Hand Gesture Control System

Overview

The Hand Gesture Control System is a computer vision-based project that enables users to interact with a computer using hand gestures. It utilizes OpenCV and MediaPipe for real-time hand tracking and gesture recognition, allowing hands-free control of various applications.

Features

• Real-time hand tracking using OpenCV and MediaPipe
• Gesture recognition for various actions
• Control system functionalities using predefined hand gestures
• User-friendly and interactive interface

Technologies Used

• Python
• OpenCV (Computer Vision Library)
• MediaPipe (Hand Tracking and Pose Estimation)
• NumPy (Scientific Computing)
• PyAutoGUI (Simulating Keyboard and Mouse Inputs)

Installation

1. Clone the repository:

    https://github.com/Yuvraj-1107-ML/Computer_Vision_Project.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the program:

   python app.py

How It Works

1. The webcam captures real-time video input.
2. MediaPipe detects and tracks hand landmarks.
3. Custom gestures are mapped to specific system commands.
4. Using PyAutoGUI, gestures trigger corresponding actions (e.g., volume control, mouse movement, media playback).

Usage

• Two-Finger Pinch: Zoom In/Out

Future Improvements

• Add support for more complex gestures.
• Integrate with smart home devices.
• Improve accuracy using machine learning models.

Contributing

Contributions are welcome! Feel free to fork the repository and submit pull requests.