| | --- |
| | title: Sign Language Detector Pro |
| | emoji: π |
| | colorFrom: red |
| | colorTo: yellow |
| | sdk: streamlit |
| | app_file: src/streamlit_app.py |
| | app_port: 8501 |
| | tags: |
| | - streamlit |
| | pinned: false |
| | short_description: Streamlit template space |
| | license: mit |
| | --- |
| | |
| | # Sign Language Detector Pro |
| |
|
| | An advanced Python application for detecting and interpreting sign language gestures from images and videos. Features cutting-edge computer vision using MediaPipe for hand landmark detection, AI-powered gesture classification via OpenAI API, and a modern web interface for professional analysis and reporting. |
| |
|
| | ## β¨ Enhanced Features |
| |
|
| | ### π― Core Functionality |
| | - **Advanced Hand Detection**: MediaPipe-powered 21-point hand landmark detection |
| | - **AI Gesture Classification**: OpenAI API integration for accurate sign language interpretation |
| | - **Batch File Processing**: Support for multiple images and videos simultaneously |
| | - **Professional Analytics**: Interactive charts, confidence metrics, and detailed analysis |
| |
|
| | ### π¨ Modern Web Interface |
| | - **Professional Design**: Modern, responsive UI with gradient themes and animations |
| | - **Interactive Visualizations**: 3D hand landmark plots, confidence charts, and timeline analysis |
| | - **Multiple Export Formats**: JSON, CSV, and PDF report generation |
| | - **Real-time Progress Tracking**: Enhanced progress indicators and status updates |
| |
|
| | ### π Advanced Analytics |
| | - **Confidence Scoring**: Detailed confidence metrics for all detections |
| | - **3D Visualization**: Interactive 3D plots of hand landmarks |
| | - **Timeline Analysis**: Frame-by-frame video processing with visual timelines |
| | - **Comparison Views**: Side-by-side before/after image comparisons |
| |
|
| | ## Setup |
| |
|
| | 1. Clone the repository |
| | 2. Create a virtual environment: |
| | ```bash |
| | python -m venv venv |
| | source venv/bin/activate # On Windows: venv\Scripts\activate |
| | ``` |
| |
|
| | 3. Install dependencies: |
| | ```bash |
| | pip install -r requirements.txt |
| | ``` |
| |
|
| | 4. Set up environment variables: |
| | ```bash |
| | cp .env.example .env |
| | # Edit .env and add your OpenAI API key |
| | ``` |
| |
|
| | ## Usage |
| |
|
| | ### Enhanced Command Line Interface |
| | ```bash |
| | # File processing mode (camera functionality removed) |
| | python3 main.py --input path/to/video.mp4 |
| | |
| | # Batch processing with output directory |
| | python3 main.py --input path/to/directory --output results/ |
| | |
| | # Disable speech output |
| | python3 main.py --input path/to/image.jpg --no-speech |
| | ``` |
| |
|
| | ### Professional Web Interface |
| | ```bash |
| | streamlit run app.py |
| | ``` |
| | **Features:** |
| | - Drag-and-drop file upload |
| | - Batch processing with progress tracking |
| | - Interactive 3D visualizations |
| | - Multiple export formats (JSON, CSV, PDF) |
| | - Real-time analytics dashboard |
| |
|
| | ### Demo Mode (No API Key Required) |
| | ```bash |
| | python3 demo.py |
| | ``` |
| |
|
| | ## Project Structure |
| |
|
| | - `main.py` - Main application entry point |
| | - `app.py` - Streamlit GUI application |
| | - `src/` - Source code modules |
| | - `hand_detector.py` - Hand landmark detection |
| | - `gesture_extractor.py` - Gesture feature extraction |
| | - `openai_classifier.py` - OpenAI API integration |
| | - `camera_handler.py` - Real-time camera processing |
| | - `file_handler.py` - File input processing |
| | - `output_handler.py` - Text and speech output |
| | - `tests/` - Unit tests |
| | - `examples/` - Example videos and images |
| |
|
| | ## Requirements |
| |
|
| | - Python 3.8+ |
| | - OpenAI API key (for gesture classification) |
| | - Webcam (for real-time mode) |
| |
|
| | ## Quick Start |
| |
|
| | 1. **Test without API key (Demo mode):** |
| | ```bash |
| | python3 demo.py |
| | ``` |
| | This will show hand detection and gesture analysis without requiring an OpenAI API key. |
| |
|
| | 2. **Set up OpenAI API key:** |
| | ```bash |
| | cp .env.example .env |
| | # Edit .env and add: OPENAI_API_KEY=your_key_here |
| | ``` |
| |
|
| | 3. **Run real-time detection:** |
| | ```bash |
| | python3 main.py --mode realtime |
| | ``` |
| |
|
| | 4. **Process a video file:** |
| | ```bash |
| | python3 main.py --mode file --input examples/sample_video.mp4 |
| | ``` |
| |
|
| | 5. **Launch web interface:** |
| | ```bash |
| | streamlit run app.py |
| | ``` |
| |
|
| | ## π Enhanced Features Delivered |
| |
|
| | ### β
Core Processing |
| | - **Advanced Hand Detection** - MediaPipe 21-point landmark detection with enhanced visualization |
| | - **AI-Powered Classification** - OpenAI API integration with confidence scoring |
| | - **Batch File Processing** - Simultaneous processing of multiple images and videos |
| | - **Professional Analytics** - Comprehensive metrics and statistical analysis |
| |
|
| | ### β
Modern Web Interface |
| | - **Responsive Design** - Professional UI with gradient themes and animations |
| | - **Interactive Visualizations** - 3D hand plots, confidence charts, timeline analysis |
| | - **Multiple Export Formats** - JSON, CSV, and PDF report generation |
| | - **Real-time Progress** - Enhanced progress tracking with detailed status updates |
| |
|
| | ### β
Advanced Analytics |
| | - **3D Visualization** - Interactive 3D hand landmark plots |
| | - **Timeline Analysis** - Frame-by-frame video processing visualization |
| | - **Confidence Metrics** - Detailed confidence scoring and analysis |
| | - **Comparison Views** - Side-by-side before/after image comparisons |
| | - **Summary Reports** - Comprehensive processing statistics and insights |
| |
|
| | ### β
User Experience |
| | - **Drag-and-Drop Upload** - Intuitive file upload with visual feedback |
| | - **Settings Panel** - Configurable detection parameters |
| | - **Error Handling** - User-friendly error messages and recovery |
| | - **Export Functionality** - Multiple format options for results |