This repository aims to provide the code base for temporal several prediction tasks, such as trajectory :curly_loop:, motion :dancer:, and video :movie_camera:.
pip install -r requirements.txt
git submodule init
git submodule update
Please follow the trajdata instruction and specify the dataset path by cfg.DATA.PATH in keepflow/utils/default_params.py.
cfg.DATA.PATH/traj/raw/all_data
├── biwi_eth.txt
├── biwi_hotel.txt
├── crowds_zara01.txt
├── crowds_zara02.txt
├── crowds_zara03.txt
├── students001.txt
├── students003.txt
└── uni_examples.txt
Please follow the jrdb-traj instruction and execute dataload.sh
and preprocess.sh
in extern/traj/jrdb-traj/.
python train.py --config_file CONFIG_FILE_PATH --device DEVICE
Example
python train.py --config_file configs/traj/FlowChain/CIF_separate_cond_v_trajectron/eth.yml --device cuda:0
You can execute training consecutively by script
python scripts/run_configs.py --config_dir configs/traj/FlowChain/CIF_separate_cond_v_trajectron/ --device cuda:0 (--test_only)
python test.py --config_file CONFIG_FILE_PATH --device DEVICE (--visualize)
Example
python test.py --config_file configs/traj/FlowChain/CIF_separate_cond_v_trajectron/eth.yml --device cuda:0