdJ9XKjiSY3t3w2tVkQ1YtQk+VMQRjJxhREAMkI1Fcd8PVDHHYYtGuXWlmMioSaLLd5MzRsaMtyGsnDFEQAyQjUVx3wzag+7rjy0OFG9SBUPCbfHAj7vYxkYQoigHRTENb/UP0I52Iy95KRTKyTOoB0cTG1aOHWuj7nnFRLYgTim7QYaEFs2gRHHJF8eYz0xRREAOliQQBMmJBqCYxg1Kvn4mUFczGdeGJqZDLSE3MxBZAuFoRRvQmcLKfq9i3MhpFMIioIEfmV35oNtZ50siCM6ktgPKadO10sJuuDMJJJNA3/pcBKEfmLiHRNtECpZvt2aNzY4tMbqSUwHpPNgTBSQUQFoapXAD2B74ApIvK5iIwWkVo5GjueYTYMo6oEuphMQRipICrXkaruxC3sMx1oCwwH5ovITQmULSXEO8yGYVSF1q1hxw43qx8sDpORGqLpgxgqIq8DHwL1gD6qOhjIBX6bWPGSjykIozoQOBfCLAgjFUQzzPVC4O+q+rF/oqoWi8g1iRErdRQVQYcOqZbCSHf8Z1N37FiuIFq1Sp1MRvoRjYtpAvClb0dEGolIDoCqzkmIVCnELAijOuCzFPwtiBYtbPCEkVyiURAvA6V++we9tFrJ9u3WSW2knsB4TBZmw0gF0SiIuqq637fjbddPnEip4+BBN948nAUxbRrk5LjF5XNy3L5hxJvAiK6mIIxUEI2C2CIiQ307IjIM+ClxIqWOHTvcdygFMW0ajB4Na9e6ma1r17p9UxJGvMnMhCZNyl1MmzaZgjCSTzQKYgxwp4isE5H1wO+B66K5uIgMEpEVIrJKRMYFOd5JROaIyGIR+VBEsr30Ht58i6XesUtjqVRViRRmY/x4KC6umFZc7NINI974T5YzC8JIBRFHManqd8DJItLE298dzYVFJAN4AjgbKATmicgbqrrML9tDwPOq+pyInAn8CbgSKAZ+raorRaQd8JWIzFbVolgqFyuRwmysWxdbumEcCj4FceAAbNtmcZiM5BNVNFcROQ/oDjQUb7USVZ0Y4bQ+wCpVXe1dYzowDPBXEN2A/+dtzwVmetf+1pdBVX8Qkc1AKyClCqJjR+dWCpZuGPGmdWtYtQp++ql83zCSSTQT5f4bF4/pJkCAi4FOUVy7PbDeb7/QS/NnEXCBtz0caCoiWQHl98F1in8XRLbRIlIgIgVbtmyJQqTwRHIxTZrkfMP+ZGa6dMOINz4LwibJGakimj6Ifqr6a2C7qt4HnAIcE6fybwP6i8gCoD+wATeMFgARaQtMBa5S1dLAk1V1sqrmqWpeqzjMIIpkQeTnw+TJ0KmTW/axUye3n59/yEUbRiXatHHWww8/uH1TEEayicbF5EWDodjrD9iKi8cUiQ2A/5zkbC+tDFX9Ac+C8Po4LvT1M4jIYcB/gPGq+n9RlHfI+BREuHkQ+fmmEIzk0Lq1Gy23bFn5vmEkk2gsiDdFpDnwIDAfWAO8GMV584AuItJZROoDlwFv+GcQkZZ+a03cATzjpdcHXsd1YL8STUXiQVER1K3rwn0bRqrxdUovWVJx3zCSRVgF4TXec1S1SFVfxfU9dFXVeyJdWFVLgBuB2cByYIaqLhWRiX7zKgYAK0TkW6AN4PPmXwKcDowSkYXep0cV6hcTvjAbXj+8YaQUfwVRvz4cdlhq5THSj7AuJlUtFZEncOtBoKr7gH3RXlxVZwGzAtLu8dt+BRdGPPC8F4AXoi0nXthaEEZ1wudSWrbMbduLi5FsonExzRGRC0Vq/+NpgfqM6oTPgti71/ofjNQQjYK4Dhecb5+I7BSRXSKyM8FypQRTEEZ1olkz51oCUxBGaohmydGmqlpHVeur6mHefq30hpqLyahOiJQrBlMQRiqIOMxVRE4Plh64gFBtwCwIo7rRpg0UFtoIJiM1RDMP4nd+2w1xITS+As5MiEQpQtXWgjCqHz7FYBaEkQqiCdb3K/99EekAPJwwiVJEcTGUlJgFYVQvzMVkpJJoOqkDKQSOi7cgqSZSmA3DSAVmQRipJJo+iMcA9XbrAD1wM6prFZEC9RlGKjAFYaSSaPogCvy2S4B/qeqnCZInZZgFYVRH+vaFo45yH8NINtEoiFeAvap6ENxCQCKSqarFEc6rUZiCMKoj/fq5NSEMIxVENZMaaOS33wh4PzHipA5zMRmGYVQkGgXR0H+ZUW87M0z+GolZEIZhGBWJRkHsEZFevh0R6Q38nDiRUoNPQTRrllo5DMMwqgvR9EHcCrwsIj/glhw9ArcEaa2iqMiFU87ISLUkhmEY1YNoJsrNE5GuwLFe0gpVPZBYsZKPhdkwDMOoSEQXk4jcADRW1a9V9WugiYhcn3jRkouF2TAMw6hINH0Q1/rWiQZQ1e3AtYkTKTUUFZkFYRiG4U80CiLDf7EgEckA6idOpNRgLibDMIyKRNNJ/Q7wkoj8j7d/HfB24kRKDbYWhGEYRkWiURC/B0YDY7z9xbiRTLUKsyAMwzAqEs2KcqXAF8Aa3FoQZwLLEytWcjlwAPbsMQvCMAzDn5AKQkSOEZF7ReQb4DFgHYCqnqGqjydLwGTgC7Phb0FMmwY5OVCnjvueNi0VkhmGYaSOcC6mb4BPgCGqugpARH6TFKmSTGCYjWnTYPRot4gQwNq1bh8gPz/58hmGYaSCcC6mC4Afgbki8pSInIWbSR01IjJIRFaIyCoRGRfkeCcRmSMii0XkQxHJ9js2UkRWep+RsZQbKz4F4XMxjR9frhx8FBe7dMMwjHQhpIJQ1ZmqehnQFZiLC7nRWkSeFJFzIl3YGw77BDAY6AaMEJFuAdkeAp5X1ROBicCfvHNbAPcCfXH9HveKSMK6kANdTOvWBc8XKt0wDKM2Ek0n9R5VfdFbmzobWIAb2RSJPsAqVV2tqvuB6cCwgDzdgA+87bl+x38JvKeq27yJee8Bg6Ios0oEupg6dgyeL1S6YRhGbSSmNalVdbuqTlbVs6LI3h5Y77df6KX5swjnygIYDjQVkawoz0VERotIgYgUbNmyJdpqVCJwLYhJkyAzIKB5ZqZLNwzDSBdiUhAJ4Dagv4gsAPoDG4CD0Z7sKas8Vc1r1apVlYUItCDy82HyZOjUCUTc9+TJ1kFtGEZ6Ec1EuaqyAejgt5/tpZWhqj/gWRAi0gS4UFWLRGQDMCDg3A8TJej27dCgATRsWJ6Wn28KwTCM9CaRFsQ8oIuIdBaR+sBlwBv+GUSkpYj4ZLgDeMbbng2cIyKHe53T53hpCcEC9RmGYVQmYQpCVUuAG3EN+3JghqouFZGJIjLUyzYAWCEi3wJtgEneuduA+3FKZh4w0UtLCBZmwzAMozKiqqmWIS7k5eVpQUFBlc4dONDNc/jsszgLZRiGUc0Rka9UNS/YsVR3UlcLzMVkGIZRGVMQmIvJMAwjGKYgsLUgDMMwgpH2CqK01FxMhmEYwUh7BbFrl1MSZkEYhmFUJO0VREkJDBsGxx2XakkMwzCqF4mcSV0jyMqCmTNTLYVhGEb1I+0tCMMwDCM4piAMwzCMoJiCMAzDMIJiCsIwDMMIiikIwzAMIyimIAzDMIygmIIwDMMwgmIKwjAMwwiKKQjDMAwjKKYgDMMwjKCYgjAMwzCCYgrCMAzDCIopCMMwDCMopiAMwzCMoJiCMAzDMIJiCsIwDMMISkIVhIgMEpEVIrJKRMYFOd5RROaKyAIRWSwi53rp9UTkORFZIiLLReSORMppGIZhVCZhCkJEMoAngMFAN2CEiHQLyHYXMENVewKXAf/w0i8GGqjqCUBv4DoRyUmUrIZhGEZlEmlB9AFWqepqVd0PTAeGBeRR4DBvuxnwg196YxGpCzQC9gM7EyirYRiGEUAiFUR7YL3ffqGX5s8E4AoRKQRmATd56a8Ae4AfgXXAQ6q6LbAAERktIgUiUrBly5Y4i28YhpHepLqTegQwRVWzgXOBqSJSB2d9HATaAZ2B34rIkYEnq+pkVc1T1bxWrVolU27DMIxaTyIVxAagg99+tpfmzzXADABV/RxoCLQELgfeUdUDqroZ+BTIS6CshmEYRgCJVBDzgC4i0llE6uM6od8IyLMOOAtARI7DKYgtXvqZXnpj4GTgmwTKahiGYQSQMAWhqiXAjcBsYDlutNJSEZkoIkO9bL8FrhWRRcC/gFGqqrjRT01EZClO0TyrqosTJathGIZRGXHtcc0nLy9PCwoKUi2GYRhGjUJEvlLVoC78VHdSG4ZhGNUUUxCGYRhGUExBGIZhGEExBWEYhmEExRSEYRiGERRTEIZhGEZQTEEYhmEYQTEFYRiGYQSlbqoFMAwj/hw4cIDCwkL27t2balGMakLDhg3Jzs6mXr16UZ9jCsIwaiGFhYU0bdqUnJwcRCTV4hgpRlXZunUrhYWFdO7cOerzzMVkGLWQvXv3kpWVZcrBAEBEyMrKitmiNAVhGLUUUw6GP1V5HkxBGIZhGEExBWEYBtOmQU4O1KnjvqdNO7Trbd26lR49etCjRw+OOOII2rdvX7a/f//+sOcWFBRw8803RyyjX79+hyakERHrpDaMNGfaNBg9GoqL3f7atW4fID+/atfMyspi4cKFAEyYMIEmTZpw2223lR0vKSmhbt3gzU9eXh55eZEXkPzss8+qJlwKOXjwIBkZGakWI2rMgjCMNGf8+HLl4KO42KXHk1GjRjFmzBj69u3L7bffzpdffskpp5xCz5496devHytWrADgww8/ZMiQIYBTLldffTUDBgzgyCOP5NFHHy27XpMmTcryDxgwgIsuuoiuXbuSn5+Pb52bWbNm0bVrV3r37s3NN99cdl1/1qxZw2mnnUavXr3o1atXBcXzwAMPcMIJJ5Cbm8u4ceMAWLVqFQMHDiQ3N5devXrx3XffVZAZ4MYbb2TKlCkA5OTk8Pvf/55evXrx8ssv89RTT3HSSSeRm5vLhRdeSLF38zdt2sTw4cPJzc0lNzeXzz77jHvuuYeHH3647Lrjx4/nkUceOeTfIlrMgjCMNGfdutjSD4XCwkI+++wzMjIy2LlzJ5988gl169bl/fff58477+TVV1+tdM4333zD3Llz2bVrF8ceeyxjx46tNJZ/wYIFLF26lHbt2nHqqafy6aefkpeXx3XXXcfHH39M586dGTFiRFCZWrduzXvvvUfDhg1ZuXIlI0aMoKCggLfffpt///vffPHFF2RmZrJt2zYA8vPzGTduHMOHD2fv3r2Ulpayfv36sPXOyspi/vz5gHO/XXvttQDcddddPP3009x0003cfPPN9O/fn9dff52DBw+ye/du2rVrxwUXXMCtt95KaWkp06dP58svv4z5vlcVUxCGkeZ07OjcSsHS483FF19c5mLZsWMHI0eOZOXKlYgIBw4cCHrOeeedR4MGDWjQoAGtW7dm06ZNZGdnV8jTp0+fsrQePXqwZs0amjRpwpFHHlk27n/EiBFMnjy50vUPHDjAjTfeyMKFC8nIyODbb78F4P333+eqq64iMzMTgBYtWrBr1y42bNjA8OHDATf5LBouvfTSsu2vv/6au+66i6KiInbv3s0vf/lLAD744AOef/55ADIyMmjWrBnNmjUjKyuLBQsWsGnTJnr27ElWVlZUZcYDUxCGkeZMmlSxDwIgM9Olx5vGjRuXbd99992cccYZvP7666xZs4YBAwYEPadBgwZl2xkZGZSUlFQpTyj+/ve/06ZNGxYtWkRpaWnUjb4/devWpbS0tGw/cL6Bf71HjRrFzJkzyc3NZcqUKXz44Ydhr/1f//VfTJkyhY0bN3L11VfHLNuhYH0QhpHm5OfD5MnQqROIuO/Jk6veQR0tO3bsoH379gBl/vp4cuyxx7J69WrWrFkDwEsvvRRSjrZt21KnTh2mTp3KwYMHATj77LN59tlny/oItm3bRtOmTcnOzmbmzJkA7Nu3j+LiYjp16sSyZcvYt28fRUVFzJkzJ6Rcu3btom3bthw4cIBpfsPFzjrrLJ588knAdWbv2LEDgOHDh/POO+8wb968MmsjWZiCMAyD/HxYswZKS913opUDwO23384dd9xBz549Y3rjj5ZGjRrxj3/8g0GDBtG7d2+aNm1Ks2bNKuW7/vrree6558jNzeWbb74pe9sfNGgQQ4cOJS8vjx49evDQQw8BMHXqVB599FFOPPFE+vXrx8aNG+nQoQOXXHIJxx9/PJdccgk9e/YMKdf9999P3759OfXUU+natWtZ+iOPPMLcuXM54YQT6N27N8uWLQOgfv36nHHGGVxyySVJHwElvt7+mk5eXp4WFBSkWgzDqBYsX76c4447LtVipJzdu3fTpEkTVJUbbriBLl268Jvf/CbVYsVEaWlp2QioLl26HNK1gj0XIvKVqgYdV5xQC0JEBonIChFZJSLjghzvKCJzRWSBiCwWkXP9jp0oIp+LyFIRWSIisTsGDcNIa5566il69OhB9+7d2bFjB9ddd12qRYqJZcuWcfTRR3PWWWcdsnKoCgmzIEQkA/gWOBsoBOYBI1R1mV+eycACVX1SRLoBs1Q1R0TqAvOBK1V1kYhkAUWqejBUeWZBGEY5ZkEYwahOFkQfYJWqrlbV/cB0YFhAHgUO87abAT942+cAi1V1EYCqbg2nHAzDMIz4k0gF0R7wnz1S6KX5MwG4QkQKgVnATV76MYCKyGwRmS8itydQTsMwDCMIqR7FNAKYoqrZwLnAVBGpg5uf8Qsg3/seLiJnBZ4sIqNFpEBECrZs2ZJMuQ3DMGo9iVQQG4AOfvvZXpo/1wAzAFT1c6Ah0BJnbXysqj+pajHOuugVWICqTlbVPFXNa9WqVQKqYBiGkb4kUkHMA7qISGcRqQ9cBrwRkGcdcBaAiByHUxBbgNnACSKS6XVY9weWYRhGjeCMM85g9uzZFdIefvhhxo4dG/KcAQMG4Btocu6551JUVFQpz4QJE8rmI4Ri5syZZXMIAO655x7ef//9WMQ3PBKmIFS1BLgR19gvB2ao6lIRmSgiQ71svwWuFZFFwL+AUerYDvwNp2QWAvNV9T+JktUwjPgyYsQIpk+fXiFt+vTpIQPmBTJr1iyaN29epbIDFcTEiRMZOHBgla6VKnyzuVNNQmMxqeosnHvIP+0ev+1lwKkhzn0BeCGR8hlGOnDrreAtzRA3evQAvyjUlbjooou466672L9/P/Xr12fNmjX88MMPnHbaaYwdO5Z58+bx888/c9FFF3HfffdVOj8nJ4eCggJatmzJpEmTeO6552jdujUdOnSgd+/egJvjMHnyZPbv38/RRx/N1KlTWbhwIW+88QYfffQRf/jDH3j11Ve5//77GTJkCBdddBFz5szhtttuo6SkhJNOOoknn3ySBg0akJOTw8iRI3nzzTc5cOAAL7/8coVZzuDCgl955ZXs2bMHgMcff7xs0aIHHniAF154gTp16jB48GD+/Oc/s2rVKsaMGcOWLVvIyMjg5ZdfZv369Tz00EO89dZbgAsLnpeXx6hRo8jJyeHSSy/lvffe4/bbb2fXrl2V6peZmcmmTZsYM2YMq1evBuDJJ5/knXfeoUWLFtx6662ACwveunVrbrnllkP6nVPdSW0YRi2kRYsW9OnTh7fffhtw1sMll1yCiDBp0iQKCgpYvHgxH330EYsXLw55na+++orp06ezcOFCZs2axbx588qOXXDBBcybN49FixZx3HHH8fTTT9OvXz+GDh3Kgw8+yMKFCznqqKPK8u/du5dRo0bx0ksvsWTJEkpKSspiHwG0bNmS+fPnM3bs2KBuLF9Y8Pnz5/PSSy+VrXrnHxZ80aJF3H67G3SZn5/PDTfcwKJFi/jss89o27ZtxPvmCwt+2WWXBa0fUBYWfNGiRcyfP5/u3btz9dVXl0WC9YUFv+KKKyKWFwmL5moYtZxwb/qJxOdmGjZsGNOnTy9r4GbMmMHkyZMpKSnhxx9/ZNmyZZx44olBr/HJJ58wfPjwspDbQ4cOLTsWKmx2KFasWEHnzp055phjABg5ciRPPPFE2Vv3BRdcAEDv3r157bXXKp2fjmHB096CiPdavIZhOIYNG8acOXOYP38+xcXF9O7dm++//56HHnqIOXPmsHjxYs4777xKobGjZdSoUTz++OMsWbKEe++9t8rX8eELGR4qXLh/WPCCgoKIa2sHI9aw4LHUzxcW/Nlnn41bWPC0VhC+tXjXrgXV8rV4TUkYxqHTpEkTzjjjDK6++uqyzumdO3fSuHFjmjVrxqZNm8pcUKE4/fTTmTlzJj///DO7du3izTffLDsWKmx206ZN2bVrV6VrHXvssaxZs4ZVq1YBLipr//79o65POoYFT2sFkay1eA0jXRkxYgSLFi0qUxC5ubn07NmTrl27cvnll3PqqUHHqJTRq1cvLr30UnJzcxk8eDAnnXRS2bFQYbMvu+wyHnzwQXr27Ml3331Xlt6wYUOeffZZLr74Yk444QTq1KnDmDFjoq5LOoYFT+tw33XqOMshEBEXF98waioWrC/9iCYseHUK1lftCbXmbiLW4jUMw0gUiQoLntajmJK5Fq9hGEai6NatW9m8iHiS1hZEqtbiNYxkUFvcx0Z8qMrzkNYWBDhlYArBqG00bNiQrVu3kpWVhYikWhwjxagqW7dujXo+ho+0VxCGURvJzs6msLAQC4Nv+GjYsCHZ2dkxnWMKwjBqIfXq1aNz586pFsOo4aR1H4RhGIYRGlMQhmEYRlBMQRiGYRhBqTUzqUVkC7A2QraWwE9JEKc6kq51t3qnF1bv2OmkqkHXbK41CiIaRKQg1JTy2k661t3qnV5YveOLuZgMwzCMoJiCMAzDMIKSbgpicqoFSCHpWnerd3ph9Y4jadUHYRiGYURPulkQhmEYRpSYgjAMwzCCkjYKQkQGicgKEVklIuNSLU+iEJFnRGSziHztl9ZCRN4TkZXe9+GplDERiEgHEZkrIstEZKmI3OKl1+q6i0hDEflSRBZ59b7PS+8sIl94z/tLIlI/1bImAhHJEJEFIvKWt58u9V4jIktEZKGIFHhpcX/W00JBiEgG8AQwGOgGjBCRbqmVKmFMAQYFpI0D5qhqF2COt1/bKAF+q6rdgJOBG7zfuLbXfR9wpqrmAj2AQSJyMvAA8HdVPRrYDlyTQhkTyS3Acr/9dKk3wBmq2sNv/kPcn/W0UBBAH2CVqq5W1f3AdGBYimVKCKr6MbAtIHkY8Jy3/RxwflKFSgKq+qOqzve2d+EajfbU8rqrY7e3W8/7KHAm8IqXXuvqDSAi2cB5wD+9fSEN6h2GuD/r6aIg2gPr/fYLvbR0oY2q/uhtbwTapFKYRCMiOUBP4AvSoO6em2UhsBl4D/gOKFLVEi9LbX3eHwZuB0q9/SzSo97gXgLeFZGvRGS0lxb3Z93Wg0gzVFVFpNaObRaRJsCrwK2qutN/NbXaWndVPQj0EJHmwOtA1xSLlHBEZAiwWVW/EpEBqZYnBfxCVTeISGvgPRH5xv9gvJ71dLEgNgAd/PazvbR0YZOItAXwvjenWJ6EICL1cMphmqq+5iWnRd0BVLUImAucAjQXEd8LYG183k8FhorIGpzL+EzgEWp/vQFQ1Q3e92bcS0EfEvCsp4uCmAd08UY41AcuA95IsUzJ5A1gpLc9Evh3CmVJCJ7/+Wlguar+ze9Qra67iLTyLAdEpBFwRifxfQAAAq1JREFUNq7/ZS5wkZet1tVbVe9Q1WxVzcH9nz9Q1Xxqeb0BRKSxiDT1bQPnAF+TgGc9bWZSi8i5OJ9lBvCMqk5KsUgJQUT+BQzAhf/dBNwLzARmAB1xIdEvUdXAjuwajYj8AvgEWEK5T/pOXD9Era27iJyI65DMwL3wzVDViSJyJO7NugWwALhCVfelTtLE4bmYblPVIelQb6+Or3u7dYEXVXWSiGQR52c9bRSEYRiGERvp4mIyDMMwYsQUhGEYhhEUUxCGYRhGUExBGIZhGEExBWEYhmEExRSEYURARA56UTN9n7gF/BORHP/Iu4ZRnbBQG4YRmZ9VtUeqhTCMZGMWhGFUES8m/1+8uPxfisjRXnqOiHwgIotFZI6IdPTS24jI697aDYtEpJ93qQwRecpbz+Fdb0Y0InKzt77FYhGZnqJqGmmMKQjDiEyjABfTpX7HdqjqCcDjuJn6AI8Bz6nqicA04FEv/VHgI2/thl7AUi+9C/CEqnYHioALvfRxQE/vOmMSVTnDCIXNpDaMCIjIblVtEiR9DW6xntVeoMCNqpolIj8BbVX1gJf+o6q2FJEtQLZ/6AcvNPl73iIviMjvgXqq+gcReQfYjQuVMtNv3QfDSApmQRjGoaEhtmPBP1bQQcr7Bs/DrYTYC5jnF6XUMJKCKQjDODQu9fv+3Nv+DBdhFCAfF0QQ3DKQY6FskZ9moS4qInWADqo6F/g90AyoZMUYRiKxNxLDiEwjb8U2H++oqm+o6+EishhnBYzw0m4CnhWR3wFbgKu89FuAySJyDc5SGAv8SHAygBc8JSLAo956D4aRNKwPwjCqiNcHkaeqP6VaFsNIBOZiMgzDMIJiFoRhGIYRFLMgDMMwjKCYgjAMwzCCYgrCMAzDCIopCMMwDCMopiAMwzCMoPx/JAQavopxCvcAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b0gtdBE8Empi",
        "outputId": "90ae72ec-8049-4fd0-d83d-91b021294812"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"model_3\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_6 (InputLayer)         [(None, 180, 180, 3)]     0         \n",
            "_________________________________________________________________\n",
            "sequential_1 (Sequential)    (None, 180, 180, 3)       0         \n",
            "_________________________________________________________________\n",
            "vgg16 (Functional)           (None, None, None, 512)   14714688  \n",
            "_________________________________________________________________\n",
            "flatten_3 (Flatten)          (None, 12800)             0         \n",
            "_________________________________________________________________\n",
            "dense_4 (Dense)              (None, 256)               3277056   \n",
            "_________________________________________________________________\n",
            "dropout_2 (Dropout)          (None, 256)               0         \n",
            "_________________________________________________________________\n",
            "dense_5 (Dense)              (None, 1)                 257       \n",
            "=================================================================\n",
            "Total params: 17,992,001\n",
            "Trainable params: 3,277,313\n",
            "Non-trainable params: 14,714,688\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tKH41SosG-Vm"
      },
      "source": [
        "vgg16_frozen.trainable = True\n",
        "for layer in vgg16_frozen.layers[:-4]:\n",
        "    layer.trainable = False"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HDCDwqxlNFbH"
      },
      "source": [
        "model.compile(optimizer=keras.optimizers.RMSprop(learning_rate=1e-5), \n",
        "              loss=\"binary_crossentropy\",\n",
        "              metrics=[\"accuracy\"])\n",
        "\n",
        "callbacks = [keras.callbacks.ModelCheckpoint(\n",
        "    filepath=\"fine_tuning.keras\",\n",
        "    save_best_only=True,\n",
        "    monitor=\"val_loss\"\n",
        ")]"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EJBamknJNO-n",
        "outputId": "3c8b0af0-9058-4491-b8a7-d6aae6b995d5"
      },
      "source": [
        "history = model.fit(train_dataset,\n",
        "                    epochs=30,\n",
        "                    validation_data=val_dataset,\n",
        "                    callbacks=callbacks)"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/30\n",
            "63/63 [==============================] - 9s 124ms/step - loss: 0.6164 - accuracy: 0.9720 - val_loss: 1.9829 - val_accuracy: 0.9570\n",
            "Epoch 2/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.3948 - accuracy: 0.9765 - val_loss: 1.8667 - val_accuracy: 0.9590\n",
            "Epoch 3/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.3756 - accuracy: 0.9785 - val_loss: 1.6108 - val_accuracy: 0.9620\n",
            "Epoch 4/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.3501 - accuracy: 0.9785 - val_loss: 1.6660 - val_accuracy: 0.9590\n",
            "Epoch 5/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.2805 - accuracy: 0.9815 - val_loss: 2.1984 - val_accuracy: 0.9440\n",
            "Epoch 6/30\n",
            "63/63 [==============================] - 8s 119ms/step - loss: 0.3039 - accuracy: 0.9815 - val_loss: 1.5272 - val_accuracy: 0.9610\n",
            "Epoch 7/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.2562 - accuracy: 0.9825 - val_loss: 1.4831 - val_accuracy: 0.9650\n",
            "Epoch 8/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.2667 - accuracy: 0.9840 - val_loss: 1.5032 - val_accuracy: 0.9650\n",
            "Epoch 9/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.2067 - accuracy: 0.9870 - val_loss: 1.4830 - val_accuracy: 0.9630\n",
            "Epoch 10/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1804 - accuracy: 0.9860 - val_loss: 1.3759 - val_accuracy: 0.9650\n",
            "Epoch 11/30\n",
            "63/63 [==============================] - 8s 121ms/step - loss: 0.1008 - accuracy: 0.9925 - val_loss: 1.3276 - val_accuracy: 0.9670\n",
            "Epoch 12/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1837 - accuracy: 0.9875 - val_loss: 1.4587 - val_accuracy: 0.9610\n",
            "Epoch 13/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1889 - accuracy: 0.9885 - val_loss: 1.2873 - val_accuracy: 0.9670\n",
            "Epoch 14/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1297 - accuracy: 0.9895 - val_loss: 1.3166 - val_accuracy: 0.9620\n",
            "Epoch 15/30\n",
            "63/63 [==============================] - 8s 119ms/step - loss: 0.1748 - accuracy: 0.9885 - val_loss: 1.6769 - val_accuracy: 0.9520\n",
            "Epoch 16/30\n",
            "63/63 [==============================] - 8s 119ms/step - loss: 0.1067 - accuracy: 0.9865 - val_loss: 1.4171 - val_accuracy: 0.9610\n",
            "Epoch 17/30\n",
            "63/63 [==============================] - 8s 121ms/step - loss: 0.1493 - accuracy: 0.9880 - val_loss: 1.3479 - val_accuracy: 0.9650\n",
            "Epoch 18/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1271 - accuracy: 0.9905 - val_loss: 1.1729 - val_accuracy: 0.9680\n",
            "Epoch 19/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0778 - accuracy: 0.9930 - val_loss: 1.2547 - val_accuracy: 0.9650\n",
            "Epoch 20/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1002 - accuracy: 0.9915 - val_loss: 1.1527 - val_accuracy: 0.9720\n",
            "Epoch 21/30\n",
            "63/63 [==============================] - 8s 121ms/step - loss: 0.0540 - accuracy: 0.9920 - val_loss: 1.2701 - val_accuracy: 0.9660\n",
            "Epoch 22/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0952 - accuracy: 0.9905 - val_loss: 1.6494 - val_accuracy: 0.9650\n",
            "Epoch 23/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0757 - accuracy: 0.9915 - val_loss: 1.3399 - val_accuracy: 0.9640\n",
            "Epoch 24/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0570 - accuracy: 0.9930 - val_loss: 1.2073 - val_accuracy: 0.9640\n",
            "Epoch 25/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0631 - accuracy: 0.9955 - val_loss: 1.1628 - val_accuracy: 0.9670\n",
            "Epoch 26/30\n",
            "63/63 [==============================] - 8s 121ms/step - loss: 0.0856 - accuracy: 0.9950 - val_loss: 1.1532 - val_accuracy: 0.9650\n",
            "Epoch 27/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.1185 - accuracy: 0.9910 - val_loss: 1.2601 - val_accuracy: 0.9660\n",
            "Epoch 28/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0684 - accuracy: 0.9935 - val_loss: 1.9142 - val_accuracy: 0.9570\n",
            "Epoch 29/30\n",
            "63/63 [==============================] - 8s 119ms/step - loss: 0.1008 - accuracy: 0.9925 - val_loss: 1.3296 - val_accuracy: 0.9650\n",
            "Epoch 30/30\n",
            "63/63 [==============================] - 8s 120ms/step - loss: 0.0521 - accuracy: 0.9940 - val_loss: 1.3231 - val_accuracy: 0.9690\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x_9s6ElCNVRI",
        "outputId": "60ba5d29-eb16-4df4-d8e8-94c5f2d9d84c"
      },
      "source": [
        "test_model = keras.models.load_model(\"fine_tuning.keras\")\n",
        "test_loss, test_acc = test_model.evaluate(test_dataset)\n",
        "print(\"Test loss: {}, test accuracy: {:.4f}\".format(test_loss, test_acc))"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "63/63 [==============================] - 5s 72ms/step - loss: 1.2070 - accuracy: 0.9705\n",
            "Test loss: 1.206950306892395, test accuracy: 0.9705\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QZ5F3zCUT781"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}