- Create and activate an environment with all required packages:
conda env create -f environment.yml
conda activate motsynth
- Install the additional modules:
Tracktor
, Torchreid
and Trackeval
:
pip install https://github.com/phil-bergmann/tracking_wo_bnw/archive/master.zip
pip install https://github.com/KaiyangZhou/deep-person-reid/archive/master.zip
pip install https://github.com/JonathonLuiten/TrackEval/archive/master.zip
- Optionally modify the path
OUTPUT_DIR
in configs/path_cfg.py
, download TrackEval's ground truth data from here and place it in at MOTCHA_ROOT
. E.g.:
MOTCHA_ROOT=$(python -c "from configs.path_cfg import MOTCHA_ROOT; print(MOTCHA_ROOT);")
wget -P $MOTCHA_ROOT https://omnomnom.vision.rwth-aachen.de/data/TrackEval/data.zip
- Optionally modify the path
OUTPUT_DIR
in configs/path_cfg.py
, and download our trained models:
OUTPUT_DIR=$(python -c "from configs.path_cfg import OUTPUT_DIR; print(OUTPUT_DIR);")
mkdir ${OUTPUT_DIR}/models
wget -P ${OUTPUT_DIR}/models https://vision.in.tum.de/webshare/u/brasoand/motsynth/resnet50_fc512_reid_epoch_19.pth
wget -P ${OUTPUT_DIR}/models https://vision.in.tum.de/webshare/u/brasoand/motsynth/maskrcnn_resnet50_fpn_epoch_10.pth