README.md

metadata

title: Sign Language Detector Pro
emoji: 🚀
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.

✨ Enhanced Features

🎯 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

🎨 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

📊 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:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Set up environment variables:

   cp .env.example .env
   # Edit .env and add your OpenAI API key
   

Usage

Enhanced Command Line Interface

# 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

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)

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):

   python3 demo.py
   

   This will show hand detection and gesture analysis without requiring an OpenAI API key.

2. Set up OpenAI API key:

   cp .env.example .env
   # Edit .env and add: OPENAI_API_KEY=your_key_here
   

3. Run real-time detection:

   python3 main.py --mode realtime
   

4. Process a video file:

   python3 main.py --mode file --input examples/sample_video.mp4
   

5. Launch web interface:

   streamlit run app.py
   

🚀 Enhanced Features Delivered

✅ 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

✅ 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

✅ 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

✅ 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