Gesture Recognition with MediaPipe

This project is a gesture recognition system built using the MediaPipe framework. It allows you to recognize hand gestures from different input sources such as your webcam, images, and videos. Additionally, it provides a Streamlit interface to make the system more interactive.

Project Overview

The system is capable of recognizing gestures in real-time from:

• Webcam: Use your webcam to capture hand gestures.
• Images: Upload images for gesture recognition.
• Videos: Process video files to detect hand gestures.
• Streamlit Interface: A simple user interface using Streamlit to interact with the system.

The project relies on MediaPipe, a machine learning framework used for building perception pipelines like gesture detection.

Setup Guide

To keep the dependencies isolated, it's recommended to create a virtual environment:

bash

For Windows

python -m venv venv

For Linux/Mac

python3 -m venv venv

Activate the virtual environment:

For Windows

venv\Scripts\activate

For Linux/Mac

source venv/bin/activate

Once the virtual environment is activated, install the required Python packages:

pip install -r requirements.txt

To use your webcam for gesture recognition, run:

python app.py

To upload and recognize gestures in an image, run:

app2.py

For processing a video file and detecting gestures in it, run:

app3.py

For a user-friendly interface, you can launch the Streamlit app using the following command:

streamlit run appInterface.py

Hope this helps! If you have any questions, feel free to ask.

This README.md file provides a simple overview of the project, setup instructions, and usage guidance. It includes instructions for running each of the four Python files along with details about creating a virtual environment and installing dependencies. Let me know if you need further customization!