This repository contains a Hand Gesture Recognition system implemented using a combination of Scikit-Learn for machine learning, Tkinter for the user interface, and MediaPipe for efficient hand tracking. The goal of this project is to enable intuitive and hands-free control of applications through the recognition of various hand gestures.
Machine Learning Model: The core of the system involves training a Random Forest Classifier using Scikit-Learn. The model is designed to accurately recognize a variety of hand gestures.
User Interface with Tkinter: The graphical user interface is developed using Tkinter, providing an interactive platform for users to control applications seamlessly through hand gestures.
Efficient Hand Tracking with MediaPipe: MediaPipe is utilized for robust hand tracking, ensuring accurate and real-time detection of hand movements.
