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