Welcome to the Hand Tracking Using OpenCV repository! This project allows you to track and analyze hand movements using computer vision with OpenCV. Whether you want to create gesture-controlled applications, interactive interfaces, or just explore the world of hand tracking, this repository is a great starting point.

• Real-time hand tracking.
• Hand landmark estimation, providing 21 key points on the hand.
• Hand gesture recognition for common gestures.
• Customizable and easy to integrate into your projects.

• Getting Started
• Installation
• Usage
• Documentation
• Contributing

Before you start using this repository, make sure you have the necessary prerequisites installed. Check out the Installation section for details.

1. Clone this repository:

   git clone https://github.com/PratikMore55/HandTrackingUsingOpenCV.git
   

2. Install the required Python libraries : OpenCV:

   pip install opencv-python
   

3. Mediapipe library:

   pip install mediapipe
   

This project can be used for a wide range of applications, including:

Gesture recognition for controlling devices or software. Virtual reality and augmented reality experiences. Sign language recognition. Human-computer interaction research. To get started with your own application, refer to the Documentation and explore the example code provided.

For comprehensive documentation, tutorials, and API reference, visit OpenCV's official Documentation.

Contributions are welcome! Whether you want to report a bug, request a new feature, or submit a pull request, please check our Contributing Guidelines.