added images of rotor37_1200

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Laureηt 2023-07-07 16:33:58 +02:00
parent 5405648c96
commit 1d0b0dae66
5 changed files with 24 additions and 1 deletions

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@ -445,6 +445,13 @@ Le principal ensemble de données sur lequel j'ai travaillé pendant mon stage s
\label{fig:process-rotor37-1200} \label{fig:process-rotor37-1200}
\end{figure} \end{figure}
\begin{figure}[h!]
\centering
\includegraphics[width=4.5cm]{rotor37_1.png}\includegraphics[width=4.5cm]{rotor37_2.png}\includegraphics[width=4.5cm]{rotor37_3.png}
\caption{Échantillon de l'ensemble de données Rotor37\_1200 sous plusieurs angles}
\label{fig:example-rotor37-1200}
\end{figure}
Chaque aube du jeu de données est une déformation de l'aube nominale. Ainsi tous les maillages possèdent le même nombre de points et la même connectivité. Pour donner un ordre de grandeur, chaque maillage est constitué de 29773 points, 59328 triangles et 89100 arêtes. Chaque aube du jeu de données est une déformation de l'aube nominale. Ainsi tous les maillages possèdent le même nombre de points et la même connectivité. Pour donner un ordre de grandeur, chaque maillage est constitué de 29773 points, 59328 triangles et 89100 arêtes.
Chaque échantillon est constitué de deux fichiers distincts. Le premier est un fichier au format .vtk qui contient le maillage de l'aube, comprenant les positions 3D, les normales et la connectivité de chaque point du maillage. Ce fichier .vtk inclut également les champs physiques associés à chaque point, tels que la température, la pression, etc. Le second fichier est un fichier .csv qui contient des métadonnées globales spécifiques à l'échantillon, telles que les entrées et les sorties de la simulation \gls{cfd}. Chaque échantillon est constitué de deux fichiers distincts. Le premier est un fichier au format .vtk qui contient le maillage de l'aube, comprenant les positions 3D, les normales et la connectivité de chaque point du maillage. Ce fichier .vtk inclut également les champs physiques associés à chaque point, tels que la température, la pression, etc. Le second fichier est un fichier .csv qui contient des métadonnées globales spécifiques à l'échantillon, telles que les entrées et les sorties de la simulation \gls{cfd}.

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@ -37,7 +37,6 @@
year = {2021}, year = {2021},
address = {Online and Punta Cana, Dominican Republic}, address = {Online and Punta Cana, Dominican Republic},
publisher = {Association for Computational Linguistics}, publisher = {Association for Computational Linguistics},
url = {https://aclanthology.org/2021.emnlp-demo.21},
pages = {175--184}, pages = {175--184},
abstract = {The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, versioning, and documentation, while providing a lightweight front-end that behaves similarly for small datasets as for internet-scale corpora. The design of the library incorporates a distributed, community-driven approach to adding datasets and documenting usage. After a year of development, the library now includes more than 650 unique datasets, has more than 250 contributors, and has helped support a variety of novel cross-dataset research projects and shared tasks. The library is available at https://github.com/huggingface/datasets.}, abstract = {The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, versioning, and documentation, while providing a lightweight front-end that behaves similarly for small datasets as for internet-scale corpora. The design of the library incorporates a distributed, community-driven approach to adding datasets and documenting usage. After a year of development, the library now includes more than 650 unique datasets, has more than 250 contributors, and has helped support a variety of novel cross-dataset research projects and shared tasks. The library is available at https://github.com/huggingface/datasets.},
eprint = {2109.02846}, eprint = {2109.02846},
@ -45,3 +44,11 @@
primaryclass = {cs.CL}, primaryclass = {cs.CL},
url = {https://github.com/huggingface/datasets} url = {https://github.com/huggingface/datasets}
} }
@software{von_Platen_Diffusers_State-of-the-art_diffusion,
author = {von Platen, Patrick and {The HuggingFace team}},
license = {Apache-2.0},
title = {{Diffusers: State-of-the-art diffusion models}},
url = {https://github.com/huggingface/diffusers},
version = {0.12.1}
}