Fitness Form Analyzer with Pose Detection
Investment
$102 CAD
Course structure
Build Schedule
- Video capture setup with frame rate optimization
- Pose estimation model integration and calibration
- Joint angle calculation and biomechanics validation
- Exercise library with proper form reference data
- Real-time feedback system with visual overlays
- Repetition counting with accuracy tracking
- Workout history and progress analytics
- Performance testing across different lighting conditions
Exercise Coverage
Includes analysis for squats, lunges, push-ups, planks, and deadlifts, with plans to expand to Olympic lifts.
What you'll build
The app uses your phone camera to track body position during exercises and provides instant corrections when form breaks down. Machine learning models detect joint angles and body alignment, comparing them against proper technique standards for each movement.
Real-time analysis happens on the device, tracking multiple body landmarks simultaneously. When the system detects improper form, it offers specific corrections like adjusting hip height during squats or maintaining neutral spine position during deadlifts.
Students implement pose estimation using pre-trained models and customize them for fitness applications. The project covers real-time video processing optimization, angle calculation from skeletal tracking data, and designing clear visual cues that guide users without overwhelming them during workouts.
Included in this program
By the numbers
67
Code samples
14
Integration patterns
8
AI model types
22
Technique demonstrations