Real-time ASL interpreter using OpenCV and TensorFlow/Keras for hand gesture recognition. Features custom hand tracking, image preprocessing, and gesture classification to translate American Sign Language into text and speech output. Built with accessibility in mind.

Real-time Human Emotion Detection system using deep learning and facial expression recognition. Built with Python, TensorFlow/Keras, and a user-friendly GUI.

This repository contains code for detecting sign language gestures using YOLOv5. It includes data collection, model training, and detection scripts.

A real-time American Sign Language (ASL) recognition system that tracks 21 hand landmarks using MediaPipe and classifies A–Z gestures with a TensorFlow neural network. Includes dataset capture tool, training pipeline, and live webcam prediction. Works on any laptop (no GPU needed).

A piano that can be controlled using real-time gestures

SignSense is a web application built with Flask and deep learning technologies like TensorFlow and Keras. It is designed to recognize hand signs and provide sign language recognition in real-time. 🚀

Hand gesture recognition system with an mobile app to play a game of Rock-Paper-Scissors