Hand Gesture Control Systems

This repository contains two powerful computer vision-based gesture control applications:

1. AI Virtual Keyboard - Type without touching your physical keyboard
2. Advanced Virtual Mouse - Control your cursor with hand gestures

Both applications use webcam input to track hand movements and translate them into keyboard or mouse actions, providing a touchless interface for computer interaction.

Features

AI Virtual Keyboard

• Virtual on-screen keyboard with visual feedback
• Type by making "clicking" gestures with your hand
• Text editing capabilities and cursor control
• Word suggestions and autocorrection
• Special keys (Space, Backspace, Shift, Enter, etc.)
• Page navigation controls
• Zoom functionality
• Audio feedback for keypresses

Advanced Virtual Mouse

• Control cursor movement with hand gestures
• Perform left and right clicks
• Drag and drop functionality
• Scrolling (single and continuous modes)
• Zoom control
• Multiple gesture modes with visual indicators

Requirements

opencv-python
numpy
mediapipe
autopy
pyautogui
pygame

Installation

1. Clone this repository:

git clone https://github.com/yourusername/hand-gesture-control.git
cd hand-gesture-control

2. Install dependencies:

pip install opencv-python numpy mediapipe autopy pyautogui pygame

Usage

Running the AI Virtual Keyboard

python virtual_keyboard.py

Running the Advanced Virtual Mouse

python virtual_mouse.py

Gesture Controls

AI Virtual Keyboard

• Move your hand to position the cursor
• Bring your index and middle fingers together to "click" keys
• Distance between fingers must be less than 40 pixels to register a click

Advanced Virtual Mouse

• Two fingers up (index and middle): Move cursor
• Middle finger down, index up: Right-click
• Index finger down, middle up: Left-click
• Closed fist: Start drag operation (hold and move)
• Opening hand after drag: End drag operation
• Three fingers up: Single scroll mode (move hand up/down to scroll)
• Four fingers up: Continuous scroll mode with variable speed
• Five fingers up: Zoom mode (move hand up to zoom in, down to zoom out)

Implementation Details

Both applications use MediaPipe's hand tracking solution to detect hand landmarks in real-time. The systems process these landmarks to determine finger positions and gestures, which are then mapped to keyboard or mouse actions.

Key components include:

• Hand detection and tracking
• Gesture recognition algorithms
• Coordinate mapping and transformation
• User interface elements
• Performance optimization for real-time operation

Customization

You can modify these parameters in the code to customize your experience:

AI Virtual Keyboard

• Keyboard layout and key size
• Click detection threshold
• Sound effects
• Word suggestion dictionary
• Auto-correction pairs

Advanced Virtual Mouse

• Gesture cooldown times
• Scroll speed
• Movement smoothening factor
• Click detection sensitivity

Troubleshooting

• Poor detection: Ensure you have good lighting conditions
• Cursor jitter: Increase the smoothening factor
• Accidental clicks: Adjust the click detection threshold
• Performance issues: Reduce camera resolution or close background applications

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• MediaPipe team for their excellent hand tracking solution
• OpenCV community for computer vision tools
• PyAutoGUI developers for system control capabilities