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TransTrack: Multiple-Object Tracking with Transformer

Models are also available in Baidu Drive by code m4iv.

• Evaluating crowdhuman-training model and mot-training model use different command lines, see Steps.
• We observe about 1 MOTA noise.
• If the resulting MOTA of your self-trained model is not desired, playing around with the --track_thresh sometimes gives a better performance.
• The training time is on 8 NVIDIA V100 GPUs with batchsize 16.
• We use the models pre-trained on imagenet.

The codebases are built on top of Deformable DETR and CenterTrack.

• Linux, CUDA>=9.2, GCC>=5.4
• Python>=3.7
• PyTorch ≥ 1.5 and torchvision that matches the PyTorch installation. You can install them together at pytorch.org to make sure of this
• OpenCV is optional and needed by demo and visualization

1. Install and build libs

git clone https://github.com/PeizeSun/TransTrack.git
cd TransTrack
cd models/ops
python setup.py build install
cd ../..
pip install -r requirements.txt

2. Prepare dataset

mkdir -p crowdhuman/annotations
cp -r /path_to_crowdhuman_dataset/annotations/CrowdHuman_val.json crowdhuman/annotations/CrowdHuman_val.json
cp -r /path_to_crowdhuman_dataset/annotations/CrowdHuman_train.json crowdhuman/annotations/CrowdHuman_train.json
cp -r /path_to_crowdhuman_dataset/CrowdHuman_train crowdhuman/CrowdHuman_train
cp -r /path_to_crowdhuman_dataset/CrowdHuman_val crowdhuman/CrowdHuman_val
mkdir mot
cp -r /path_to_mot_dataset/train mot/train
cp -r /path_to_mot_dataset/test mot/test
python track_tools/convert_mot_to_coco.py

CrowdHuman dataset is available in CrowdHuman. We provide annotations of json format.

MOT dataset is available in MOT.

3. Pre-train on crowdhuman

sh track_exps/crowdhuman_train.sh
python track_tools/crowdhuman_model_to_mot.py

The pre-trained model is available crowdhuman_final.pth.

4. Train TransTrack

sh track_exps/crowdhuman_mot_trainhalf.sh

5. Evaluate TransTrack

sh track_exps/mot_val.sh
sh track_exps/mot_eval.sh

6. Visualize TransTrack

python track_tools/txt2video.py

• Evaluate pre-trained CrowdHuman model on MOT

sh track_exps/det_val.sh
sh track_exps/mot_eval.sh

TransTrack is released under MIT License.

If you use TransTrack in your research or wish to refer to the baseline results published here, please use the following BibTeX entries:

@article{transtrack,
  title   =  {TransTrack: Multiple-Object Tracking with Transformer},
  author  =  {Peize Sun and Yi Jiang and Rufeng Zhang and Enze Xie and Jinkun Cao and Xinting Hu and Tao Kong and Zehuan Yuan and Changhu Wang and Ping Luo},
  journal =  {arXiv preprint arXiv: 2012.15460},
  year    =  {2020}
}