Open3D PointNet implementation with PyTorch
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README.md

Open3D-PointNet

PointNet implementation and visualization with Open3D, an open-source library that supports rapid development of software that deals with 3D data. As part of the Open3D ecosystem, this repository demonstrates how Open3D can be used for ML/DL research projects.

This repository is forked from fxia22's PyTorch implementation.

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Changelog

  1. Added CPU support for non-cuda-enabled devices.
  2. Used Open3D point cloud loader for loading PointNet datasets (datasets.py).
  3. Added example for PointNet inference with Open3D Jupyter visualization (open3d_pointnet_inference.ipynb).
  4. Added example for native OpenGL visualization with Open3D (open3d_visualize.py).

Setup

# Install Open3D, must be v0.4.0 or above for Jupyter support
pip install open3d-python

# Install PyTorch
# Follow: https://pytorch.org/

# Install other dependencies
pip install -r requirements.txt

Now, launch

jupyter notebook

and run open3d_pointnet_inference.ipynb. All datasets and pre-trained models shall be downloaded automatically. If you run into issues downloading files, please run download.py separately.