-
STEP 1: Create enviroment
## python3.8 should be strictly followed. conda create -n b2d_zoo python=3.8 conda activate b2d_zoo
-
STEP 2: Install cudatoolkit
conda install -c "nvidia/label/cuda-11.8.0" cuda-toolkit
-
STEP 3: Install torch
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
-
STEP 4: Set environment variables
export PATH=YOUR_GCC_PATH/bin:$PATH export CUDA_HOME=YOUR_CUDA_PATH/
-
STEP 5: Install ninja and packaging
pip install ninja packaging
-
STEP 6: Install our repo
pip install -v -e .
-
STEP 7: Prepare pretrained weights. create directory
ckpts
mkdir ckpts
Download
resnet50-19c8e357.pth
form Hugging Face or Baidu Cloud or from Pytorch official website.Download
r101_dcn_fcos3d_pretrain.pth
form Hugging Face or Baidu Cloud or from BEVFormer official repo. -
STEP 8: Install CARLA for closed-loop evaluation.
## Ignore the line about downloading and extracting CARLA if you have already done so. mkdir carla cd carla wget https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/CARLA_0.9.15.tar.gz tar -xvf CARLA_0.9.15.tar.gz cd Import && wget https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/AdditionalMaps_0.9.15.tar.gz cd .. && bash ImportAssets.sh export CARLA_ROOT=YOUR_CARLA_PATH ## Important!!! Otherwise, the python environment can not find carla package echo "$CARLA_ROOT/PythonAPI/carla/dist/carla-0.9.15-py3.7-linux-x86_64.egg" >> YOUR_CONDA_PATH/envs/YOUR_CONDA_ENV_NAME/lib/python3.7/site-packages/carla.pth # python 3.8 also works well, please set YOUR_CONDA_PATH and YOUR_CONDA_ENV_NAME