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Project Elements: A computational entity-component-system in a scene-graph pythonic framework, for a neural, geometric computer graphics curriculum
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Elements introduces for the first time the power of the Entity-Component-System (ECS) with the versatility of Scenegraphs, in the context of Computer Graphics (CG), Deep Learning (DL) for Scientific Visualization (SciViz). It also aims to provide the basic tools to anyone that wants to be involved with basic Computer Graphics as well as advanced topics such as Geometric Deep Learning, Geometric Algebra and many many more.
Following a modern educational approach, all related packages are in the Python programming language.
To dive in the details of the project check its detailed developer documentation and the research paper behind this project: arXiv LINK, Eurographics LINK.
Begin by following the installation instructions, found HERE. For Computer Graphics Course students, the instructions are HERE.
[!NOTE] We strongly recommend using:
- Anaconda for your python environment,
- Visual Studio Code as your IDE, and
- Fork/Sourcetree for version control.
The main steps summarize as follows:
conda create -n elements python=3.8,
and activate it via
conda activate elementspip install -e .Elements/examples folder.If you want to contribute to Elements, kindly check its WIKI for a list of potential projects and a contribution guide. A list of contributors can be found here.
If you have any questions or would like to learn more about our project, please don't hesitate to contact us.
If you are using the Elements project, please cite:
@inproceedings {Elements2023,
booktitle = {Eurographics 2023 - Education Papers},
editor = {Magana, Alejandra and Zara, Jiri},
title = {{Project Elements: A Computational Entity-component-system in a Scene-graph Pythonic Framework, for a Neural, Geometric Computer Graphics Curriculum}},
author = {Papagiannakis, George and Kamarianakis, Manos and Protopsaltis, Antonis and Angelis, Dimitris and Zikas, Paul},
year = {2023},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
ISBN = {978-3-03868-210-3},
DOI = {10.2312/eged.20231015}
}