Awesome
Superpoint Network for Point Cloud Oversegmentation
by Le Hui, Jia Yuan, Mingmei Cheng, Jin Xie, Xiaoya Zhang, and Jian Yang
This is a rough README.md, and we'll work through it. !!!
Project Code
Requirements
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basic environment
Python 3.6.6 Pytorch 1.4.0 CUDA 10.1
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compile the "libply_c" library (Please refer to SPG)
CONDAENV=YOUR_CONDA_ENVIRONMENT_LOCATION cd libs/ply_c cmake . -DPYTHON_LIBRARY=$CONDAENV/lib/libpython3.6m.so -DPYTHON_INCLUDE_DIR=$CONDAENV/include/python3.6m -DBOOST_INCLUDEDIR=$CONDAENV/include -DEIGEN3_INCLUDE_DIR=$CONDAENV/include/eigen3 make cd ../../
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build the ops
cd libs/pointops && python setup.py install && cd ../../ Note that this may take a long time.
Training and Evaluation
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To train and evaluate SPNet, run the following command:
# Train & Eval # Note that you should change the paths in the yaml file. sh tool/sh_train.sh s3dis 20220121 config/spnet.yaml sh tool/sh_test.sh s3dis 20220121 config/spnet.yaml 850
Citation
If you find the code or trained models useful, please consider citing:
@inproceedings{hui2021spnet,
title={Superpoint Network for Point Cloud Oversegmentation},
author={Hui, Le and Yuan, Jia and Cheng, Mingmei and Xie, Jin and Yang, Jian},
booktitle={ICCV},
year={2021}
}
Acknowledgement
Our code refers to SPG and PointWeb. Many thanks to SPG for a great work.