This repository provides the code for our VISAPP 2022 paper CLOSED: A Dashboard for 3D Point Cloud Segmentation Analysis using Deep Learning
Please consider citing this work if you find it influential or useful in your research.
@inproceedings{Zoumpekas2022VISAPP,
author = {Zoumpekas, Thanasis and Molina, Guillem and Puig, Anna and Salamó, Maria},
title = {CLOSED: A Dashboard for 3D Point Cloud Segmentation Analysis using Deep Learning},
booktitle = {Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year = {2022},
pages = {403-410},
publisher = {SciTePress},
organization = {INSTICC},
doi = {10.5220/0010826000003124},
isbn = {978-989-758-555-5},
issn = {2184-4321},
}
YouTube video: https://www.youtube.com/watch?v=bCDWw4VYSZA
Please install Python Poetry. Then simply run (inside the project directory):
poetry install
If you want to use the dashboard as it is please use the below folder taxonomy for your 3D point clouds files. Then simply run poetry run python dashboard.py inside the project directory.
If you use the Torch-Points 3D framework for running deep learning models for 3D point cloud analysis, then you can change the path of DIR and benchmark_dir inside the dashboard.py to match the benchmark directory of your runs and run poetry run python dashboard.py inside the project directory.
MIT LICENSE.