/Hand-Tracking-Project

🖐️ Real-time hand tracking using OpenCV and MediaPipe. Detect hands, landmarks, and visualize results from your webcam.

Primary LanguagePython

🖐️ Hand-Tracking-Project

A real-time hand tracking project using OpenCV and MediaPipe that efficiently detects and visualizes hand landmarks through your webcam feed.
Great for gesture recognition, interactive interfaces, and experimentation!

✨ Features

  • 👐 Detects up to two hands simultaneously in live video.
  • 🎯 Draws clear hand landmarks and connections on each frame.
  • 📍 Returns the position of each landmark for further use, like gesture recognition.
  • 🖨️ Prints landmark coordinates to the console.
  • ⚡ Displays real-time FPS overlay for performance insight.

🛠️ Requirements

  • Python 3.6+
  • OpenCV (cv2)
  • MediaPipe

Install dependencies:# Hand-Tracking-Project

🚀 Getting Started

  1. Clone this repository: 
    git clone https://github.com/your-username/Hand-Tracking-Project.git
cd Hand-Tracking-Project
  2. Run the main hand tracking module: 
    python HTModule.py
  3. Quit:
    Focus the image window and press q to exit.

📂 Files Included

  • HTModule.py: Main, modular hand tracker with landmark detection and visualization.
  • HandTracking.py: Simple, single-script version for experiments and quick demos.

📝 How It Works

  1. 📷 Captures frames from your camera.
  2. 🤚 Detects & tracks hands with MediaPipe.
  3. 🖊️ Draws landmarks and hand connections on video.
  4. 💻 Prints coordinates of hand landmarks to console.
  5. ⏱️ Overlays FPS metric for real-time feedback.

⚙️ Customization

  • Adjust number of hands, confidence thresholds, or visualization options in the handDetector class.
  • Use printed landmark lists to build your own gesture controls or hand-based interfaces!

📄 License

Open-source under the MIT License.

🔗 References

🙋‍♂️ Issues or ideas? Open an issue or a pull request – contributions welcome!