U-Net semantic segmentation for satellite imagery

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This digital tool is part of the catalog of tools of the Inter-American Development Bank. You can learn more about the IDB initiative at code.iadb.org


A set of classes and CLI tools for training a semantic segmentation model based on the U-Net architecture, using Tensorflow and Keras.

This implementation is tuned specifically for satellite imagery and other geospatial raster data.


Bugs / Questions


Bug reports and pull requests are welcome on GitHub at the issues page. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

Made with contrib.rocks.


This project is licensed under Apache 2.0. Refer to LICENSE.txt.