Pose Tracking Module for AlphaPose
AlphaPose provide three different tracking methods for now, you can try different method to see which one is better for you.
1. Human-ReID based tracking (Recommended)
Currently the best performance tracking model. Paper coming soon.
Getting started
Download human reid model and place it into AlphaPose/trackers/weights/.
Then simply run alphapose with additional flag --pose_track
You can try different person reid model by modifing cfg.arch and cfg.loadmodel in ./trackers/tracker_cfg.py.
If you want to train your own reid model, please refer to this project
Demo
./scripts/inference.sh ${CONFIG} ${CHECKPOINT} ${VIDEO_NAME} ${OUTPUT_DIR}, --pose_track
Todo
- [] Evaluation Tools for PoseTrack
- [] More Models
- [] Training code for PoseTrack Dataset
2. Detector based human tracking
Use a human detecter with tracking module (JDE). Please refer to detector/tracker/
Getting started
Download detector JDE-1088x608 and place it under AlphaPose/detector/tracker/data/
Enable tracking by setting the detector as tracker: --detector tracker
Demo
./scripts/inference.sh ${CONFIG} ${CHECKPOINT} ${VIDEO_NAME} ${OUTPUT_DIR}, --detector tracker
3. PoseFlow human tracking
This tracker is based on our BMVC 2018 paper PoseFlow, for more info please refer to PoseFlow/README.md
Getting started
Simply run alphapose with additional flag --pose_flow