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| title: Sign Language Interpreter | |
| emoji: "🤟" | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: streamlit | |
| sdk_version: "1.24.0" | |
| app_file: simple_sign_interpreter.py | |
| pinned: false | |
| # 🤟 Sign Language Interpreter | |
| A real-time sign language recognition system built with Python, MediaPipe, TensorFlow, and Streamlit. This application can detect and interpret sign language gestures in real-time using computer vision and machine learning. | |
| ## 🌟 Features | |
| - **Real-time Hand Detection**: Uses MediaPipe for accurate hand landmark detection | |
| - **Sign Language Recognition**: Supports 29 gestures including: | |
| - Numbers: 1, 2, 4, 5, 6, 7, 8 | |
| - Letters: A-X (excluding E) | |
| - **Live Webcam Processing**: Real-time gesture recognition through webcam | |
| - **Interactive Web Interface**: Built with Streamlit for easy use | |
| - **Adjustable Confidence**: Configurable detection confidence threshold | |
| - **Optimized Performance**: Fast response with temporal prediction smoothing | |
| ## 🚀 Quick Start | |
| ### Prerequisites | |
| - Python 3.8+ | |
| - Webcam | |
| - Git | |
| ### Installation | |
| 1. **Clone the repository** | |
| ```bash | |
| git clone https://github.com/yourusername/ai-sign-language-interpreter.git | |
| cd ai-sign-language-interpreter | |
| ``` | |
| 2. **Install dependencies** | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| 3. **Run the application** | |
| ```bash | |
| streamlit run simple_sign_interpreter.py | |
| ``` | |
| 4. **Open your browser** and navigate to `http://localhost:8501` | |
| ## 🎯 Usage | |
| 1. **Start the application** using the command above | |
| 2. **Allow camera access** when prompted by your browser | |
| 3. **Click "START"** to begin webcam capture | |
| 4. **Show hand gestures** to the camera | |
| 5. **Adjust confidence threshold** using the sidebar slider for better detection | |
| 6. **View real-time predictions** in the "Current Sign" panel | |
| ## 📁 Project Structure | |
| ``` | |
| ai-sign-language-interpreter/ | |
| ├── simple_sign_interpreter.py # Main Streamlit application | |
| ├── sign_utils.py # Core prediction and landmark detection | |
| ├── models/ | |
| │ ├── sign_model.tflite # Trained TensorFlow Lite model | |
| │ └── labels.txt # Class labels for gestures | |
| ├── requirements.txt # Python dependencies | |
| ├── .gitignore # Git ignore file | |
| └── README.md # Project documentation | |
| ``` | |
| ## 🔧 Technical Details | |
| ### Architecture | |
| - **Frontend**: Streamlit web interface | |
| - **Computer Vision**: MediaPipe for hand landmark detection | |
| - **Machine Learning**: TensorFlow Lite for gesture classification | |
| - **Real-time Processing**: Optimized prediction pipeline with temporal smoothing | |
| ### Model Information | |
| - **Input**: 63-dimensional hand landmark features (21 landmarks × 3 coordinates) | |
| - **Output**: 29 sign language gesture classes | |
| - **Format**: TensorFlow Lite (.tflite) for optimized inference | |
| - **Performance**: Real-time processing at 30+ FPS | |
| ### Key Components | |
| 1. **MediaPipeLandmarksModel**: Handles hand detection and landmark extraction | |
| 2. **SignLanguagePredictor**: Manages model inference and prediction smoothing | |
| 3. **Streamlit Interface**: Provides user-friendly web interface | |
| ## 🎛️ Configuration | |
| ### Adjustable Parameters | |
| - **Detection Confidence**: Minimum confidence for hand detection (default: 0.5) | |
| - **Tracking Confidence**: Minimum confidence for hand tracking (default: 0.5) | |
| - **Prediction Threshold**: Minimum confidence for gesture prediction (default: 0.5) | |
| - **Buffer Size**: Number of frames for prediction smoothing (default: 8) | |
| ## 🤝 Contributing | |
| 1. Fork the repository | |
| 2. Create a feature branch (`git checkout -b feature/amazing-feature`) | |
| 3. Commit your changes (`git commit -m 'Add amazing feature'`) | |
| 4. Push to the branch (`git push origin feature/amazing-feature`) | |
| 5. Open a Pull Request | |
| ## 📝 License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |
| ## 🙏 Acknowledgments | |
| - **MediaPipe** for hand landmark detection | |
| - **TensorFlow** for machine learning framework | |
| - **Streamlit** for the web interface | |
| - **OpenCV** for computer vision utilities | |
| ## 📞 Support | |
| If you encounter any issues or have questions: | |
| 1. Check the [Issues](https://github.com/kris07hna/SIGN-LANG-INTREPRETOR/issues) page | |
| 2. Create a new issue with detailed description | |
| 3. Include system information and error messages | |
| ## 🔮 Future Enhancements | |
| - [ ] Support for more sign language gestures | |
| - [ ] Multi-hand gesture recognition | |
| - [ ] Sign language sentence formation | |
| - [ ] Mobile app version | |
| - [ ] Real-time translation to multiple languages | |