CBAM and mixedstyle will be merged soon. Everything else has been uploaded.
bugfix : merge_json.py : 22-06-07
Follow the official repo to install bytetrack.
We used the MOTSynth official data extraction pipelines.
datasets
|——————mot (MOT17)
| └——————train
| └——————test
└——————motsynth
| └——————MOT17-02-DPM
| └——————MOT17-04-DPM
| └——————...
| └——————annotations
| └——————comb_annotations
| └——————frames
└——————data_path
To reproduce the performance, you need 8 GPUs with no less than 40G memory.
- Stage1. Training warm_up model with below script, or download warm-up model (58.1 HOTA), and save it in
python3 tools/train.py -f exps/example/mot/yolox_x_source_only.py -d 8 -b 48 --fp16 -o
- Make pseudo label, run below code
python3 tools/track.py -f exps/example/mot/yolox_x_mix_det.py -c weight/warm-up.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py
python3 make_PU.py
python3 ./tools/convert_mot17_to_coco_pu.py
python3 merge_json.py
- Stage2. Cross-domain Mixed Sampling with mosaic augmentation
python3 tools/train.py -f exps/example/mot/yolox_x_mixed.py -d 8 -b 48 --fp16 -o -c weight/warm-up.pth.tar
- Make pseudo label, run below code
python3 tools/track.py -f exps/example/mot/yolox_x_ft.py -c weight/mixed.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py
python3 make_PU.py
python3 ./tools/convert_mot17_to_coco_pu.py # We removed values with confidence less than 0.7 (L 108 in ./tools/convert_mot17_to_coco_pu.py) because predictions with low confidence can act as label noise.
- Stage3. Make multiple fine-tune model and model soup # when fine-tuned, the EMA is not used.
(Note that when performing fine-tune in Step 3, the augmentation combination should be different in L49-57 of ./yolox/data/datasets/mot.py)
python3 wa.py # you have to adjust it manually. (Until the CVPR22 conference, the completed code will be uploaded.)
python3 tools/track.py -f exps/example/mot/yolox_x_source_only.py -c weight/warm-up_67.5.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py # HOTA 58.1
python3 tools/track.py -f exps/example/mot/yolox_x_source_only.py -c weight/stage2_69.6.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py # HOTA 59.xx
python3 tools/track.py -f exps/example/mot/yolox_x_source_only.py -c weight/stage3_75.7.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py # HOTA 62.xx
python3 tools/track.py -f exps/example/mot/yolox_x_source_only.py -c weight/stage3_77.9.pth.tar -b 1 -d 1 --fp16 --fuse
python3 tools/interpolation.py # HOTA 63.xx
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