Explore the world of non-verbal communication like never before with our Body Language Detection solution. Utilizing the advanced capabilities of MediaPipe and OpenCV, we provide real-time insights into human gestures, postures, and facial expressions.

Real-time body, hand, and face landmark detection using MediaPipe. Captures keypoints from webcam, exports coordinates, and trains a machine learning model to recognize gestures or body language. Includes live prediction and visualization with OpenCV.

Real-time sign language detection using Python, OpenCV, and MediaPipe Holistic to track hand, face, and body landmarks. An LSTM model built with TensorFlow classifies gestures from video frames, enabling live recognition of sign language for improved communication accessibility.

This project uses MediaPipe and OpenCV to detect a person’s body and hands in real time through a webcam.It tracks key points, highlights palms with green circles, and shows movement using lines and dots.The system works well for gesture control, fitness tracking, or sign language detection, performing best in good lighting and clear backgrounds.