dyneth02/MoveNet-Multipose-Detection-OpenCV
A real-time multi-person human pose estimation system using TensorFlow MoveNet Multipose (Lightning). Built with OpenCV for video and webcam inference, it detects and visualizes keypoints and skeletal connections with confidence-based filtering, optimized for speed and multi-person scenarios.
This tool helps you analyze human movement in real-time from video files or a live camera feed. It takes your video or webcam stream and identifies up to six people, showing their body keypoints and skeletal connections. Fitness instructors, sports coaches, and surveillance operators could use this to track movement.
Use this if you need to automatically detect and visualize the poses of multiple people simultaneously for applications like fitness analysis or security monitoring.
Not ideal if you only need to detect single-person poses or require extremely high precision for medical-grade motion capture.
Stars
8
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 02, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/dyneth02/MoveNet-Multipose-Detection-OpenCV"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DeepLabCut/DeepLabCut
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with...
openpifpaf/openpifpaf
Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and...
lambdaloop/anipose
🐜🐀🐒🚶 A toolkit for robust markerless 3D pose estimation
DIYer22/bpycv
Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
NeLy-EPFL/DeepFly3D
Motion capture (markerless 3D pose estimation) pipeline and helper GUI for tethered Drosophila.