Datasets:
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README.md
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## Credits
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## Data loading
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The Github repository associated to this dataset contains a PyTorch dataset class [here)(https://github.com/gastruc/OmniSat/blob/main/src/data/Pastis.py) that can be readily used to load data for training models on PASTIS-HD.
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The time series contained in PASTIS have variable lengths.
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The Sentinel 1 and 2 time series are stored in numpy array. The SPOT images are in TIFF format.
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The annotations are in numpy array too.
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## Ground Truth Annotations
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The agricultural parcels are grouped into 18 different crop classes as shown in the table below. The backgroud class corresponds to non-agricultural land, and the void label for parcels that are mostly outside their patch.
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Additional information about the dataset can be found in the documentation/pastis-documentation.pdf document.
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## Credits
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