Skip to main content

Lightweight code to run inference with CloudSEN12 models

Project description

Article DOI:10.1038/s41597-022-01878-2 PyPI PyPI - License

Logo CloudSEN12

This package contains minimum code to run the CloudSEN12 models proposed in Aybar et al. 2022 and Aybar et al. 2024. The main dependencies of this package 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:

For more examples see cloudsen12.github.io.

Citation

If you find this code useful please cite:

@article{aybar_cloudsen12_2024,
	title = {{CloudSEN12}+: {The} largest dataset of expert-labeled pixels for cloud and cloud shadow detection in {Sentinel}-2},
	issn = {2352-3409},
	url = {https://www.sciencedirect.com/science/article/pii/S2352340924008163},
	doi = {10.1016/j.dib.2024.110852},
	journal = {Data in Brief},
	author = {Aybar, Cesar and Bautista, Lesly and Montero, David and Contreras, Julio and Ayala, Daryl and Prudencio, Fernando and Loja, Jhomira and Ysuhuaylas, Luis and Herrera, Fernando and Gonzales, Karen and Valladares, Jeanett and Flores, Lucy A. and Mamani, Evelin and Quiñonez, Maria and Fajardo, Rai and Espinoza, Wendy and Limas, Antonio and Yali, Roy and Alcántara, Alejandro and Leyva, Martin and Loayza-Muro, Rau´l and Willems, Bram and Mateo-García, Gonzalo and Gómez-Chova, Luis},
	month = aug,
	year = {2024},
	pages = {110852},
}

@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},
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cloudsen12_models-0.4.1.tar.gz (8.7 kB view details)

Uploaded Source

Built Distribution

cloudsen12_models-0.4.1-py3-none-any.whl (9.2 kB view details)

Uploaded Python 3

File details

Details for the file cloudsen12_models-0.4.1.tar.gz.

File metadata

  • Download URL: cloudsen12_models-0.4.1.tar.gz
  • Upload date:
  • Size: 8.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for cloudsen12_models-0.4.1.tar.gz
Algorithm Hash digest
SHA256 4ccf8d4cb64deab6d676db315cbaa44e3b1231d8d9d86316c6d1b129d3599d00
MD5 e6da9afb88693e4230f6dd448ebf8ec1
BLAKE2b-256 d2e703ebd8f72071267ad6c1feff60d13601dd3362fc1c6ac57dd7df3e04aaaa

See more details on using hashes here.

File details

Details for the file cloudsen12_models-0.4.1-py3-none-any.whl.

File metadata

File hashes

Hashes for cloudsen12_models-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6c84341db0959b88eaff03fc8c0ebeb695320fc4838df5a64371332318b1528d
MD5 2087fe5c0bff0d3c024cb8139b4279a8
BLAKE2b-256 7e9f62116770525a8daae5b6b026208e9164a8f286bf1e1e1663ad41d4927cc4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page