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tjiiv-cprg/EQNet

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SETUP

PREPARE DATASET

  • You need to first download Argoverse 2 motion forecasting dataset.

  • You need to modify the data root inEQNet/env_config.yml:machines/default/argoverse_v2_dataroot to the correct location.

  • The dataset folder structure example:

    /mnt/data/argoverse2/├── test│   ├── processed│   └── raw├── train│   ├── processed│   └── raw└── val    ├── processed    │   ├── 6a24bd-1ad8-44c7-9a0e-5e93bb41d5ae.pkl    |   ...    └── raw        ├── 6a24bd-1ad8-44c7-9a0e-5e93bb41d5ae        ...

    Theprocessed folder contains the cache data, which is generated from the raw data. It will be automatically generated on the initial run. Theraw folder contains the original data.

PREPARE ENVIRONMENT

git clone<this-repo># we use conda to manage system packages# to compile cuda extensions: gcc=9.5.0 gxx=9.5.0# evalai dependencies: lxml# av2-api dependencies: rustconda create --name py310rust python=3.10 gcc=9.5.0 gxx=9.5.0 lxml rust virtualenv -c conda-forge conda activate py310rustpip install virtualenv# we use virtualenv to manage python packagescd<repo_root>python3 -m venv .venv# to be able to navigate the library code in the explorer tree, create the .venv folder locallysource .venv/bin/activatepip install -U setuptools pip<install-pytorch-via-pip-with-proper-version-of-cuda># accord with /usr/local/cuda version<install-pytorch-geometric-via-pip-with-proper-version-of-cuda># https://pytorch-geometric.readthedocs.io/en/1.6.3/notes/installation.htmlpip install https://github.com/argoverse/av2-api.git# mkdir .venv/src ; cd .venv/src; git clone git@github.com:argoverse/av2-api.git; pip install -e av2-api; cd ../..pip install https://github.com/JonathonLuiten/TrackEval.git# mkdir .venv/src ; cd .venv/src; git clone git@github.com:JonathonLuiten/TrackEval.git; pip install -e TrackEval; cd ../..pip install beautifulsoup4==4.7.1 beautifultable==0.7.0"boto3>=1.9.88" docker==3.6.0 validators==0.12.6 termcolor==1.1.0"tqdm>=4.49.0"# manually manage dependencies for evalai to avoid conflictspip install evalai --no-depspip install lightning einops torchscale huggingface_hub tensorboard==2.12.1pip install GitPython json5 shapely descartes imageio omegaconf colour pyyaml docstring_parser typing_inspect ipdb matplotlib clickpip install"numpy<2.0"

TRAINING

conda activate py310rustsource .venv/bin/activatebash EQNet/train.sh -m

TESTING

TBA

BENCHMARK SPEED

TBA

VISUALIZATION

  • checkoutvisualize.ipynb.

CITATION

TBA

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