Overview: The Sign Language Detection project is a Sign Language Recognition System that recognizes alphabets using hand gestures. It utilizes MediaPipe for hand gesture detection and other machine learning techniques for recognizing and classifying the hand shapes corresponding to different letters of the alphabet.

Idea: During the process of learning various ML tools i came across opencv and other tools, at the same timeperiod i met some of the differenty-abled people who could only communicate using their hand gesture, at that time the idea of this project came across my mind.

Challenges: One of the main challenges was properly training the model with multiple alphabets and ensuring their vector encoding were proper.

Technologies Used: MediaPipe, OpenCV, Tensorflow, numpy