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Source code for torchgeo.datamodules.xview

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

"""xView2 datamodule."""

from typing import Any

import torch
from torch.utils.data import random_split

from ..datasets import XView2
from .geo import NonGeoDataModule


[docs]class XView2DataModule(NonGeoDataModule): """LightningDataModule implementation for the xView2 dataset. Uses the train/val/test splits from the dataset. .. versionadded:: 0.2 """
[docs] def __init__( self, batch_size: int = 64, num_workers: int = 0, val_split_pct: float = 0.2, **kwargs: Any, ) -> None: """Initialize a new XView2DataModule instance. Args: batch_size: Size of each mini-batch. num_workers: Number of workers for parallel data loading. val_split_pct: What percentage of the dataset to use as a validation set **kwargs: Additional keyword arguments passed to :class:`~torchgeo.datasets.XView2`. """ super().__init__(XView2, batch_size, num_workers, **kwargs) self.val_split_pct = val_split_pct
[docs] def setup(self, stage: str) -> None: """Set up datasets. Args: stage: Either 'fit', 'validate', 'test', or 'predict'. """ if stage in ['fit', 'validate']: self.dataset = XView2(split='train', **self.kwargs) generator = torch.Generator().manual_seed(0) self.train_dataset, self.val_dataset = random_split( self.dataset, [1 - self.val_split_pct, self.val_split_pct], generator ) if stage in ['test']: self.test_dataset = XView2(split='test', **self.kwargs)

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