Awesome
PointVisualizaiton
A point cloud visualization repo
- Multiple Point Cloud Renderer using Mitsuba 3
- Real Time Point Cloud View Tool
Dependencies
python >= 3.7
pip install -r requirements.txt
Quick Usage
# Render a single file to colorful image
python main.py --path example/chair.npy --render
# Render a single file to knn cluster colorful image
python main.py --path <file path> --render --knn
# Render a single file to white image
python main.py --path <file path> --render --white
# Render a single file to specified RGB
python main.py --path <file path> --render --RGB R G B
# Render a single file to split part using knn
python main.py --path <file path> --part
# Render a single file with rotation 90 degree in y axis
python main.py --path <file path> --render --rot 0 90 0
# Render a single file with voxelization style
python main.py --path <file path> --render --radius 0.03 --num 384 --type voxel
# view real time point cloud
python main.py --path <file path> --tool
# view real time colorful point cloud with bbox
python main.py --path example/furniture.npy --tool --bbox example/bbox.npy --BGR
Args Introduction
- Required Parameters
--path
: Specify the path for the input file.
Currently, supports .npy
, .ply
, .npz
, .txt
, and .pth
formats for input, with a size of N × 3 (without color) or N × 6 (with color).
If the size is B × N × 3, the first element in the batch will be selected.
--render
: Using mitsuba to create beautiful image with shadow.
--tool
: Using real time point cloud visualization tools, you can drag the point clouds. Typing "Q" to exit.
- Optional Parameters
--knn
: Using KNN cluster to generate render color map. Note that KNN render will ignore the origin color infomation (if have).
--num
: Specify the downsample point num, default is inf.
--center_num
: The knn center num, default is 24.
--part
: Perform KNN clustering on the objects and render each segment separately, with the 'center_num' parameter equally effective.
--white
: Render white object. Note that white render will ignore the origin color infomation (if have).
--RGB
: Render object with specific RGB value. Note that RGB render will ignore the origin color infomation (if have).
--mask
: Render masked point cloud.
Source
Many thanks to following codes that help us a lot in building this codebase:
Citation
If you find this project helpful for your research, please consider citing the following BibTeX entry.
@inproceedings{qi2023recon,
title={Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining},
author={Qi, Zekun and Dong, Runpei and Fan, Guofan and Ge, Zheng and Zhang, Xiangyu and Ma, Kaisheng and Yi, Li},
booktitle={International Conference on Machine Learning (ICML) },
year={2023}
}
@inproceedings{dong2023act,
title={Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?},
author={Runpei Dong and Zekun Qi and Linfeng Zhang and Junbo Zhang and Jianjian Sun and Zheng Ge and Li Yi and Kaisheng Ma},
booktitle={The Eleventh International Conference on Learning Representations (ICLR) },
year={2023},
url={https://openreview.net/forum?id=8Oun8ZUVe8N}
}