| # ml4floods pre-trained models | |
| This repository contains the trained models of the publication: | |
| > 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. | |
| We include the trained models: | |
| * Unet multioutput - `models/WF2_unetv2_all` | |
| * Unet multioutput S2-to-L8 - `models/WF2_unetv2_bgriswirs` | |
| * Unet multioutput RGBNIR - `models/WF2_unetv2_rgbi` | |
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| In order to run any of these models in Landsat or Sentinel-2 scene see the tutorial [*Inference with clouds aware floods segmentation model*](https://spaceml-org.github.io/ml4floods/content/ml4ops/HOWTO_Run_Inference_multioutput_binary.html) in the ml4floods docs. | |
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| license: cc-by-nc-4.0 | |
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