Gesture-Based Volume Control

Control your system volume with hand gestures using computer vision and hand tracking technologies.

Overview

This project enables users to control system volume using intuitive hand gestures. By leveraging computer vision and hand tracking, we've created a touchless interface that adjusts volume based on the distance between your thumb and index finger. This solution enhances accessibility and provides an innovative approach to user interaction.

Tech Stack

• Python 3
• OpenCV: For capturing video frames and image processing
• Mediapipe: For real-time hand detection and tracking
• PyCaw: For interacting with system audio settings
• NumPy: For numerical operations and interpolation
• Custom HandTrackingModule: A purpose-built module for advanced hand tracking features

Key Features

• 🎮 Gesture-Based Volume Control: Adjust system volume by changing the distance between thumb and index finger
• 🔍 Real-time Hand Detection: Instant hand gesture recognition using Mediapipe
• 📊 Smooth Transition: Optimized gesture recognition for fluid volume adjustments
• 🛠️ Custom HandTrackingModule: Enhanced capabilities for finger tracking and gesture recognition

Getting Started

Prerequisites

• Computer with a webcam
• Python 3.x installed

Installation

1. Clone the repository:

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

2. Navigate to the project directory:

   cd gesture-volume-control

3. Install required dependencies:

   pip install -r requirements.txt

Running the Tool

1. Start the application:

   python VolumeControl.py

2. Use hand gestures to control volume:

   • Bring thumb and index finger closer for lower volume
   • Move them apart for higher volume

3. Press 'Esc' to exit the application

How it Works

1. The webcam detects your hand in real-time
2. Position your hand in front of the camera
3. Adjust volume by changing thumb-index finger distance:
   • Closer = Lower volume
   • Wider = Higher volume
4. On-screen display shows current volume percentage

Custom HandTrackingModule

Our custom-built module enhances Mediapipe functionality with:

• Precise hand landmark detection
• Real-time distance calculation between fingers
• Specialized gesture recognition for volume control

Applications

• Accessibility: Touchless control for users with mobility challenges
• Hands-Free Environments: Ideal for presentations or cooking scenarios
• Innovation: Stepping stone for future gesture-based interfaces

Documentation

For detailed instructions and API documentation, visit our Documentation.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Contact

For questions or feedback:

• 📧 Email: [email protected]
• 🐙 GitHub: @mjgandhi2305

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Made with ❤️ by Miten Gandhi