Computer Vision
FitLens
Real-time fitness form assistant using pose estimation, movement analysis, and voice-guided feedback.
Overview
FitLens is an AI fitness companion that acts as a real-time form coach, translating raw spatial tracking points into clear biomechanical feedback.
The system handles sub-second coordinate tracking and instantaneous audio queues to help users execute compound lifts safely and correctly.
Tech Stack
Vision
MediaPipe Pose Framework
OpenCV Image Pipelines
Backend
Flask Application Framework
Mathematics
NumPy Coordinate Trigonometry
Features
+ Low-latency landmark-based pose estimation
+ Real-time rule-based exercise angular analysis
+ Dynamic interactive text-to-speech voice coaching
+ Continuous vector coordinate movement tracking
+ Asynchronous feedback evaluation loop
Architecture
Hardware Camera Capture API
->MediaPipe Landmark Extractor Engine
->Biomechanical Rule Matcher Core
->Audio Synthesis Voice Engine
->Interactive Client Session
Challenges
Processing high-frequency computer vision streams while generating clear, non-delayed audio queues proved computationally bottlenecked.
Isolated the visual processing step from the voice trigger logic to maximize throughput across hardware threads.
Configured trigonometric tolerance matrices to account for user height and variable camera perspectives.
Lessons Learned
- Implementation details of coordinate-based human pose structures
- Performance and loop optimization profiles for real-time computer vision
- User-experience patterns for real-time voice-activated feedback systems