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hand-detection-project

This project implements a real-time hand detection system using Python, leveraging MediaPipe's robust hand detecting solution and OpenCV for video capture and visualization. The system accurately identifies and detects hand landmarks.

Features

• Hand Detection and Tracking: Detects and tracks 21 hand landmarks in real-time.
• Real-Time Performance: Efficient processing ensures smooth and responsive hand detection.

Installation

1. Clone the repository:

   git clone https://github.com/CyberBoy-Mayank/hand-detection-project.git
   cd hand-detection-project

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the hand main script:

   python main.py

2. The script will start capturing video from your in-built webcam and display the detected hand landmarks in real-time.

Example Output

![Hand Detection Example]

Benefits

• High Accuracy: Utilizes MediaPipe's advanced hand detection model for precise landmark detection.
• Real-Time Processing: Ensures smooth and responsive hand detection suitable for interactive applications.
• Extensible: Easily customizable to include additional features such as custom gesture recognition.
• User-Friendly: Simple to set up and use, making it accessible for both beginners and advanced users.

Note

• I'm using Python Version: 3.10.2 for this project.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

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