Cylinder3D Spconv-2.2 PyTorch Lightning

Installation

1. Create conda environment with following command:

cd Cylinder3D-Spconv-2.2-PyTorch-Lightning
conda env create --name envname --file=environment.yml

2. Install PyTorch

pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113

3. Install torch-scatter

pip install --no-index torch-scatter -f https://data.pyg.org/whl/torch-1.12.1+cu113.html

4. Install spconv

pip install spconv-cu114==2.2.6

5. Install other dependencies

pip install -r requirements.txt

Training

1. modify the config/semantickitti_pl.yaml, including data path, log path (tensorboard log and model checkpoint), batch size, ddp training GPU device number
2. train the network by running CUDA_VISIBLE_DEVICES=0,1 python train_cylinder_asym_pl.py

Evaluation

1. evaluate the trained network by running CUDA_VISIBLE_DEVICES=0,1 python train_cylinder_asym_pl_eval.py (can eval on single or multiple GPUs)

Other Training Details

• 40 epochs
• 0.000707 base LR with sqrt_k scaling rule (equals to original 0.001 at batchsize = 2, equals 0.00489 at batchsize = 24)
• AdamW with Weight Decay 0.001
• CosineDecay Schedule

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Simple Benchmark

GPU Type	Single GPU	4 GPUs
A100	60 mins/epoch	25 mins/epoch

Reference

If you find our work useful in your research, please consider citing the original paper paper and the repo:

@article{zhu2020cylindrical,
  title={Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation},
  author={Zhu, Xinge and Zhou, Hui and Wang, Tai and Hong, Fangzhou and Ma, Yuexin and Li, Wei and Li, Hongsheng and Lin, Dahua},
  journal={arXiv preprint arXiv:2011.10033},
  year={2020}
}
@software{githubGitHubJaywu109Cylinder3DSpconv22PyTorchLightning,
  author = {Wu, Dai-Jie},
  title = {{G}it{H}ub - jaywu109/{C}ylinder3{D}-{S}pconv-2.2-{P}y{T}orch-{L}ightning --- github.com},
  url = {https://github.com/jaywu109/Cylinder3D-Spconv-2.2-PyTorch-Lightning},
  year = {2023}
}

Acknowledgments

We thanks for the opensource codebases, Cylinder3D and Cylinder3D-updated-CUDA