Vision 3D
A clean, easy-to-use PyTorch library for lidar perception. Currently supports SECOND detector.
Project goals
- Emphasis on clean code (no 1,000 LOC functions).
- General 3D detection library (easy to extend to new models and datasets).
Status
- This project is not under active development.
- Implementation of PV-RCNN is partially completed.
- These forks (one, two) have shown some promise in training on other datasets (NuScenes, and proprietary lidar data).
Usage
See inference.py and train.py. To train, need to first start a visdom server using command visdom
to enable train loss monitoring. (Requires visdom python package to be installed).
Installation
See install.md.
Sample results on validation data (KITTI)
Citing
If you find this work helpful in your research, please consider starring this repo and citing:
@article{hultman2020vision3d,
author={Jacob Hultman},
title={vision3d},
journal={https://github.com/jhultman/vision3d},
year={2020}
}
Contributions
Contributions are welcome. Please post an issue if you find any bugs.
Acknowledgements and licensing
Please see license.md. Note that the code in vision3d/ops
is largely from detectron2 and hence is subject to the Apache license.