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README.md
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> E. Portalés-Julià, G. Mateo-García, C. Purcell, and L. Gómez-Chova [Global flood extent segmentation in optical satellite images](https://www.nature.com/articles/s41598-023-47595-7). _Scientific Reports 13, 20316_ (2023). DOI: 10.1038/s41598-023-47595-7.
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The [*
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It requires approximately
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<img src="worldfloods_v2.png" alt="licence" width="65%"/>
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The *WorldFloods* database and all pre-trained models are released under a [Creative Commons non-commercial licence](https://creativecommons.org/licenses/by-nc/4.0/legalcode.txt)
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If you find this work useful, please cite:
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```
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> E. Portalés-Julià, G. Mateo-García, C. Purcell, and L. Gómez-Chova [Global flood extent segmentation in optical satellite images](https://www.nature.com/articles/s41598-023-47595-7). _Scientific Reports 13, 20316_ (2023). DOI: 10.1038/s41598-023-47595-7.
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The [*WorldFloodsv2* database](https://www.nature.com/articles/s41598-023-47595-7) contains 509 pairs of Sentinel-2 images and flood segmentation masks. Splitted in train, val and test sets.
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It requires approximately 76GB of hard-disk storage.
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<img src="worldfloods_v2.png" alt="licence" width="65%"/>
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## Download the dataset
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```
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huggingface-cli download --cache-dir /path/to/cachedir --local-dir /path/to/localdir/WorldFloodsv2 --repo-type dataset isp-uv-es/WorldFloodsv2
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```
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## Explore the dataset
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The [exploring *WorldFloodsv2*](https://spaceml-org.github.io/ml4floods/content/prep/exploring_worldfloods.html) tutorial in the [ml4floods](https://github.com/spaceml-org/ml4floods) package shows how to
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process the dataset and plot the images and masks.
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## Licence
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The *WorldFloods* database and all pre-trained models are released under a [Creative Commons non-commercial licence](https://creativecommons.org/licenses/by-nc/4.0/legalcode.txt)
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## Cite
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If you find this work useful, please cite:
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```
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