Version 1.5.0

The release focuses on making eo-learn much simpler to install, reducing the number of dependencies, and improving validation of soundness of EOPatch data.

• eo-learn is now distributed as a single package. Installation of eo-learn-mask and similar is no longer necessary and users are warned when such installations are detected.
• Changes to timestamps and bbox attributes of EOPatch objects:
  • FeatureType.TIMESTAMPS and FeatureType.BBOX have been deprecated, data should be accessed via attributes. Feature parsers no longer return these values (for instance when calling EOPatch.get_features).
  • EOPatches without temporal information now have a timestamp value of None, whereas a timestamp value [] signifies that the EOPatch has a temporal dimension of 0.
  • Introduced a get_timestamps method that will fail if timestamps are None. This can be used in cases where timestamps are assumed to be present (to avoid issues with type-checking and ill formed inputs).
  • Loading, saving, and copying of EOPatches will take timestamps into account either when processing the full eopatch (i.e. features=...) or if the selection contains a temporal feature. The behavior can be controlled via the load_timestamps/save_timestamps/copy_timestamps parameter.
• Saving and loading of FeatureType.META_INFO now processes each feature as a separate file, allowing better filtering and preventing accidental overwriting.
• The default backend for SpatialResizeTask has been switched to cv2 to reduce the number of dependencies.
• eolearn.geometry.morphology tasks now use cv2 instead of scikit-image to reduce the number of dependencies. The task interfaces have been slightly adjusted.
• Improved reports:
  • Exception grouping is now done by exception origin instead of exception message, resulting in shorter reports.
  • Added execution time statistics per node
• CloudMaskTask has been restricted to mono-temporal predictions using the s2cloudless package. For the multi-temporal one check here.
• Certain tasks (for instance SaveTask and LoadTask) no longer pass arguments to the super-class via **kwargs in order to improve documentation and type-checking.
• SaveTask and LoadTask now raise OSError exceptions instead of IOError.
• Project-specific and outdated EOTasks were moved to extras or to the example repository eo-learn-examples/extra-tasks.
• The submodule eolearn.features.bands_extraction has been renamed to eolearn.features.ndi.
• The submodule eolearn.ml_tools.extra.plotting has been moved to eolearn.visualization.utils.
• Compression of EOPatch files has been hardcoded. The parameter compression_level has been deprecated and has no effect.
• Introduced experimental zarr support for loading/saving temporal slices of temporal features. The API might be changed in future releases.
• Limited rasterio to 1.3.7 due to an issue with importing rasters from AWS S3
• Updated examples, simplified tests, various improvements.