Real-Time Neon Hand Tracking

A real-time computer vision project that detects and tracks human hands using MediaPipe and OpenCV, enhanced with dynamic neon visual effects and particle animations.

✨ Features Real-time hand detection 21-point hand landmark tracking Supports up to 2 hands Smooth hand movement tracking Dynamic neon visualization Particle and spark effects Real-time camera processing Lightweight and interactive interface 🛠️ Technologies Used Python OpenCV MediaPipe NumPy Colorsys 🧠 How It Works

The application captures live video through the webcam and processes each frame using OpenCV.

MediaPipe detects the hand and identifies its landmarks. These landmark coordinates are then used to create a visual neon effect around the hand, along with dynamic particles and animations.

Processing Pipeline

Webcam → OpenCV → MediaPipe → Hand Landmarks → Visual Effects → Real-Time Output

Interested in Artificial Intelligence, Machine Learning, Computer Vision, and Deep Learning.