lightweight-human-pose-estimation.pytorch

Why we included this project

This repo implements the Lightweight OpenPose paper, which compresses the original OpenPose approach so that multi-person pose estimation runs in real time on a plain CPU instead of needing a GPU. It detects up to 18 body keypoints per person, covering the full skeleton from head to ankles, with only a small accuracy trade-off versus the heavier model. The repository includes training code for COCO 2017, validation scripts, and working Python and C++ demos, plus a pre-trained model so you can test it right away. That makes it a useful starting point for engineers shipping pose detection on edge devices, and for anyone who wants to see how a complex keypoint-and-connection network can be slimmed down without collapsing.