✋ Hand Tracking Real-Time CPU Python

Real-time hand tracking using Python, OpenCV, and the MediaPipe library. Detect and track hand landmarks using the CPU for efficient processing.

Introduction

This project demonstrates real-time hand tracking in Python, utilizing OpenCV and the MediaPipe library. The application captures video from your camera, processes each frame to detect and track hand landmarks, and displays the result in real-time.

Features

• Real-Time Hand Tracking: Utilizes the MediaPipe library to track hand landmarks.
• Efficient CPU Processing: Performs hand tracking using CPU resources for efficient processing.
• Visual Hand Landmarks: Draws connections between hand landmarks for visualization.
• Easy Integration: Simple Python script that can be easily integrated into other projects.

Prerequisites

• Python installed on your system.
• OpenCV library (cv2).
• MediaPipe library (mediapipe).

Installation

1. Clone the GitHub repository:

   git clone https://github.com/codeterrayt/HandTrackingRealTimeCPUPython.git
   cd HandTrackingRealTimeCPUPython

2. Install the required libraries:

   pip install opencv-python mediapipe

3. Run the hand tracking script:

   python HandTrackingRealTimeCPU.py

Usage

1. Ensure your camera is connected and working.

2. Run the script using the command mentioned in the installation steps.

3. View the real-time hand tracking on the displayed video window.

4. Press 'Q' to close the video window.

Development

The main script is HandTrackingRealTimeCPU.py. Feel free to explore and modify the code to suit your needs. Contributions are welcome!

Acknowledgments

This project uses the MediaPipe library for hand tracking. Check out the MediaPipe GitHub Repository for more information.

🤚 Happy Hand Tracking! 🎥