🏌️‍♂️ How I Built a Golf Swing Analyzer in Python Using AI Pose Detection (That Actually Works)

⛳ Why This Project Matters

Golf has always been a game of inches , a micro-adjustment in wrist angle, a fraction of a second in timing, or a subtle shift in posture can be the difference between a 300-yard drive and a slice into the trees.

Traditionally, only elite players with access to swing coaches, motion capture systems, or $10,000 launch monitors could dissect their biomechanics. Everyone else? We just squint at slow-mo YouTube replays of Tiger and hope for the best.

That gap is what I set out to solve.


What if anyone, anywhere, with nothing more than a smartphone video and a Colab notebook, could access near-pro-level swing diagnostics?

That was the genesis of GolfPosePro , an AI-powered golf swing analyzer that:

• Tracks your swing phases frame-by-frame with pose estimation.
  


• Visualizes biomechanics (like wrist trajectory) in debug plots.
  


• Compares your motion to PGA Tour pros , side-by-side.
  


• Generates enhanced playback with slow motion, labeled overlays, and pro benchmarks.
  

All built with Python, MediaPipe, OpenCV, matplotlib, and Google Colab Pro.


This isn’t just about golf — it’s a case study in democratizing biomechanics through AI.

⚙️ What It Does

• 🧠 Extracts wrist motion from your swing video.
  


• 🪄 Segments swing phases dynamically:
  Address → Backswing → Top → Downswing → Impact → Follow-through
  


• 🔍 Overlays debug plots of wrist trajectory, velocity, and key checkpoints.
  


• 🎯 Runs side-by-side comparisons against PGA swings (downloaded with yt-dlp).
  


• 🐢 Encodes slow-motion video segments, highlighting your motion frame-by-frame.
  

🏌️ Built For

• Amateurs → Upload iPhone swing clips, get coach-like insights.


• Coaches → Use it as a feedback tool without expensive sensors.


• Developers → A sandbox for exploring pose detection + video analytics.
  This notebook isn’t replacing coaches or TrackMan — but it’s democratizing access to biomechanics.

🙏 Credits

• Pro swing footage: YouTube Shorts (Max Homa, Ludvig Åberg).


• Frameworks: MediaPipe, OpenCV, matplotlib, FFmpeg.


• Countless test swings (and slices) on the driving range.

🚀 What’s Next

• 🗣️ AI coach commentary overlay.


• 🏌️ Support for left-handed players (pose normalization).


• 🎥 Ball tracer integration.


• 📊 Automatic swing grading with ML classifiers.


• 📱 Mobile-friendly UI.

🏁 Final Thoughts

Golf is often said to be a battle between the player and themselves.
By applying AI pose detection, we finally have a way to quantify the invisible — turning milliseconds of motion into data you can act on.

This project isn’t just about golf.
It’s a glimpse of how AI can democratize performance analysis across all sports.

And for me? It’s about making practice smarter, not just longer.

⛳ Let’s bring AI to the range — one frame at a time

If you enjoyed this project, consider buying me a coffee to support more free AI tutorials and tools:


👉