Running Form Analyzer

A computer vision application that analyzes running gait and form in real-time or from video footage.

Features (MVP)

1. Real-time pose detection - Track 33 body keypoints using MediaPipe
2. Gait analysis - Analyze stride length, cadence, and body alignment
3. Form feedback - Provide real-time feedback on running technique
4. Video processing - Analyze pre-recorded running videos
5. Data visualization - Generate charts and reports of running metrics

Project Structure

form-analyzer/
├── src/
│   ├── __init__.py
│   ├── pose_detector.py      # Core pose detection logic
│   ├── gait_analyzer.py      # Running form analysis
│   ├── video_processor.py    # Video input/output handling
│   └── utils.py              # Helper functions
├── tests/
│   └── __init__.py
├── data/                     # Sample videos and output
├── requirements.txt
└── main.py                   # Main application entry point

Installation

1. Create and activate virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

Usage

Real-time Analysis

python main.py --mode realtime

Video Analysis

python main.py --mode video --input path/to/video.mp4

System Design

The application follows a modular architecture:

1. Input Layer: Camera feed or video file
2. Pose Detection Layer: MediaPipe for real-time pose estimation
3. Analysis Layer: Custom algorithms for gait analysis
4. Output Layer: Real-time feedback and data visualization

Key Technologies

• MediaPipe: Google's ML framework for pose detection
• OpenCV: Computer vision operations and video processing
• TensorFlow: Deep learning models for enhanced pose estimation
• NumPy/SciPy: Numerical computations and signal processing