The Hand-Tracking-Volume-Control project is an innovative Python application that allows users to control the volume of their computer using hand gestures. Utilizing the power of the MediaPipe library, this project offers a unique way to interact with your device, making volume control more accessible and fun.
- Hand Gesture Recognition: Leverages the MediaPipe library for accurate hand tracking and gesture recognition.
- Volume Control: Adjust the volume of your primary audio output device by simply moving your hand up or down.
- Real-Time Feedback: Provides immediate response to hand movements, ensuring a seamless user experience.
Before you begin, ensure you have met the following requirements:
- Python 3.6 or above installed on your computer.
- A webcam or any compatible camera module for hand tracking.
To install Hand-Tracking-Volume-Control, follow these steps:
- Clone the repository or download the source code: git clone https://github.com/xn-coder/Hand-Tracking-Volume-Control.git
- Navigate to the project directory: cd Hand-Tracking-Volume-Control
- Install the required dependencies: pip install -r requirements.txt
To use Hand-Tracking-Volume-Control, follow these steps:
- Run the application: python AIVolume.py
- Place your hand in front of the camera. The application will track your hand's position and adjust the volume accordingly:
- Move your hand up to increase the volume.
- Move your hand down to decrease the volume.
Contributions to the Hand-Tracking-Volume-Control project are welcome. If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
- This project is built using the MediaPipe framework for hand tracking and pose estimation.
- Special thanks to the pycaw library for controlling the system volume.
The Hand-Tracking-Volume-Control project is developed and maintained by @xn-coder. It's an open-source initiative designed to explore and demonstrate the capabilities of hand tracking technology for practical applications.
For more information, please visit the project repository.