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\n"
- },
- "metadata": {}
- }
- ],
- "source": [
- "# Placeholder for the directory path\n",
- "surpirse_directory_path = '/content/train/fear' # Replace with your directory path\n",
- "plot_images_from_directory(surpirse_directory_path, class_name = 'Fear')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "TN9WziDDG5x1"
- },
- "source": [
- "# Checking shapes and channels."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "sCLl3jD8GsXN",
- "outputId": "c4b4c7fe-faa7-4763-9bf8-7a9925473572"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Shape: (48, 48, 3)\n"
- ]
- }
- ],
- "source": [
- "image = '/content/train/angry/Training_10118481.jpg'\n",
- "img = cv2.imread(image) # Default load in color format.\n",
- "\n",
- "# If the image is loaded successfully, print its pixel values\n",
- "if img is not None:\n",
- " # print(img)\n",
- " print(\"Shape:\", img.shape)\n",
- "else:\n",
- " print(\"The image could not be loaded. Please check the path and file permissions.\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "bWSy_Z1CGsUd",
- "outputId": "70f9ed2e-5893-4399-b18a-1ff0843b7ea3"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Shape: (48, 48)\n"
- ]
- }
- ],
- "source": [
- "image_path = '/content/train/angry/Training_10118481.jpg'\n",
- "\n",
- "# Load the image in grayscale\n",
- "img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)\n",
- "\n",
- "# If the image is loaded successfully, print its pixel values\n",
- "if img is not None:\n",
- " # print(img)\n",
- " print(\"Shape:\", img.shape) # This should now print (48, 48)\n",
- "else:\n",
- " print(\"The image could not be loaded. Please check the path and file permissions.\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "zLYFkBz5HJdz"
- },
- "source": [
- "# Initializing the ImageGenerators"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "id": "Hea0bVwqHBYO"
- },
- "outputs": [],
- "source": [
- "# Define paths to the train and validation directories\n",
- "train_data_dir = '/content/train'\n",
- "test_data_dir = '/content/test'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "ICnT2MeaHBSo",
- "outputId": "247bf56e-15c7-4818-e422-4bdca56e8947"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Found 28709 images belonging to 7 classes.\n",
- "Found 7178 images belonging to 7 classes.\n"
- ]
- }
- ],
- "source": [
- "# Directory paths for training and testing data\n",
- "train_dir = '/content/train'\n",
- "test_dir = '/content/test'\n",
- "\n",
- "# Batch size for data generators\n",
- "batch_size = 64\n",
- "\n",
- "# Data augmentation configuration for training data\n",
- "train_datagen = ImageDataGenerator(\n",
- " rescale=1 / 255., # Rescale pixel values to [0,1]\n",
- " rotation_range=10, # Random rotation within range [-10,10] degrees\n",
- " zoom_range=0.2, # Random zoom between [0.8, 1.2]\n",
- " width_shift_range=0.1, # Random horizontal shift within range [-0.1, 0.1]\n",
- " height_shift_range=0.1, # Random vertical shift within range [-0.1, 0.1]\n",
- " horizontal_flip=True, # Random horizontal flip\n",
- " fill_mode='nearest' # Fill mode for handling newly created pixels\n",
- " )\n",
- "\n",
- "# Configuration for testing data (only rescaling)\n",
- "test_datagen = ImageDataGenerator(\n",
- " rescale=1 / 255. # Rescale pixel values to [0,1]\n",
- " )\n",
- "\n",
- "# Data generators for training and testing data\n",
- "train_generator = train_datagen.flow_from_directory(\n",
- " train_dir, # Directory containing training data\n",
- " class_mode=\"categorical\", # Classification mode for categorical labels\n",
- " target_size=(224, 224), # Resize input images to (224,224)\n",
- " color_mode='rgb', # Color mode for images (RGB)\n",
- " shuffle=True, # Shuffle training data\n",
- " batch_size=64, # Batch size for training\n",
- " subset='training' # Subset of data (training)\n",
- " )\n",
- "\n",
- "test_generator = test_datagen.flow_from_directory(\n",
- " test_dir, # Directory containing testing data\n",
- " class_mode=\"categorical\", # Classification mode for categorical labels\n",
- " target_size=(224, 224), # Resize input images to (224,224)\n",
- " color_mode=\"rgb\", # Color mode for images (RGB)\n",
- " shuffle=False, # Do not shuffle testing data\n",
- " batch_size=64 # Batch size for testing\n",
- " )\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "EwlhK4zZHbMt"
- },
- "source": [
- "# Introducing Class wieghts for imbalanced data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "iS9SIz8FHBPe",
- "outputId": "7279cff0-7a0b-4549-85e1-d01e0df30f79"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Class Weights Dictionary: {0: 1.0266046844269623, 1: 9.406618610747051, 2: 1.0010460615781582, 3: 0.5684387684387684, 4: 0.8260394187886635, 5: 0.8491274770777877, 6: 1.293372978330405}\n"
- ]
- }
- ],
- "source": [
- "# Extract class labels for all instances in the training dataset\n",
- "classes = np.array(train_generator.classes)\n",
- "\n",
- "# Calculate class weights to handle imbalances in the training data\n",
- "# 'balanced' mode automatically adjusts weights inversely proportional to class frequencies\n",
- "class_weights = compute_class_weight(\n",
- " class_weight='balanced', # Strategy to balance classes\n",
- " classes=np.unique(classes), # Unique class labels\n",
- " y=classes # Class labels for each instance in the training dataset\n",
- ")\n",
- "\n",
- "# Create a dictionary mapping class indices to their calculated weights\n",
- "class_weights_dict = dict(enumerate(class_weights))\n",
- "\n",
- "# Output the class weights dictionary\n",
- "print(\"Class Weights Dictionary:\", class_weights_dict)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "yxd2ltlxHT9K"
- },
- "source": [
- "# Model: Transfer Learning - ResNet50"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "gOqq4b6lHBMa",
- "outputId": "083597d2-0725-4848-80bb-7231c2ba12fc"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50v2_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
- "\u001b[1m94668760/94668760\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
- ]
- }
- ],
- "source": [
- "ResNet50V2 = tf.keras.applications.ResNet50V2(input_shape=(224, 224, 3),\n",
- " include_top= False,\n",
- " weights='imagenet'\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "id": "pdTYcYm-HYPQ"
- },
- "outputs": [],
- "source": [
- "# Freezing all layers except last 50\n",
- "\n",
- "ResNet50V2.trainable = True\n",
- "\n",
- "for layer in ResNet50V2.layers[:-50]:\n",
- " layer.trainable = False"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "id": "IOzfDPhrHYMy"
- },
- "outputs": [],
- "source": [
- "model = Sequential([\n",
- " ResNet50V2,\n",
- " Dropout(0.2),\n",
- " BatchNormalization(),\n",
- " Flatten(),\n",
- " Dense(128, activation='relu'),\n",
- " BatchNormalization(),\n",
- " Dropout(0.1),\n",
- " Dense(7,activation='softmax')\n",
- " ])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 417
- },
- "id": "wuPd71ZUHYKO",
- "outputId": "d6cc2ff3-cc82-4581-c0d7-76d4e4e846e1"
- },
- "outputs": [
- {
- "output_type": "display_data",
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- "\u001b[1mModel: \"sequential\"\u001b[0m\n"
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- "Model: \"sequential\"\n",
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- "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
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- "│ dropout (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m2048\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
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- "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
- "│ flatten (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100352\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
- "│ dense (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m12,845,184\u001b[0m │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
- "│ batch_normalization_1 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m512\u001b[0m │\n",
- "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
- "│ dropout_1 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n",
- "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
- "│ dense_1 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m) │ \u001b[38;5;34m903\u001b[0m │\n",
- "└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
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- "┃ Layer (type) ┃ Output Shape ┃ Param # ┃\n",
- "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
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- "model.summary()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {
- "id": "F1gSKvxuHYHf"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {
- "id": "J7JHpr9FHvsK"
- },
- "outputs": [],
- "source": [
- "# File path for the model checkpoint\n",
- "chk_path = 'emotion_detection_ResNet50.keras'\n",
- "\n",
- "# Callback to save the model checkpoint\n",
- "checkpoint = ModelCheckpoint(filepath=chk_path,\n",
- " save_best_only=True,\n",
- " verbose=1,\n",
- " mode='min',\n",
- " monitor='val_loss')\n",
- "# Save only the weights\n",
- "weights_checkpoint = ModelCheckpoint(\n",
- " filepath='emotion_detector_resnet50_weights.weights.h5',\n",
- " monitor=\"val_loss\",\n",
- " verbose=1,\n",
- " save_best_only=True,\n",
- " save_weights_only=True, # Save only the weights\n",
- " mode='min',\n",
- " save_freq='epoch'\n",
- ")\n",
- "\n",
- "\n",
- "# Callback for early stopping\n",
- "earlystop = EarlyStopping(monitor = 'val_loss',\n",
- " patience = 4,\n",
- " restore_best_weights = True,\n",
- " verbose=1)\n",
- "\n",
- "# Callback to reduce learning rate\n",
- "reduce_lr = ReduceLROnPlateau(monitor='val_loss',\n",
- " factor=0.2,\n",
- " patience=2,\n",
- "# min_lr=0.00005,\n",
- " verbose=1)\n",
- "\n",
- "# Callback to log training data to a CSV file\n",
- "csv_logger = CSVLogger('training.log')\n",
- "\n",
- "# Aggregating all callbacks into a list\n",
- "callbacks = [checkpoint, weights_checkpoint, earlystop, csv_logger] # Adjusted as per your use-case\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "Sg3qfwd3Hvp4",
- "outputId": "d890e527-94b2-4035-a386-c1556ede6a17"
- },
- "outputs": [
- {
- "metadata": {
- "tags": null
- },
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Epoch 1/50\n"
- ]
- },
- {
- "metadata": {
- "tags": null
- },
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/usr/local/lib/python3.10/dist-packages/keras/src/trainers/data_adapters/py_dataset_adapter.py:122: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored.\n",
- " self._warn_if_super_not_called()\n"
- ]
- },
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 821ms/step - accuracy: 0.3498 - loss: 1.8674\n",
- "Epoch 1: val_loss improved from inf to 1.30877, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 1: val_loss improved from inf to 1.30877, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m433s\u001b[0m 880ms/step - accuracy: 0.3499 - loss: 1.8668 - val_accuracy: 0.5127 - val_loss: 1.3088\n",
- "Epoch 2/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 788ms/step - accuracy: 0.5073 - loss: 1.3292\n",
- "Epoch 2: val_loss did not improve from 1.30877\n",
- "\n",
- "Epoch 2: val_loss did not improve from 1.30877\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m395s\u001b[0m 825ms/step - accuracy: 0.5073 - loss: 1.3292 - val_accuracy: 0.4232 - val_loss: 3.8130\n",
- "Epoch 3/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 783ms/step - accuracy: 0.5391 - loss: 1.2036\n",
- "Epoch 3: val_loss did not improve from 1.30877\n",
- "\n",
- "Epoch 3: val_loss did not improve from 1.30877\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m373s\u001b[0m 820ms/step - accuracy: 0.5392 - loss: 1.2036 - val_accuracy: 0.5425 - val_loss: 1.3672\n",
- "Epoch 4/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 786ms/step - accuracy: 0.5779 - loss: 1.1256\n",
- "Epoch 4: val_loss improved from 1.30877 to 1.13009, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 4: val_loss improved from 1.30877 to 1.13009, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m383s\u001b[0m 840ms/step - accuracy: 0.5779 - loss: 1.1256 - val_accuracy: 0.5886 - val_loss: 1.1301\n",
- "Epoch 5/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 787ms/step - accuracy: 0.6008 - loss: 1.0399\n",
- "Epoch 5: val_loss did not improve from 1.13009\n",
- "\n",
- "Epoch 5: val_loss did not improve from 1.13009\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m378s\u001b[0m 833ms/step - accuracy: 0.6008 - loss: 1.0399 - val_accuracy: 0.4585 - val_loss: 73.3798\n",
- "Epoch 6/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 786ms/step - accuracy: 0.6110 - loss: 1.0121\n",
- "Epoch 6: val_loss improved from 1.13009 to 1.05142, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 6: val_loss improved from 1.13009 to 1.05142, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m390s\u001b[0m 849ms/step - accuracy: 0.6110 - loss: 1.0121 - val_accuracy: 0.6163 - val_loss: 1.0514\n",
- "Epoch 7/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 786ms/step - accuracy: 0.6234 - loss: 0.9838\n",
- "Epoch 7: val_loss did not improve from 1.05142\n",
- "\n",
- "Epoch 7: val_loss did not improve from 1.05142\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m429s\u001b[0m 821ms/step - accuracy: 0.6234 - loss: 0.9838 - val_accuracy: 0.5839 - val_loss: 1.1548\n",
- "Epoch 8/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 782ms/step - accuracy: 0.6323 - loss: 0.9444\n",
- "Epoch 8: val_loss improved from 1.05142 to 1.04015, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 8: val_loss improved from 1.05142 to 1.04015, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m380s\u001b[0m 836ms/step - accuracy: 0.6323 - loss: 0.9444 - val_accuracy: 0.6225 - val_loss: 1.0402\n",
- "Epoch 9/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 787ms/step - accuracy: 0.6431 - loss: 0.9080\n",
- "Epoch 9: val_loss did not improve from 1.04015\n",
- "\n",
- "Epoch 9: val_loss did not improve from 1.04015\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m379s\u001b[0m 833ms/step - accuracy: 0.6431 - loss: 0.9081 - val_accuracy: 0.6265 - val_loss: 1.0644\n",
- "Epoch 10/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 780ms/step - accuracy: 0.6422 - loss: 0.9123\n",
- "Epoch 10: val_loss did not improve from 1.04015\n",
- "\n",
- "Epoch 10: val_loss did not improve from 1.04015\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m379s\u001b[0m 825ms/step - accuracy: 0.6422 - loss: 0.9124 - val_accuracy: 0.6096 - val_loss: 1.0452\n",
- "Epoch 11/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 786ms/step - accuracy: 0.6491 - loss: 0.8995\n",
- "Epoch 11: val_loss did not improve from 1.04015\n",
- "\n",
- "Epoch 11: val_loss did not improve from 1.04015\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m373s\u001b[0m 822ms/step - accuracy: 0.6491 - loss: 0.8995 - val_accuracy: 0.6048 - val_loss: 1.9697\n",
- "Epoch 12/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 783ms/step - accuracy: 0.6564 - loss: 0.8688\n",
- "Epoch 12: val_loss improved from 1.04015 to 1.01523, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 12: val_loss improved from 1.04015 to 1.01523, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m399s\u001b[0m 858ms/step - accuracy: 0.6564 - loss: 0.8688 - val_accuracy: 0.6449 - val_loss: 1.0152\n",
- "Epoch 13/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 784ms/step - accuracy: 0.6620 - loss: 0.8381\n",
- "Epoch 13: val_loss did not improve from 1.01523\n",
- "\n",
- "Epoch 13: val_loss did not improve from 1.01523\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m373s\u001b[0m 820ms/step - accuracy: 0.6620 - loss: 0.8381 - val_accuracy: 0.6245 - val_loss: 1.0511\n",
- "Epoch 14/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 780ms/step - accuracy: 0.6643 - loss: 0.8503\n",
- "Epoch 14: val_loss did not improve from 1.01523\n",
- "\n",
- "Epoch 14: val_loss did not improve from 1.01523\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m372s\u001b[0m 817ms/step - accuracy: 0.6643 - loss: 0.8503 - val_accuracy: 0.6244 - val_loss: 1.4191\n",
- "Epoch 15/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 782ms/step - accuracy: 0.6753 - loss: 0.8148\n",
- "Epoch 15: val_loss improved from 1.01523 to 0.98972, saving model to emotion_detection_ResNet50.keras\n",
- "\n",
- "Epoch 15: val_loss improved from 1.01523 to 0.98972, saving model to emotion_detector_resnet50_weights.weights.h5\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m402s\u001b[0m 862ms/step - accuracy: 0.6753 - loss: 0.8148 - val_accuracy: 0.6513 - val_loss: 0.9897\n",
- "Epoch 16/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 781ms/step - accuracy: 0.6786 - loss: 0.8098\n",
- "Epoch 16: val_loss did not improve from 0.98972\n",
- "\n",
- "Epoch 16: val_loss did not improve from 0.98972\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m421s\u001b[0m 816ms/step - accuracy: 0.6786 - loss: 0.8099 - val_accuracy: 0.6169 - val_loss: 1.2917\n",
- "Epoch 17/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 788ms/step - accuracy: 0.6768 - loss: 0.8122\n",
- "Epoch 17: val_loss did not improve from 0.98972\n",
- "\n",
- "Epoch 17: val_loss did not improve from 0.98972\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m375s\u001b[0m 825ms/step - accuracy: 0.6768 - loss: 0.8122 - val_accuracy: 0.6397 - val_loss: 0.9935\n",
- "Epoch 18/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 784ms/step - accuracy: 0.6948 - loss: 0.7745\n",
- "Epoch 18: val_loss did not improve from 0.98972\n",
- "\n",
- "Epoch 18: val_loss did not improve from 0.98972\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m380s\u001b[0m 820ms/step - accuracy: 0.6947 - loss: 0.7745 - val_accuracy: 0.6356 - val_loss: 1.0452\n",
- "Epoch 19/50\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 785ms/step - accuracy: 0.6898 - loss: 0.7703\n",
- "Epoch 19: val_loss did not improve from 0.98972\n",
- "\n",
- "Epoch 19: val_loss did not improve from 0.98972\n",
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m374s\u001b[0m 821ms/step - accuracy: 0.6898 - loss: 0.7703 - val_accuracy: 0.6318 - val_loss: 1.3801\n",
- "Epoch 19: early stopping\n",
- "Restoring model weights from the end of the best epoch: 15.\n"
- ]
- }
- ],
- "source": [
- "train_history = model.fit(\n",
- " train_generator,\n",
- " epochs=50,\n",
- " validation_data=test_generator,\n",
- " class_weight=class_weights_dict,\n",
- " callbacks = callbacks\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {
- "id": "BOXlD0cBHvmb"
- },
- "outputs": [],
- "source": [
- "model.save(\"emotion_dectector.keras\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "XrLYepljH9Y7"
- },
- "source": [
- "# Plotting Performance Metrics"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "YcobLDapHvjE"
- },
- "outputs": [],
- "source": [
- "def plot_training_history(history):\n",
- "\n",
- " acc = history.history['accuracy']\n",
- " val_acc = history.history['val_accuracy']\n",
- " loss = history.history['loss']\n",
- " val_loss = history.history['val_loss']\n",
- "\n",
- " epochs_range = range(len(acc))\n",
- "\n",
- " plt.figure(figsize=(20, 5))\n",
- "\n",
- " # Plot training and validation accuracy\n",
- " plt.subplot(1, 2, 1)\n",
- " plt.plot(epochs_range, acc, label='Training Accuracy')\n",
- " plt.plot(epochs_range, val_acc, label='Validation Accuracy')\n",
- " plt.legend(loc='lower right')\n",
- " plt.title('Training and Validation Accuracy')\n",
- "\n",
- " # Plot training and validation loss\n",
- " plt.subplot(1, 2, 2)\n",
- " plt.plot(epochs_range, loss, label='Training Loss')\n",
- " plt.plot(epochs_range, val_loss, label='Validation Loss')\n",
- " plt.legend(loc='upper right')\n",
- " plt.title('Training and Validation Loss')\n",
- "\n",
- " plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 329
- },
- "id": "hv0NQB8iIAjR",
- "outputId": "2d92e400-b3cb-4ab5-8b90-47454a312048"
- },
- "outputs": [
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- ""
- ],
- "image/png": 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- },
- "metadata": {}
- }
- ],
- "source": [
- "plot_training_history(train_history)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "cosdWUWgIAd8",
- "outputId": "c8e074a8-ea33-479b-e8ed-bcf03e97efe7"
- },
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "\u001b[1m449/449\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m343s\u001b[0m 764ms/step - accuracy: 0.6933 - loss: 0.8300\n",
- "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m17s\u001b[0m 146ms/step - accuracy: 0.5806 - loss: 1.1462\n",
- "final train accuracy = 69.58 , validation accuracy = 65.13\n"
- ]
- }
- ],
- "source": [
- "train_loss, train_accu = model.evaluate(train_generator)\n",
- "test_loss, test_accu = model.evaluate(test_generator)\n",
- "print(\"final train accuracy = {:.2f} , validation accuracy = {:.2f}\".format(train_accu*100, test_accu*100))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "g0BlC7jcIKqk"
- },
- "outputs": [],
- "source": [
- "# Assuming your true_classes and predicted_classes are already defined\n",
- "true_classes = test_generator.classes\n",
- "predicted_classes = np.argmax(model.predict(test_generator, steps=int(np.ceil(test_generator.samples/test_generator.batch_size))), axis=1)\n",
- "class_labels = list(test_generator.class_indices.keys())\n",
- "\n",
- "# Generate the confusion matrix\n",
- "cm = confusion_matrix(true_classes, predicted_classes)\n",
- "\n",
- "# Plotting with seaborn\n",
- "plt.figure(figsize=(10, 8))\n",
- "sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=class_labels, yticklabels=class_labels)\n",
- "plt.title('Confusion Matrix')\n",
- "plt.ylabel('True label')\n",
- "plt.xlabel('Predicted label')\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "fABYhNidIKnk"
- },
- "outputs": [],
- "source": [
- "# Printing the classification report\n",
- "report = classification_report(true_classes,\n",
- " predicted_classes,\n",
- " target_names=class_labels,\n",
- " zero_division=0)\n",
- "print(\"Classification Report:\\n\", report)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "kD0YQ_1LIl3g"
- },
- "source": [
- "# AUC ROC plot for each class"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "sDzb9PsFIKkY"
- },
- "outputs": [],
- "source": [
- "true_labels = test_generator.classes\n",
- "preds = model.predict(test_generator, steps=len(test_generator))\n",
- "pred_labels = np.argmax(preds, axis=1)\n",
- "classes=list(test_generator.class_indices.keys())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 504
- },
- "id": "u-vBWb_ZIKfl",
- "outputId": "31630b8d-e8e0-4544-add2-52b09d54c9d5"
- },
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "execution_count": 33
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- ""
- ],
- "image/png": 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\n"
- },
- "metadata": {}
- }
- ],
- "source": [
- "y_encoded = pd.get_dummies(true_labels).astype(int).values\n",
- "preds_encoded = pd.get_dummies(pred_labels).astype(int).values\n",
- "\n",
- "fpr = dict()\n",
- "tpr = dict()\n",
- "roc_auc = dict()\n",
- "for i in range(7):\n",
- " fpr[i], tpr[i], _ = roc_curve(y_encoded[:,i], preds_encoded[:,i])\n",
- " roc_auc[i] = auc(fpr[i], tpr[i])\n",
- "\n",
- "plt.figure(figsize=(10,5))\n",
- "colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2']\n",
- "for i, color in enumerate(colors):\n",
- " plt.plot(fpr[i], tpr[i], color=color, lw=2, label=f\"ROC curve for {classes[i]} (area = {roc_auc[i]:0.2f})\")\n",
- "\n",
- "plt.plot([0, 1], [0, 1], 'k--', lw=2)\n",
- "plt.xlim([0, 1])\n",
- "plt.ylim([0, 1])\n",
- "plt.xlabel('False Positive Rate')\n",
- "plt.ylabel('True Positive Rate')\n",
- "plt.title('ROC Curve')\n",
- "plt.legend(loc='lower right')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "JmBH-NezInqk"
- },
- "outputs": [],
- "source": [
- "model.save(\"Resnet_model.keras\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "oOh6OeSmt5FT"
- },
- "source": [
- "# Uploading the model on drive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "PleH2v_jtiuI"
- },
- "outputs": [],
- "source": [
- "# Mount Google Drive\n",
- "drive.mount('/content/drive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {
- "id": "c3-oYoAwuD9C",
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 321
- },
- "outputId": "6fbcd78d-07ac-4deb-c684-497ca46befa6"
- },
- "outputs": [
- {
- "output_type": "error",
- "ename": "FileNotFoundError",
- "evalue": "[Errno 2] No such file or directory: '/content/drive/MyDrive/Image_classification/gender_detector_resnet_model.keras'",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# Save your trained model to the specified path\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_save_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py\u001b[0m in \u001b[0;36merror_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[0;31m# To get the full stack trace, call:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 121\u001b[0m \u001b[0;31m# `keras.config.disable_traceback_filtering()`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 122\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfiltered_tb\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 123\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[0;32mdel\u001b[0m \u001b[0mfiltered_tb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/keras/src/saving/saving_lib.py\u001b[0m in \u001b[0;36msave_model\u001b[0;34m(model, filepath, weights_format, zipped)\u001b[0m\n\u001b[1;32m 139\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip_filepath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 140\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 141\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"wb\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 142\u001b[0m \u001b[0m_save_model_to_fileobj\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights_format\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 143\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/content/drive/MyDrive/Image_classification/gender_detector_resnet_model.keras'"
- ]
- }
- ],
- "source": [
- "\n",
- "# Define the path where you want to save the model in your Google Drive\n",
- "model_save_path = '/content/drive/MyDrive/Image_classification/gender_detector_resnet_model.keras'\n",
- "\n",
- "# Save your trained model to the specified path\n",
- "model.save(model_save_path)\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "yC8PtV0vuD6Y"
- },
- "outputs": [],
- "source": [
- "# Unmount Google Drive\n",
- "drive.flush_and_unmount()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "LAnFhqB-uWPj"
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "accelerator": "GPU",
- "colab": {
- "gpuType": "T4",
- "provenance": []
- },
- "kernelspec": {
- "display_name": "Python 3",
- "name": "python3"
- },
- "language_info": {
- "name": "python"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
\ No newline at end of file
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