Bryson DeChambeau Uses Google Cloud Vision Models to Dissect Every Golf Swing
DeChambeau's system deploys deep learning on Google Cloud with proprietary 2D and 3D models. It tracks over 30 body, club, and ball keypoints and labels swing phases such as top of backswing, impact, and finish. Shot outcome data are logged automatically for each repetition.
Athletes stop guessing about mechanics and start iterating from quantitative feedback. The workflow shifts from subjective coaching notes to version controlled swing data that can be compared across sessions and players.
Bryson DeChambeau partnered with Google Cloud to run the models during practice rounds. Early tests showed measurable reductions in swing variability after reviewing the labeled keypoint sequences.
Step 1: Open Google Cloud Vision documentation at https://cloud.google.com/vision and enable the Pose Detection API. Step 2: Upload a 60 fps swing video to a Cloud Storage bucket and run the 2D/3D pose model to extract the 30 keypoints. Step 3: Export the JSON output into a spreadsheet and tag each frame with swing phase labels to compare sessions.