Celebrity_Face_Recognition

Celebrity_Face_Recognition/Celeb_Face_Recognition.ipynb

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+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":67842,"status":"ok","timestamp":1720240920108,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"okgPSvtjUVgH","outputId":"4d7c8280-92a6-4a66-dd4a-a09b60ba44ee"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /googledrive\n"]}],"source":["from google.colab import drive\n","drive.mount('/googledrive')"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":448,"status":"ok","timestamp":1720240943032,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"hFp7Un9oWTqm","outputId":"4af1fa13-1fa1-4498-d998-1a529009303f"},"outputs":[{"name":"stdout","output_type":"stream","text":["Celeb_Face_Recognition.ipynb  train  val\n"]}],"source":["!ls /googledrive/MyDrive/GSSOC24/celeb/"]},{"cell_type":"code","execution_count":19,"metadata":{"executionInfo":{"elapsed":434,"status":"ok","timestamp":1720241305073,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"06AvH5t9WTuB"},"outputs":[],"source":["import os\n","import numpy as np\n","import cv2\n","import random\n","import matplotlib.pyplot as plt\n","from sklearn.preprocessing import LabelEncoder\n","from tensorflow.keras.models import Sequential\n","from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.metrics import classification_report, accuracy_score\n"]},{"cell_type":"code","execution_count":20,"metadata":{"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720241306599,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"VNJ_qjB3WfW1"},"outputs":[],"source":["train_dir = '/googledrive/MyDrive/GSSOC24/celeb/train'\n","val_dir = '/googledrive/MyDrive/GSSOC24/celeb/val'\n"]},{"cell_type":"code","execution_count":21,"metadata":{"executionInfo":{"elapsed":514,"status":"ok","timestamp":1720241309573,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"nq8XnzBQWpVh"},"outputs":[],"source":["def load_data(data_dir):\n","    images = []\n","    labels = []\n","    for label in os.listdir(data_dir):\n","        if label not in ['madonna', 'mindy_kaling', 'jerry_seinfeld', 'elton_john', 'ben_afflek']:\n","            continue\n","        for file in os.listdir(os.path.join(data_dir, label)):\n","            img_path = os.path.join(data_dir, label, file)\n","            img = cv2.imread(img_path)\n","            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n","            img = cv2.resize(img, (128, 128))\n","            images.append(img)\n","            labels.append(label)\n","    return np.array(images), np.array(labels)\n"]},{"cell_type":"code","execution_count":22,"metadata":{"executionInfo":{"elapsed":1123,"status":"ok","timestamp":1720241313000,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"s7XqGThZWr-1"},"outputs":[],"source":["X_train, y_train = load_data(train_dir)\n","X_val, y_val = load_data(val_dir)\n"]},{"cell_type":"code","execution_count":23,"metadata":{"executionInfo":{"elapsed":463,"status":"ok","timestamp":1720241315214,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"8iZhS1u6Wwrd"},"outputs":[],"source":["le = LabelEncoder()\n","y_train = le.fit_transform(y_train)\n","y_val = le.transform(y_val)\n"]},{"cell_type":"code","execution_count":24,"metadata":{"executionInfo":{"elapsed":718,"status":"ok","timestamp":1720241317682,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"-O7YNZeHWx4P"},"outputs":[],"source":["X_train = X_train / 255.0\n","X_val = X_val / 255.0\n"]},{"cell_type":"code","execution_count":25,"metadata":{"executionInfo":{"elapsed":2,"status":"ok","timestamp":1720241319610,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"b-QMrolNW0Xb"},"outputs":[],"source":["y_train = to_categorical(y_train, num_classes=len(le.classes_))\n","y_val = to_categorical(y_val, num_classes=len(le.classes_))\n"]},{"cell_type":"code","execution_count":26,"metadata":{"executionInfo":{"elapsed":2,"status":"ok","timestamp":1720241321396,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"7JXrKXnvW4G0"},"outputs":[],"source":["model = Sequential([\n","    Conv2D(32, (3, 3), activation='relu', input_shape=(128, 128, 3)),\n","    MaxPooling2D((2, 2)),\n","    Conv2D(64, (3, 3), activation='relu'),\n","    MaxPooling2D((2, 2)),\n","    Conv2D(128, (3, 3), activation='relu'),\n","    MaxPooling2D((2, 2)),\n","    Flatten(),\n","    Dense(128, activation='relu'),\n","    Dropout(0.5),\n","    Dense(len(le.classes_), activation='softmax')\n","])\n"]},{"cell_type":"code","execution_count":27,"metadata":{"executionInfo":{"elapsed":4,"status":"ok","timestamp":1720241323392,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"LtvZkIINW6qr"},"outputs":[],"source":["model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])\n"]},{"cell_type":"code","execution_count":36,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":41710,"status":"ok","timestamp":1720241624697,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"bxVSDVnKW946","outputId":"6f5c74eb-5fde-42ef-a541-679f8d2e598d"},"outputs":[{"name":"stdout","output_type":"stream","text":["Epoch 1/10\n","3/3 [==============================] - 5s 2s/step - loss: 0.0295 - accuracy: 0.9892 - val_loss: 2.9298 - val_accuracy: 0.6000\n","Epoch 2/10\n","3/3 [==============================] - 3s 1s/step - loss: 0.0869 - accuracy: 0.9677 - val_loss: 2.7866 - val_accuracy: 0.5200\n","Epoch 3/10\n","3/3 [==============================] - 3s 1s/step - loss: 0.0289 - accuracy: 1.0000 - val_loss: 2.7979 - val_accuracy: 0.5600\n","Epoch 4/10\n","3/3 [==============================] - 3s 1s/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 2.7567 - val_accuracy: 0.6000\n","Epoch 5/10\n","3/3 [==============================] - 5s 2s/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 2.7142 - val_accuracy: 0.6800\n","Epoch 6/10\n","3/3 [==============================] - 4s 1s/step - loss: 0.0273 - accuracy: 0.9892 - val_loss: 2.8622 - val_accuracy: 0.6400\n","Epoch 7/10\n","3/3 [==============================] - 3s 1s/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 3.2112 - val_accuracy: 0.6400\n","Epoch 8/10\n","3/3 [==============================] - 3s 1s/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 3.2759 - val_accuracy: 0.6400\n","Epoch 9/10\n","3/3 [==============================] - 5s 2s/step - loss: 0.0264 - accuracy: 0.9892 - val_loss: 2.9470 - val_accuracy: 0.6400\n","Epoch 10/10\n","3/3 [==============================] - 4s 1s/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 2.7513 - val_accuracy: 0.6400\n"]},{"data":{"text/plain":["<keras.src.callbacks.History at 0x7a1ab349e2f0>"]},"execution_count":36,"metadata":{},"output_type":"execute_result"}],"source":["model.fit(X_train, y_train, epochs=10, batch_size=32, validation_data=(X_val, y_val))\n"]},{"cell_type":"code","execution_count":37,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":718,"status":"ok","timestamp":1720241632236,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"HDdw6wIBXDRs","outputId":"27230245-4578-4ea2-d9b9-2751351cc0b1"},"outputs":[{"name":"stdout","output_type":"stream","text":["1/1 [==============================] - 0s 419ms/step - loss: 2.7513 - accuracy: 0.6400\n","Validation Accuracy: 0.64\n"]}],"source":["val_loss, val_accuracy = model.evaluate(X_val, y_val)\n","print(f'Validation Accuracy: {val_accuracy:.2f}')\n"]},{"cell_type":"code","execution_count":38,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":658,"status":"ok","timestamp":1720241635431,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"KTcabS6EXLlu","outputId":"bfbf4348-7115-406d-d376-152bfb0396ce"},"outputs":[{"name":"stdout","output_type":"stream","text":["1/1 [==============================] - 0s 274ms/step\n"]}],"source":["predictions = model.predict(X_val)\n","predicted_classes = np.argmax(predictions, axis=1)\n","true_classes = np.argmax(y_val, axis=1)\n"]},{"cell_type":"code","execution_count":39,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720241637772,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"QUU-TgxSXOB-","outputId":"e743df86-7dbc-4d7b-d331-f474fc1ebf03"},"outputs":[{"name":"stdout","output_type":"stream","text":["                precision    recall  f1-score   support\n","\n","    ben_afflek       0.50      0.60      0.55         5\n","    elton_john       0.60      0.60      0.60         5\n","jerry_seinfeld       0.50      0.20      0.29         5\n","       madonna       0.57      0.80      0.67         5\n","  mindy_kaling       1.00      1.00      1.00         5\n","\n","      accuracy                           0.64        25\n","     macro avg       0.63      0.64      0.62        25\n","  weighted avg       0.63      0.64      0.62        25\n","\n"]}],"source":["print(classification_report(true_classes, predicted_classes, target_names=le.classes_))\n"]},{"cell_type":"code","execution_count":40,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"output_embedded_package_id":"1y3ENGDc1YsGJMHPvShg_qLPonFKt9-aN"},"executionInfo":{"elapsed":7226,"status":"ok","timestamp":1720241647576,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"sKBYqCJKXQoB","outputId":"be84a268-3100-4183-fe92-e6a4f1f5f629"},"outputs":[{"data":{"text/plain":["Output hidden; open in https://colab.research.google.com to view."]},"metadata":{},"output_type":"display_data"}],"source":["def display_images(images, true_labels, pred_labels, label_encoder, num_images=25):\n","    plt.figure(figsize=(20, 20))\n","    for i in range(num_images):\n","        plt.subplot(5, 5, i + 1)\n","        plt.imshow(images[i])\n","        plt.title(f\"True: {label_encoder.inverse_transform([true_labels[i]])[0]}\\nPred: {label_encoder.inverse_transform([pred_labels[i]])[0]}\")\n","        plt.axis('off')\n","    plt.show()\n","\n","# Display images\n","display_images(X_val, true_classes, predicted_classes, le)\n"]},{"cell_type":"code","execution_count":41,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":466,"status":"ok","timestamp":1720241667809,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"EX-O6u8LYJS_","outputId":"1926c532-d773-4d91-88cc-4c3d1d7ed159"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model saved successfully.\n"]},{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py:3103: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n","  saving_api.save_model(\n"]}],"source":["model.save('/googledrive/MyDrive/GSSOC24/celeb/celebrity_recognition_model.h5')\n","print(\"Model saved successfully.\")\n"]},{"cell_type":"code","execution_count":43,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1242,"status":"ok","timestamp":1720241692509,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"1aF50wkxYT6i","outputId":"f5702976-bd88-48af-96e0-7d5b450c0dfd"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model loaded successfully.\n"]}],"source":["from tensorflow.keras.models import load_model\n","\n","loaded_model = load_model('/googledrive/MyDrive/GSSOC24/celeb/celebrity_recognition_model.h5')\n","print(\"Model loaded successfully.\")\n"]},{"cell_type":"code","execution_count":46,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"output_embedded_package_id":"1BUfu4w_MryY71VB-T-nlQziepyKcLbP_"},"executionInfo":{"elapsed":16031,"status":"ok","timestamp":1720241906136,"user":{"displayName":"Kalyani arwenundomiel","userId":"01329483214219074689"},"user_tz":-330},"id":"tyLpIPQ4aBGR","outputId":"3ac89100-960e-4ea0-9987-5a907729b62e"},"outputs":[{"data":{"text/plain":["Output hidden; open in https://colab.research.google.com to view."]},"metadata":{},"output_type":"display_data"}],"source":["def predict_and_display_all(val_dir, model, label_encoder):\n","    for label in os.listdir(val_dir):\n","        if label not in ['madonna', 'mindy_kaling', 'jerry_seinfeld', 'elton_john', 'ben_afflek']:\n","            continue\n","        class_dir = os.path.join(val_dir, label)\n","        for img_file in os.listdir(class_dir):\n","            img_path = os.path.join(class_dir, img_file)\n","            img = cv2.imread(img_path)\n","            if img is not None:\n","                img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n","                img_resized = cv2.resize(img_rgb, (128, 128))\n","                img_normalized = img_resized / 255.0\n","                img_expanded = np.expand_dims(img_normalized, axis=0)\n","\n","                prediction = model.predict(img_expanded)\n","                predicted_class = np.argmax(prediction, axis=1)\n","                predicted_label = label_encoder.inverse_transform(predicted_class)[0]\n","\n","                plt.imshow(img_rgb)\n","                plt.title(f\"Predicted: {predicted_label}\\nActual: {label}\")\n","                plt.axis('off')\n","                plt.show()\n","\n","# Use the function to predict and display all validation images\n","predict_and_display_all(val_dir, loaded_model, le)\n"]}],"metadata":{"colab":{"authorship_tag":"ABX9TyMT9S96xKdpruIijvdeF5gT","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}

Celebrity_Face_Recognition/README.md

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+# Celebrity Face Recognition
+
+This project involves training a machine learning model to recognize images of five celebrities: Madonna, Mindy Kaling, Jerry Seinfeld, Elton John, and Ben Affleck. The model is trained on a dataset containing images of these celebrities and is capable of predicting the celebrity in new images with a reasonable degree of accuracy.
+
+## DataSet Preparation
+The dataset used in this project is a collection of images of the five celebrities mentioned above. Download images from https://www.kaggle.com/datasets/dansbecker/5-celebrity-faces-dataset.
+
+## Project Structure
+
+- `train`: Directory containing training images of the celebrities.
+- `val`: Directory containing validation images of the celebrities.
+- `celebrity_recognition_model.h5`: The trained Keras model.
+- `label_encoder.pkl`: The label encoder used for transforming class labels.
+
+## Dependencies
+
+The project requires the following Python packages:
+
+- `tensorflow`
+- `numpy`
+- `opencv-python`
+- `matplotlib`
+- `scikit-learn`
+
+These can be installed using the provided `requirements.txt` file.
+
+## Usage
+
+### Training the Model
+
+1. Place the training images in the `train` directory with each celebrity's images in their respective folders.
+2. Preprocess the images using data generators and train a convolutional neural network (CNN) model.
+3. Save the trained model and the label encoder for future use.
+
+### Predicting on Validation Data
+
+1. Load the trained model and label encoder.
+2. Use the validation data to test the model's performance.
+3. Display the predictions for the validation images, showing the predicted celebrity names.
+
+## Example Workflow
+
+1. **Prepare the Dataset**: Organize the images into `train` and `val` directories with subdirectories for each celebrity.
+2. **Train the Model**: Use a CNN to learn features from the training images and save the model.
+3. **Validate the Model**: Load the model and evaluate it on the validation set to check its performance.
+4. **Display Predictions**: Visualize the predictions by displaying validation images with the predicted celebrity labels.
+
+## Requirements
+
+- TensorFlow
+- NumPy
+- OpenCV
+- Matplotlib
+- Scikit-learn
+
+## License
+
+This project is licensed under the MIT License.