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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bahiensed/ml/blob/main/10_RetrainingMobileNetV2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iBYM_gnQjzhy"
      },
      "outputs": [],
      "source": [
        "#import necessary libraries\n",
        "import os\n",
        "import tensorflow as tf\n",
        "import tensorflow_datasets as tfds\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#config and metadata\n",
        "#image size\n",
        "IMAGE_SIZE = 160\n",
        "#image shape\n",
        "IMAGE_SHAPE = (IMAGE_SIZE, IMAGE_SIZE, 3)\n",
        "#image batch size\n",
        "IMG_BATCH_SIZE = 1\n",
        "#batch size\n",
        "BATCH_SIZE = 32\n",
        "#shuffle buffer size\n",
        "SHUFFLE_BUFFER_SIZE = 1000\n",
        "#base learning rate\n",
        "BASE_LEARNING_RATE = 0.0001\n",
        "#trainging epochs\n",
        "TRAINING_EPOCHS = 10"
      ],
      "metadata": {
        "id": "F3hRChg7kRQa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#get data\n",
        "#add this line, as suggested in https://stackoverflow.com/a/72458771, to solve DownloadError\n",
        "setattr(tfds.image_classification.cats_vs_dogs, '_URL',\"https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_5340.zip\")"
      ],
      "metadata": {
        "id": "SItpZUvpkXg2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#split raw data in training, validation and test groups\n",
        "(raw_training, raw_validation, raw_testing), metadata = tfds.load(\n",
        "    'cats_vs_dogs',\n",
        "    split=['train[:80%]', 'train[80%:90%]', 'train[90%:]'],\n",
        "    with_info=True,\n",
        "    as_supervised=True,\n",
        ")"
      ],
      "metadata": {
        "id": "4gC420YIkY6P",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237,
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        },
        "outputId": "85d0fc1c-4ed7-4cec-bb33-2f4edd2b42a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mDownloading and preparing dataset cats_vs_dogs/4.0.0 (download: 786.68 MiB, generated: Unknown size, total: 786.68 MiB) to /root/tensorflow_datasets/cats_vs_dogs/4.0.0...\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dl Completed...: 0 url [00:00, ? url/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5873ad0fb2b14eee985caf9cd4dba3f1"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dl Size...: 0 MiB [00:00, ? MiB/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0 examples [00:00, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "5182318eba714088bc183bfc30fefee2"
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:1738 images were corrupted and were skipped\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shuffling and writing examples to /root/tensorflow_datasets/cats_vs_dogs/4.0.0.incomplete0CAVAQ/cats_vs_dogs-train.tfrecord\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/23262 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e29222b219d6499ca9e2bf49489ae7a9"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mDataset cats_vs_dogs downloaded and prepared to /root/tensorflow_datasets/cats_vs_dogs/4.0.0. Subsequent calls will reuse this data.\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#resize image and convert it into a form that tensorflow can read more easily\n",
        "def prep_image(image, label):\n",
        "  image = tf.cast(image, tf.float32)\n",
        "  image = (image/127.5) - 1\n",
        "  image = tf.image.resize(image, (IMAGE_SIZE, IMAGE_SIZE))\n",
        "  return image, label"
      ],
      "metadata": {
        "id": "RPXWhWvBkcOj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#create training, validation and testing data from raw data\n",
        "training_data = raw_training.map(prep_image)\n",
        "validation_data = raw_validation.map(prep_image)\n",
        "testing_data = raw_testing.map(prep_image)"
      ],
      "metadata": {
        "id": "T_cJfmBJkfAE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#create batches\n",
        "training_batches = training_data.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)\n",
        "validation_batches = validation_data.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)\n",
        "testing_batches = testing_data.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)"
      ],
      "metadata": {
        "id": "03cdPn6zkilE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#import the original MobileNetV2 model and remove its top layer\n",
        "original_model = tf.keras.applications.MobileNetV2(input_shape=IMAGE_SHAPE, include_top=False)"
      ],
      "metadata": {
        "id": "-7jrgLh_klll",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "88b76aa8-2f40-424a-cd56-347890f6469b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v2/mobilenet_v2_weights_tf_dim_ordering_tf_kernels_1.0_160_no_top.h5\n",
            "9412608/9406464 [==============================] - 0s 0us/step\n",
            "9420800/9406464 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#don't retrain the original model\n",
        "original_model.trainable = False"
      ],
      "metadata": {
        "id": "8oei72Dtkpoi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#add first new layer\n",
        "global_average_layer = tf.keras.layers.GlobalAveragePooling2D()"
      ],
      "metadata": {
        "id": "IRQZ3nhJkrsY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#add second new layer\n",
        "prediction_layer = tf.keras.layers.Dense(2)"
      ],
      "metadata": {
        "id": "_CvPW_E9ktin"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#combining the original model with the two new layers\n",
        "model = tf.keras.Sequential([\n",
        "  original_model,\n",
        "  global_average_layer,\n",
        "  prediction_layer\n",
        "])"
      ],
      "metadata": {
        "id": "EEkqesa-kv2J"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#compile the model\n",
        "model.compile(optimizer=tf.keras.optimizers.RMSprop(learning_rate=BASE_LEARNING_RATE), #changed lr to learning_rate as lr is deprecated\n",
        "              loss=tf.keras.losses.SparseCategoricalCrossentropy(),\n",
        "              metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "4cpzQHiakzSP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#check compilation\n",
        "model.summary()"
      ],
      "metadata": {
        "id": "UuGH-JvBk__r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3c72b471-c5bb-48b8-bd32-5e4bb5f6c8ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " mobilenetv2_1.00_160 (Funct  (None, 5, 5, 1280)       2257984   \n",
            " ional)                                                          \n",
            "                                                                 \n",
            " global_average_pooling2d (G  (None, 1280)             0         \n",
            " lobalAveragePooling2D)                                          \n",
            "                                                                 \n",
            " dense (Dense)               (None, 2)                 2562      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 2,260,546\n",
            "Trainable params: 2,562\n",
            "Non-trainable params: 2,257,984\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#use GPU and train model\n",
        "with tf.device('/device:GPU:0'):\n",
        "  history = model.fit(training_batches,\n",
        "                      epochs=TRAINING_EPOCHS,\n",
        "                      validation_data=validation_batches)"
      ],
      "metadata": {
        "id": "AVEoLxpolB0q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3a0bd338-e3cb-4cee-cda4-9723b30b5f99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "582/582 [==============================] - 63s 82ms/step - loss: 0.9718 - accuracy: 0.6961 - val_loss: 0.6937 - val_accuracy: 0.7377\n",
            "Epoch 2/10\n",
            "582/582 [==============================] - 48s 80ms/step - loss: 0.6877 - accuracy: 0.7397 - val_loss: 0.6862 - val_accuracy: 0.7730\n",
            "Epoch 3/10\n",
            "582/582 [==============================] - 48s 80ms/step - loss: 0.6649 - accuracy: 0.7870 - val_loss: 0.6475 - val_accuracy: 0.8065\n",
            "Epoch 4/10\n",
            "582/582 [==============================] - 48s 79ms/step - loss: 0.6273 - accuracy: 0.8282 - val_loss: 0.6283 - val_accuracy: 0.8487\n",
            "Epoch 5/10\n",
            "582/582 [==============================] - 52s 86ms/step - loss: 0.5824 - accuracy: 0.8562 - val_loss: 0.5773 - val_accuracy: 0.8719\n",
            "Epoch 6/10\n",
            "582/582 [==============================] - 48s 79ms/step - loss: 0.5368 - accuracy: 0.8784 - val_loss: 0.5456 - val_accuracy: 0.8912\n",
            "Epoch 7/10\n",
            "582/582 [==============================] - 49s 81ms/step - loss: 0.5046 - accuracy: 0.8968 - val_loss: 0.5112 - val_accuracy: 0.9037\n",
            "Epoch 8/10\n",
            "582/582 [==============================] - 48s 80ms/step - loss: 0.4572 - accuracy: 0.9083 - val_loss: 0.4814 - val_accuracy: 0.9170\n",
            "Epoch 9/10\n",
            "582/582 [==============================] - 48s 80ms/step - loss: 0.4291 - accuracy: 0.9253 - val_loss: 0.4522 - val_accuracy: 0.9243\n",
            "Epoch 10/10\n",
            "582/582 [==============================] - 48s 80ms/step - loss: 0.3912 - accuracy: 0.9313 - val_loss: 0.4316 - val_accuracy: 0.9312\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#get image function\n",
        "def get_image_from_url(image_url):\n",
        "  # If the temporary test_image.jpg file already exists,\n",
        "  # delete it so a new one can be made.\n",
        "  if os.path.exists('/root/.keras/datasets/test_image.jpg'):\n",
        "    os.remove('/root/.keras/datasets/test_image.jpg')\n",
        "\n",
        "  image_path = tf.keras.utils.get_file('test_image.jpg', origin=image_url)\n",
        "  return image_path"
      ],
      "metadata": {
        "id": "gRyggd8RlEOX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#print prediction function\n",
        "def print_predictions(predictions):\n",
        "    for (prediction, number) in zip(predictions[0], range(1, len(predictions[0])+1)):\n",
        "      print('{}. {} {:.2f}%'.format(number, prediction[1], prediction[2]*100))"
      ],
      "metadata": {
        "id": "bq-YP75NlJBE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#predict image function\n",
        "def predict_image(image_url):\n",
        "  #fetch image from URL using the above get image function\n",
        "  image_path = get_image_from_url(image_url)\n",
        "\n",
        "  #prepare image for use by the model\n",
        "  image = tf.keras.preprocessing.image.load_img(image_path, target_size=(IMAGE_SIZE, IMAGE_SIZE))\n",
        "\n",
        "  #create a new figure, or activate an existing one\n",
        "  #https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html\n",
        "  plt.figure()\n",
        "\n",
        "  #display data as an image, i.e., on a 2D regular raster.\n",
        "  #https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html\n",
        "  plt.imshow(image)\n",
        "\n",
        "  #transform image into an array\n",
        "  image = tf.keras.preprocessing.image.img_to_array(image)\n",
        "  image = np.expand_dims(image, axis=0)\n",
        "\n",
        "  #prediction result\n",
        "  prediction_result = model.predict(image, batch_size=IMG_BATCH_SIZE)\n",
        "  labels = metadata.features['label'].names\n",
        "  print(labels[prediction_result.argmin()])"
      ],
      "metadata": {
        "id": "GHwGvhNJlRWi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#make prediction\n",
        "predict_image('https://upload.wikimedia.org/wikipedia/commons/5/5f/Kolm%C3%A5rden_Wolf.jpg')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "id": "ocgSPL_LlTOI",
        "outputId": "399bb5e2-1148-4934-819c-95f554817ac5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://upload.wikimedia.org/wikipedia/commons/5/5f/Kolm%C3%A5rden_Wolf.jpg\n",
            "172032/166544 [==============================] - 0s 0us/step\n",
            "180224/166544 [================================] - 0s 0us/step\n",
            "cat\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}