Lightweight code to run inference with CloudSEN12 models
Project description
CloudSEN12
This package contains minimum code to run the CloudSEN12 models proposed in Aybar et al. 2023. Its main dependencies are pytorch and the georeader package which only depends on rasterio and geopandas libraries.
The notebook run_in_gee_image.ipynb has an example of running the model on a Sentinel-2 image downloaded from the Google Earth Engine:
Citation
If you find this code useful please cite:
@article{aybar_cloudsen12_2022,
title = {{CloudSEN12}, a global dataset for semantic understanding of cloud and cloud shadow in {Sentinel}-2},
volume = {9},
issn = {2052-4463},
url = {https://www.nature.com/articles/s41597-022-01878-2},
doi = {10.1038/s41597-022-01878-2},
number = {1},
urldate = {2023-01-02},
journal = {Scientific Data},
author = {Aybar, Cesar and Ysuhuaylas, Luis and Loja, Jhomira and Gonzales, Karen and Herrera, Fernando and Bautista, Lesly and Yali, Roy and Flores, Angie and Diaz, Lissette and Cuenca, Nicole and Espinoza, Wendy and Prudencio, Fernando and Llactayo, Valeria and Montero, David and Sudmanns, Martin and Tiede, Dirk and Mateo-García, Gonzalo and Gómez-Chova, Luis},
month = dec,
year = {2022},
pages = {782},
}
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