🤖 Hand Gesture Recognition System

A real-time hand gesture recognition system that uses computer vision to control your computer's volume through hand gestures. Built with Python, OpenCV, and MediaPipe.

✨ Features

• Real-time Hand Detection: Uses MediaPipe for accurate hand landmark detection
• Volume Control: Control system volume with simple hand gestures
• Multiple Gestures: Support for index finger up and fist gestures
• Live Video Feed: Real-time camera feed with hand landmark visualization
• Cross-platform: Works on Windows, macOS, and Linux
• Easy to Use: Simple setup and intuitive gesture controls

🎯 Supported Gestures

Gesture	Action	Description
👆 Index Finger Up	Increase Volume	Point your index finger upward
✊ Fist	Decrease Volume	Make a fist with your hand

📋 Requirements

• Python 3.9 or higher
• Webcam
• Windows OS (for volume control functionality)

🚀 Installation

1. Clone the Repository

git clone <repository-url>
cd hand_gesture

2. Install Dependencies

pip install -r requirements.txt

3. Additional Dependencies

For volume control on Windows, install:

pip install pycaw

🎮 Usage

Basic Usage

python main.py

How to Use

1. Start the Program: Run python main.py
2. Show Your Hand: Position your hand in front of the camera
3. Make Gestures:
   • Index finger up → Increase volume by 1%
   • Fist → Decrease volume by 1%
4. Exit: Press ESC key to quit

Tips for Better Recognition

• Ensure good lighting conditions
• Keep your hand clearly visible to the camera
• Maintain a reasonable distance from the camera (30-200cm)
• Use clear, deliberate gestures

🏗️ Project Structure

hand_gesture/
├── main.py                 # Main application entry point
├── requirements.txt        # Python dependencies
├── README.md              # Project documentation
├── src/
│   ├── __init__.py        # Package initialization
│   ├── camera.py          # Camera interface and frame capture
│   ├── hand_detector.py   # Hand detection using MediaPipe
│   ├── gesture_classifier.py # Gesture recognition logic
│   ├── volume_control.py  # System volume control interface
│   ├── config.py          # Configuration settings
│   └── utils.py           # Utility functions

🔧 Configuration

Edit src/config.py to customize settings:

# Camera settings
CAMERA_ID = 0              # Camera device ID
FRAME_WIDTH = 640          # Frame width
FRAME_HEIGHT = 480         # Frame height

# Hand detection settings
MAX_NUM_HANDS = 1          # Maximum hands to detect
DETECTION_CONFIDENCE = 0.7 # Detection confidence threshold
TRACKING_CONFIDENCE = 0.7  # Tracking confidence threshold

# Distance settings
MIN_DISTANCE = 30          # Minimum hand distance
MAX_DISTANCE = 200         # Maximum hand distance

🛠️ Technical Details

Core Components

1. Camera Module (src/camera.py)

• Handles webcam initialization and frame capture
• Supports configurable resolution and camera selection

2. Hand Detector (src/hand_detector.py)

• Uses MediaPipe for real-time hand landmark detection
• Tracks 21 hand landmarks (fingertips, joints, etc.)
• Provides hand skeleton visualization

3. Gesture Classifier (src/gesture_classifier.py)

• Analyzes hand landmarks to classify gestures
• Currently supports:
  • Index Finger Up: Landmark 8 (fingertip) above landmark 6 (joint)
  • Fist: All fingers closed

4. Volume Control (src/volume_control.py)

• Interfaces with Windows audio system using pycaw
• Provides volume get/set functionality
• Handles volume range mapping (0-100%)

Hand Landmarks

MediaPipe detects 21 hand landmarks:

• Landmarks 0-4: Thumb
• Landmarks 5-8: Index finger
• Landmarks 9-12: Middle finger
• Landmarks 13-16: Ring finger
• Landmarks 17-20: Pinky

🔍 Troubleshooting

Common Issues

1. Camera Not Found

Error: Could not open camera!

Solution: Check if your webcam is connected and not in use by another application.

2. MediaPipe Import Error

ModuleNotFoundError: No module named 'mediapipe'

Solution: Install MediaPipe for your Python version:

pip install mediapipe

3. Volume Control Not Working

Solution: Ensure you're running on Windows and have pycaw installed:

pip install pycaw

4. Poor Hand Detection

Solutions:

• Improve lighting conditions
• Keep hand clearly visible
• Adjust distance from camera
• Check detection confidence settings

Performance Tips

• Use a good quality webcam for better detection
• Ensure adequate lighting
• Close unnecessary applications to free up system resources
• Adjust confidence thresholds in config.py if needed

🚧 Future Enhancements

• Support for more gestures (thumbs up, peace sign, etc.)
• Gesture recording and custom gesture training
• Support for multiple hands
• Cross-platform volume control
• GUI interface
• Gesture history and statistics
• Machine learning-based gesture recognition

🤝 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 file for details.

🙏 Acknowledgments

• MediaPipe - Hand tracking and detection
• OpenCV - Computer vision library
• pycaw - Windows audio control

📞 Support

If you encounter any issues or have questions:

1. Check the troubleshooting section above
2. Search existing issues in the repository
3. Create a new issue with detailed information

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Made with ❤️ for computer vision enthusiasts