An extension of the previous 'Fitness-AI-Coach': a complete web application with real-time exercise recognition and counting. The exercise recognition model achieves 99% accuracy on the test set and 95% and 90% on two additional external datasets. || Give a star ⭐ to the repository if it was useful. Thank you! 😊

Learning to learn for Personalised Human Activity Recognition

A lightweight, privacy-first, real-time rep counter for common bodyweight exercises. GC_Fit uses MediaPipe's Pose model and OpenCV to detect joint landmarks from a webcam feed and count repetitions of exercises (push-ups, sit-ups, squats) based on simple geometric rules.

A real-time fitness pose detection system for recognizing push-ups, squats, and sit-ups using MediaPipe and LSTM

A smart, wearable glove that recognizes and tracks exercise movements using AI, real-time feedback, and an interactive button interface.