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This repository contains a Python-based hand gesture recognition system that allows users to control applications using simple hand gestures. The system leverages the MediaPipe framework for real-time hand tracking and finger counting. Users can interact with their computers hands-free, making it ideal for presentations, media playback, and more.
The Hand Tracking Module is easy to be integrated within any project. It is based on Python 3.9 and 3.8 and supports python 3.9 and above. The module uses extensive libraries such as newly launched OpenCV 4.6 for best results and Mediapipe 0.8 to track hand movements and points more specifically. The applications which include volume control, ge…
This repository contains code for a real-time hand gesture recognition system using MediaPipe and OpenCV. The project enables users to control music playback by detecting hand gestures captured through a webcam.
This Python script utilizes the OpenCV library to perform real-time hand gesture recognition using a webcam. It employs a pre-trained hand detection model from the HandTrackingModule to detect and track landmarks on the hand.
This is a computer vision-based raised finger counter program that utilizes the MediaPipe library to identify hand landmarks and extract relevant information to count the number of raised fingers in a live webcam feed.