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.

Exercise Detector is a real-time system that recognizes 7 different exercises using pose estimation and deep learning. It analyzes exercise form, counts repetitions, and achieves 99% accuracy on real-world detection. The lightweight model is optimized for edge devices, enabling fast and efficient performance on mobile and low-end hardware.

Deadlift-o-Meter is a project that utilizes a Scikit-Learn model, Mediapipe, and Tkinter to count correct deadlift reps using a live webcam feed. The application analyzes the user's body movements and provides real-time feedback on their performance.