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Real-time Hand Gesture Recognition System using OpenCV

This project is aimed at developing a hand gesture recognition system that can be utilized over a web browser using WebRTC technology. The system is intended to assist mute individuals by providing them with a means of communication through hand gestures. The project utilizes Python, OpenCV, MediaPipe, Streamlit-webRTC, and digital image processing techniques to achieve its objectives. Furthermore, the application has been containerized using Docker for cross-platform execution.

Author

Features

  • Real-time hand gesture recognition using OpenCV and MediaPipe.
  • Integration with WebRTC for web browser compatibility.
  • Utilization of Python for backend processing.
  • Streamlit for creating a user-friendly web interface.
  • Docker containerization for seamless deployment across different platforms.

Requirements

  • Python 3.x
  • OpenCV
  • MediaPipe
  • Streamlit
  • Docker

Installation

Clone the repository :

 git clone https://github.com/your-username/your-repository.git

Navigate to the project directory :

 cd Real-time..

Install dependencies:

 pip install -r requirements.txt

 or use Pycharm to manually install them and run