AlphaPose
lightweight-human-pose-estimation.pytorch
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| AlphaPose | lightweight-human-pose-estimation.pytorch | |
|---|---|---|
| 4 | 2 | |
| 7,716 | 2,021 | |
| 1.5% | - | |
| 0.0 | 0.0 | |
| 4 months ago | about 1 month ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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AlphaPose
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Help finding an appropriate model for human pose estimation
alphapose: havent tried it, but looks to run at 16fps (maybe faster?) but is only intended for research not commercial. Training script available.
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[P] Gait Recognition in the wild
The model is an ST-GCN trained in a completely unsupervised manner, from a LOT of skeleton sequences. Pose estimation was performed with AlphaPose, and tracked using SORT.
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Human Pose Estimation Recommendation
Link: https://github.com/MVIG-SJTU/AlphaPose
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Tetris but you are the bricks
Pretty sure the software has improved enough to the point where it's pretty good https://github.com/MVIG-SJTU/AlphaPose
lightweight-human-pose-estimation.pytorch
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Help finding an appropriate model for human pose estimation
Lightweight OpenPose: Runs in realtime >20fps confirmed, training code is provided
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How do I properly dissect a Github repo of a ML model?
Using https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch as an example (or another repo, that was just one I found), could someone please give me a step by step process of how they read a repo for a research paper?
What are some alternatives?
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
BlazePose-tensorflow - A third-party Tensorflow Implementation for paper "BlazePose: On-device Real-time Body Pose tracking".
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
kapao - KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
VIBE - Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"