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Installation

Package

We currently support Python 3.10+ and PyTorch 2.0.0+.

We recommand to install in a new virtual environment, e.g. conda or virtualenv.

Install with PyPI

You can install the library as easy as

python3 -m pip install vis4d

Build from source

If you want to build the package from source and specify CUDA version, you can clone the repository and install it:

git clone https://github.com/SysCV/vis4d.git
cd vis4d

python3 -m pip install -r requirements/install.txt -f https://download.pytorch.org/whl/cu118/torch_stable.html
python3 -m pip install -e .

More information about torch and pytorch-lightning installation

Install CUDA Operations

Some functionalities in the library require CUDA operations. You can install them by running:

python3 -m pip install -r requirements/torch-lib.txt

Directory Layout

You can use the library in different folder structures and codebase. But by default Vis4D will use the following directories by default:

Data

The default location for datasets used in the experiments is:

--root
    --data
        --dataset1
        --dataset2

Workspace

The default output folder used in the experiments to store logs, checkpoints, etc. is:

--root
    --vis4d-workspace
        --experiment_name1
            --version1
            --version2
        --experiment_name2
            --version1
            --version2