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Source code for torchgeo.datamodules.landcoverai

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

"""LandCover.ai datamodule."""

from typing import Any

import kornia.augmentation as K

from ..datasets import LandCoverAI
from ..transforms import AugmentationSequential
from .geo import NonGeoDataModule


[docs]class LandCoverAIDataModule(NonGeoDataModule): """LightningDataModule implementation for the LandCover.ai dataset. Uses the train/val/test splits from the dataset. """
[docs] def __init__( self, batch_size: int = 64, num_workers: int = 0, **kwargs: Any ) -> None: """Initialize a new LandCoverAIDataModule 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.LandCoverAI`. """ super().__init__(LandCoverAI, batch_size, num_workers, **kwargs) self.train_aug = AugmentationSequential( K.Normalize(mean=self.mean, std=self.std), K.RandomRotation(p=0.5, degrees=90), K.RandomHorizontalFlip(p=0.5), K.RandomVerticalFlip(p=0.5), K.RandomSharpness(p=0.5), K.ColorJitter(p=0.5, brightness=0.1, contrast=0.1, saturation=0.1, hue=0.1), data_keys=['image', 'mask'], ) self.aug = AugmentationSequential( K.Normalize(mean=self.mean, std=self.std), data_keys=['image', 'mask'] )

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