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STEP 1: Create Environment
## python3.8 should be strictly followed. conda create -n b2d_zoo python=3.8 conda activate b2d_zoo
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STEP 2: Install Jittor
sudo apt install libomp-dev pip install git+https://github.com/Jittor/jittor.git # make sure use the latest version, after commit da45615
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STEP 3: Set Environment Variables
## Suggested GCC Version 9.4. Otherwise, there would be lots of unknown errors. export PATH=YOUR_GCC_PATH/bin:$PATH ## Suggested CUDA Version 11.8 export CUDA_HOME=YOUR_CUDA_PATH/
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STEP 4: Install CUDA Support for Jittor
## If you have a GPU and want to enable CUDA acceleration, install CUDA to the Jittor cache python -m jittor_utils.install_cuda
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STEP 5: Install ninja and packaging
pip install ninja packaging
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STEP 6: Install our repo
pip install -r requirements.txt ## If there is any error, consider changing the cuda version of the following package pip install spconv-cu113 pip install cupy-cuda113 pip install -v -e . pip install pillow==9.2.0 pip install cupy
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STEP 7: Prepare pretrained weights. create directory
ckpts
mkdir ckpts
Download
resnet50-19c8e357.pth
form Hugging Face or Baidu Cloud or from Pytorch official website.Download
r101_dcn_fcos3d_pretrain.pth
form Hugging Face or Baidu Cloud or from BEVFormer official repo. -
STEP 8: Install CARLA for closed-loop evaluation.
## Ignore the line about downloading and extracting CARLA if you have already done so. mkdir carla cd carla wget https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/CARLA_0.9.15.tar.gz tar -xvf CARLA_0.9.15.tar.gz cd Import && wget https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/AdditionalMaps_0.9.15.tar.gz cd .. && bash ImportAssets.sh export CARLA_ROOT=YOUR_CARLA_PATH ## Important!!! Otherwise, the python environment can not find CARLA package echo "$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 # python3.8 works well even if the egg is compiled for python3.7, please set YOUR_CONDA_PATH and YOUR_CONDA_ENV_NAME correctly