Golf Swing AI
A computer vision system that brings professional-grade biomechanical analysis to every golfer's pocket.
Overview
Golf Swing AI is a full-stack machine learning application that captures video of a golfer's swing and delivers real-time pose analysis and correction feedback. It bridges the gap between expensive professional coaching and the self-taught amateur golfer.
The system processes video frames through a MediaPipe pipeline to extract 3D skeleton coordinates, computes joint angles, classifies swing phase, and compares biomechanical signatures against a dataset of professional swings to generate prioritized correction recommendations.
The Problem
- Professional swing coaching costs $100–$300 per session
- Amateur golfers lack access to biomechanical feedback
- Video review requires trained professionals to interpret
- Generic tips don't address individual mechanics
The Solution
- Free, instant AI analysis accessible from any device
- Pose estimation extracts precise joint angles automatically
- ML models compare against professional swing patterns
- Personalized, prioritized corrections based on skill level
What it does
Real-time Pose Detection
MediaPipe detects 33 body landmarks at 30+ FPS for live swing analysis.
Instant Feedback
Biomechanical scores and correction tips appear within milliseconds of each swing.
Custom ML Models
Fine-tuned classifiers identify swing phases: address, backswing, impact, follow-through.
Skill-Level Aware
Adaptive feedback calibrated to beginner, intermediate, and advanced golfers.
Built with
Vision & AI
- MediaPipe
- TensorFlow / Keras
- OpenCV
- NumPy
- scikit-learn
App Layer
- Python 3.11
- Streamlit
- FastAPI (optional backend)
Data & Analytics
- Pandas
- Matplotlib
- Seaborn
Deployment
- Streamlit Cloud
- Docker
- GitHub Actions
Built end-to-end by Aneesh
Designed the full ML pipeline from data collection to deployment
Built and tuned the pose estimation + swing classification models
Developed the Streamlit web interface and deployed to cloud