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)