Real-time-Hand-gesture-recognition-system-using-OpenCV-and-mediapipeon-

🖐️ Hand Gesture Recognition with MediaPipe

An interactive Computer Vision pipeline that transforms your webcam into a gesture-controlled interface using Google’s MediaPipe and Python.

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🔴 Live Preview

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🔑 Key Features

• ⚡ Real-time Detection: High-speed hand landmark tracking (21 unique points).
• 🌐 Colab Native: Custom JavaScript bridge to access local webcams within virtual environments.
• 🧠 Logic-Based Classification: Robust rule-based engine to identify:

  • 🖐 Open Palm

    ✌️ Peace

    ✊ Fist

    👍 Thumbs Up

    ☝️ Pointing

• 🎨 Augmented Overlay: Dynamic rendering of the hand skeleton and gesture labels.

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🛠️ How It Works

The Pipeline

1. Capture: JavaScript initiates a webcam stream and captures a frame.
2. Processing: OpenCV converts images to RGB; MediaPipe maps 21 3D landmarks.
3. Inference: * Fingers: Compares TIP vs PIP y-coordinates to determine “Extended” vs “Curled”.
   • Thumb: Analyzes horizontal orientation relative to the palm base.
4. Feedback: The system annotates the image and renders it instantly.

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🚀 Getting Started

1. Launch Environment

Open this project in Google Colab to ensure the webcam JavaScript bridge executes correctly.

2. Install Dependencies

```bash pip install mediapipe opencv-python numpy

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