| | --- |
| | title: Face Shape Detection |
| | emoji: 👤 |
| | colorFrom: blue |
| | colorTo: purple |
| | sdk: docker |
| | pinned: false |
| | license: mit |
| | app_port: 7860 |
| | short_description: AI face shape detection with MediaPipe & ML |
| | --- |
| | |
| | # Face Shape Detection |
| |
|
| | An AI-powered application that analyzes facial features to determine face shape using MediaPipe landmarks and machine learning. |
| |
|
| | ## Features |
| |
|
| | - **Real-time face shape detection** from uploaded images |
| | - **5 face shape categories**: Heart, Oval, Round, Square, Oblong |
| | - **Facial measurements** with confidence scores |
| | - **Interactive web interface** with image upload |
| | - **RESTful API** for integration |
| |
|
| | ## How it Works |
| |
|
| | 1. **Face Detection**: Uses MediaPipe to detect and extract facial landmarks |
| | 2. **Feature Extraction**: Calculates key facial measurements and ratios |
| | 3. **ML Classification**: Uses a trained Random Forest model to predict face shape |
| | 4. **Results**: Returns face shape, confidence scores, and facial measurements |
| |
|
| | ## API Endpoints |
| |
|
| | - `POST /analyze` - Upload an image for face shape analysis |
| | - `GET /` - Web interface for image upload |
| | - `GET /video_feed` - Real-time video feed (if camera available) |
| |
|
| | ## Usage |
| |
|
| | 1. Upload an image using the web interface |
| | 2. The system will analyze the face and return: |
| | - Detected face shape |
| | - Confidence scores for all categories |
| | - Facial measurements (length, width, etc.) |
| | - Annotated image with landmarks |
| |
|
| | ## Technical Details |
| |
|
| | - **Framework**: Flask |
| | - **Computer Vision**: MediaPipe, OpenCV |
| | - **ML Model**: Random Forest (scikit-learn) |
| | - **Image Processing**: Smart preprocessing with face detection |
| | - **Deployment**: Docker container optimized for Hugging Face Spaces |
| |
|
| | ## Model Performance |
| |
|
| | The model uses optimized features extracted from 468 facial landmarks and achieves high accuracy in face shape classification across diverse face types. |
| |
|
| | ## Requirements |
| |
|
| | - Python 3.10+ |
| | - MediaPipe |
| | - OpenCV |
| | - scikit-learn |
| | - Flask |
| | - NumPy |
| |
|
| | ## License |
| |
|
| | MIT License - feel free to use and modify for your projects. |
