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Source code for torchgeo.datamodules.nasa_marine_debris

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

"""NASA Marine Debris datamodule."""

from typing import Any

import kornia.augmentation as K
import torch
from torch.utils.data import random_split

from ..datasets import NASAMarineDebris
from ..transforms import AugmentationSequential
from .geo import NonGeoDataModule
from .utils import AugPipe, collate_fn_detection


[docs]class NASAMarineDebrisDataModule(NonGeoDataModule): """LightningDataModule implementation for the NASA Marine Debris dataset. .. versionadded:: 0.2 """ std = torch.tensor(255)
[docs] def __init__( self, batch_size: int = 64, num_workers: int = 0, val_split_pct: float = 0.2, test_split_pct: float = 0.2, **kwargs: Any, ) -> None: """Initialize a new NASAMarineDebrisDataModule instance. Args: batch_size: Size of each mini-batch. num_workers: Number of workers for parallel data loading. val_split_pct: Percentage of the dataset to use as a validation set. test_split_pct: Percentage of the dataset to use as a test set. **kwargs: Additional keyword arguments passed to :class:`~torchgeo.datasets.NASAMarineDebris`. """ super().__init__(NASAMarineDebris, batch_size, num_workers, **kwargs) self.val_split_pct = val_split_pct self.test_split_pct = test_split_pct self.aug = AugPipe( AugmentationSequential( K.Normalize(mean=self.mean, std=self.std), data_keys=['image', 'boxes'] ), batch_size, ) self.collate_fn = collate_fn_detection
[docs] def setup(self, stage: str) -> None: """Set up datasets. Args: stage: Either 'fit', 'validate', 'test', or 'predict'. """ self.dataset = NASAMarineDebris(**self.kwargs) generator = torch.Generator().manual_seed(0) self.train_dataset, self.val_dataset, self.test_dataset = random_split( self.dataset, [ 1 - self.val_split_pct - self.test_split_pct, self.val_split_pct, self.test_split_pct, ], generator, )

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