Hand Gesture Recognition & Finger Drawing

This project combines hand gesture recognition with a real-time finger drawing tool built using MediaPipe, OpenCV, and NumPy.

With this demo, you can:

• Recognize hand gestures (Rock, Paper, Scissors, or None)
• Draw on the live camera feed using just your index finger

It’s designed as an interactive prototype for digital whiteboarding.

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Features

• Rock-Paper-Scissors Recognition
  Detects hand gestures and classifies them as Rock, Paper, Scissors, or None.
  (Accuracy depends on your trained recognition model.)

• Finger Drawing on Live Feed
  Tracks the index finger in real time, enabling drawing directly on the webcam stream.

• Continuous Live Video
  Uses your webcam to process frames, overlay gesture recognition, and display finger drawings instantly.

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Result:

Finger Drawing on Live Feed

Rock-Paper-Scissors Recognition

Requirements & Installation

Prerequisites

• Python 3.8+
• A working webcam

Dependencies

This project relies on the following Python libraries:

• MediaPipe – Hand tracking & gesture recognition
• OpenCV – Video capture & image processing
• NumPy – Numerical operations

Installation

Clone the repository and install the requirements:

git clone https://github.com/Haragos99/Hand-Gesture-Drawing.git
cd hand-gesture-drawing
pip install -r requirements.txt

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Requirements

This project uses Python and a few key libraries:

• MediaPipe – For real-time hand landmark detection and gesture recognition
• OpenCV – For video capture, drawing, and image processing
• NumPy – For handling image arrays and mathematical operations
• protobuf – Required by MediaPipe for model definitions
• Streamlit + streamlit-webrtc (optional) – For running the project in a browser-based app

To install all dependencies, run:

pip install -r requirements.txt