Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

add figure from the MLM demo paper #33

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
+2 −0
Open

add figure from the MLM demo paper #33

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -51,6 +51,8 @@ The main objectives of the extension are:
2) record all necessary bands, parameters, modeling artifact locations, and high-level processing steps to deploy
an inference service.

<img src="./STAC_MLM.png" width="1000px" alt="STAC_MLM">
Copy link
Collaborator

@fmigneault fmigneault Oct 22, 2024 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Do not enforce some width. It doesn't work nicely with other devices than your standard monitor. Simply use a markdown image reference and let it auto-scale.

Also, I think it makes more sense to place it just before the "See Best Practices..." below. Here, it cuts the summary description in two.

Consider adding the citation as well under it. Just another way to communicate the paper reference along #32.

Francis Charette-Migneault, Ryan Avery, Brian Pondi, Joses Omojola, Simone Vaccari, Parham Membari, Devis Peressutti, Jia Yu, and Jed Sundwall. 2024. Machine Learning Model Specification for Cataloging Spatio-Temporal Models (Demo Paper). In 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data (GeoSearch’24), October 29–November 1 2024, Atlanta, GA, USA. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3681769.3698586


Specifically, this extension records the following information to make ML models searchable and reusable:
1. Sensor band specifications
2. Model input transforms including resize and normalization
Expand Down
Binary file added STAC_MLM.png
View file
Open in desktop
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Move the image under docs/static.

Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.