erikwijmans / Pointnet2_pytorch
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Pointnet2/Pointnet++ PyTorch
-
Implemention of Pointnet2/Pointnet++ written in
PyTorch <http://pytorch.org>
_. -
Supports Multi-GPU via
nn.DataParallel <https://pytorch.org/docs/stable/nn.html#torch.nn.DataParallel>
_. -
Supports PyTorch version >= 1.0.0. Use
v1.0 <https://github.com/erikwijmans/Pointnet2_PyTorch/releases/tag/v1.0>
_ for support of older versions of PyTorch.
See the official code release for the paper (in tensorflow), charlesq34/pointnet2 <https://github.com/charlesq34/pointnet2>
_,
for official model definitions and hyper-parameters.
The custom ops used by Pointnet++ are currently ONLY supported on the GPU using CUDA.
Setup
-
Install
python
-- This repo is tested with{3.6, 3.7}
-
Install
pytorch
with CUDA -- This repo is tested with{1.4, 1.5}
. It may work with versions newer than1.5
, but this is not guaranteed. -
Install dependencies
::
pip install -r requirements.txt
Example training
Install with: pip install -e .
There example training script can be found in pointnet2/train.py
. The training examples are built
using PyTorch Lightning <https://github.com/williamFalcon/pytorch-lightning>
_ and Hydra <https://hydra.cc/>
_.
A classifion pointnet can be trained as
::
python pointnet2/train.py task=cls
Or with model=msg for multi-scale grouping
python pointnet2/train.py task=cls model=msg
Similarly, semantic segmentation can be trained by changing the task to semseg
::
python pointnet2/train.py task=semseg
Multi-GPU training can be enabled by passing a list of GPU ids to use, for instance
::
python pointnet2/train.py task=cls gpus=[0,1,2,3]
Building only the CUDA kernels
::
pip install pointnet2_ops_lib/.
Or if you would like to install them directly (this can also be used in a requirements.txt)
pip install "git+git://github.com/erikwijmans/Pointnet2_PyTorch.git#egg=pointnet2_ops&subdirectory=pointnet2_ops_lib"
Contributing
This repository uses black <https://github.com/ambv/black>
_ for linting and style enforcement on python code.
For c++/cuda code,
clang-format <https://clang.llvm.org/docs/ClangFormat.html>
_ is used for style. The simplest way to
comply with style is via pre-commit <https://pre-commit.com/>
_
::
pip install pre-commit pre-commit install
Citation
::
@article{pytorchpointnet++, Author = {Erik Wijmans}, Title = {Pointnet++ Pytorch}, Journal = {https://github.com/erikwijmans/Pointnet2_PyTorch}, Year = {2018} }
@inproceedings{qi2017pointnet++, title={Pointnet++: Deep hierarchical feature learning on point sets in a metric space}, author={Qi, Charles Ruizhongtai and Yi, Li and Su, Hao and Guibas, Leonidas J}, booktitle={Advances in Neural Information Processing Systems}, pages={5099--5108}, year={2017} }