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Source code for torchgeo.datamodules.bigearthnet

# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

"""BigEarthNet datamodule."""

from typing import Any

import torch

from ..datasets import BigEarthNet
from .geo import NonGeoDataModule


[docs]class BigEarthNetDataModule(NonGeoDataModule): """LightningDataModule implementation for the BigEarthNet dataset. Uses the train/val/test splits from the dataset. """ # (VV, VH, B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12) # min/max band statistics computed on 100k random samples mins_raw = torch.tensor( [-70.0, -72.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0] ) maxs_raw = torch.tensor( [ 31.0, 35.0, 18556.0, 20528.0, 18976.0, 17874.0, 16611.0, 16512.0, 16394.0, 16672.0, 16141.0, 16097.0, 15336.0, 15203.0, ] ) # min/max band statistics computed by percentile clipping the # above to samples to [2, 98] mins = torch.tensor( [-48.0, -42.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] ) maxs = torch.tensor( [ 6.0, 16.0, 9859.0, 12872.0, 13163.0, 14445.0, 12477.0, 12563.0, 12289.0, 15596.0, 12183.0, 9458.0, 5897.0, 5544.0, ] )
[docs] def __init__( self, batch_size: int = 64, num_workers: int = 0, **kwargs: Any ) -> None: """Initialize a new BigEarthNetDataModule instance. Args: batch_size: Size of each mini-batch. num_workers: Number of workers for parallel data loading. **kwargs: Additional keyword arguments passed to :class:`~torchgeo.datasets.BigEarthNet`. """ bands = kwargs.get("bands", "all") if bands == "all": mins = self.mins maxs = self.maxs elif bands == "s1": mins = self.mins[:2] maxs = self.maxs[:2] else: mins = self.mins[2:] maxs = self.maxs[2:] self.mean = mins self.std = maxs - mins super().__init__(BigEarthNet, batch_size, num_workers, **kwargs)

© Copyright 2021, Microsoft Corporation. Revision acad7d47.

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