All the codes are tested in the environment:
- Linux (tested on Ubuntu 16.04/18.04/20.04)
- Python 3.8 (waymo-open-dataset 2-5-0 required)
- PyTorch 1.10 or higher
- CUDA 11.0 or higher
- GCC 5.4+
- spconv v2.x
a. Create a conda virtual environment.
conda create --name detzero python=3.8
conda activate detzero
b. Install PyTorch and torchvision following the official instructions.
pip install torch==1.10.0+cu111 torchvision==0.11.0+cu111 torchaudio==0.10.0 -f https://download.pytorch.org/whl/torch_stable.html
Note: Make sure that your compilation CUDA version and runtime CUDA version match.
c. Install cmake.
conda install cmake
d. Install sparse conv.
pip install spconv-cu111
e. Install pytorch scatter (for DynamicVFE). We suggest to follow the instructions of torch_scatter to install the package based on your own environment version.
f. Install Waymo evaluation module.
pip install waymo-open-dataset-tf-2-5-0
g. Install other required dependent libraries.
cd DetZero && pip install -r requirements.txt
h. Compile other libraries.
cd DetZero/utils && python setup.py develop
i. Compile the libraries of specific algorithm modules.
cd DetZero/detection && python setup.py develop
cd DetZero/tracking && python setup.py develop
cd DetZero/refining && python setup.py develop