trackers

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 ( Mega drive or Baidu Pan, code:6a8b)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