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Release FM4CS dataset on Hugging Face #7

@NielsRogge

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@NielsRogge

Hi @SarmadNR 🤗

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your excellent work, "DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models", on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.

The paper page lets people discuss about your paper and lets them find artifacts about it (your models or datasets for instance), you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

It's great to see that you've already made the DiffFuSR model checkpoints (WorldStrat SR, NAIP-no-harm SR, NAIP-harm SR) available on the Hugging Face Hub at https://huggingface.co/NorskRegnesentralSTI/DiffFuSR – that's fantastic! We can also link these models directly to your paper page, which will further improve their discoverability.

Regarding the "FM4CS" dataset mentioned in your GitHub repository for training the fusion model, which is noted as "not released yet": Would you be interested in hosting this new dataset on https://huggingface.co/datasets as well?

Hosting on Hugging Face will give it more visibility/enable better discoverability, and will also allow people to do:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/your-dataset")

If you're down, here's a guide: https://huggingface.co/docs/datasets/loading.
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.

Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.

After uploaded, we can also link the dataset to the paper page (read here) so people can discover your work.

Let me know if you're interested/need any guidance.

Kind regards,

Niels

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