Drop Python 3.9 support (#1966)

.github/workflows/style.yaml

@@ -158,7 +158,7 @@ jobs:
     - name: List pip dependencies
       run: pip list
     - name: Run pyupgrade checks
-      run: pyupgrade --py39-plus $(find . -path ./docs/src -prune -o -name "*.py" -print)
+      run: pyupgrade --py310-plus $(find . -path ./docs/src -prune -o -name "*.py" -print)
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.head.label || github.head_ref || github.ref }}
   cancel-in-progress: true

.github/workflows/tests.yaml

@@ -17,7 +17,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12']
     steps:
     - name: Clone repo
       uses: actions/checkout@v4.1.2
@@ -71,7 +71,7 @@ jobs:
     - name: Set up python
       uses: actions/setup-python@v5.1.0
       with:
-        python-version: '3.9'
+        python-version: '3.10'
     - name: Cache dependencies
       uses: actions/cache@v4.0.2
       id: cache

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ repos:
         rev: v3.15.2
         hooks:
         -   id: pyupgrade
-            args: [--py39-plus]
+            args: [--py310-plus]
 
     -   repo: https://github.com/pycqa/isort
         rev: 5.13.2

docs/user/contributing.rst

@@ -103,7 +103,7 @@ All of these tools should be used from the root of the project to ensure that ou
 
    $ black .
    $ isort .
-   $ pyupgrade --py39-plus $(find . -name "*.py")
+   $ pyupgrade --py310-plus $(find . -name "*.py")
 
 
 Flake8, pydocstyle, and mypy won't format your code for you, but they will warn you about potential issues with your code or docstrings:

experiments/ssl4eo/download_ssl4eo.py

@@ -56,7 +56,7 @@ import warnings
 from collections import defaultdict
 from datetime import date, timedelta
 from multiprocessing.dummy import Lock, Pool
-from typing import Any, Optional
+from typing import Any
 
 import ee
 import numpy as np
@@ -168,7 +168,7 @@ def get_patch(
     new_resolutions: list[int],
     dtype: str = "float32",
     meta_cloud_name: str = "CLOUD_COVER",
-    default_value: Optional[float] = None,
+    default_value: float | None = None,
 ) -> dict[str, Any]:
     image = collection.sort(meta_cloud_name).first()
     region = ee.Geometry.Point(center_coord).buffer(radius).bounds()
@@ -214,7 +214,7 @@ def get_random_patches_match(
     new_resolutions: list[int],
     dtype: str,
     meta_cloud_name: str,
-    default_value: Optional[float],
+    default_value: float | None,
     dates: list[date],
     radius: float,
     debug: bool = False,

pyproject.toml

@@ -10,7 +10,7 @@ build-backend = "setuptools.build_meta"
 name = "torchgeo"
 description = "TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data"
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license = {file = "LICENSE"}
 authors = [
     {name = "Adam J. Stewart", email = "ajstewart426@gmail.com"},
@@ -29,7 +29,6 @@ classifiers = [
     "License :: OSI Approved :: MIT License",
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -39,9 +38,8 @@ classifiers = [
 dependencies = [
     # einops 0.3+ required for einops.repeat
     "einops>=0.3",
-    # fiona 1.8.19+ required to fix erroneous warning
-    # https://github.com/Toblerity/Fiona/issues/986
-    "fiona>=1.8.19",
+    # fiona 1.8.21+ required for Python 3.10 wheels
+    "fiona>=1.8.21",
     # kornia 0.6.9+ required for kornia.augmentation.RandomBrightness
     "kornia>=0.6.9",
     # lightly 1.4.4+ required for MoCo v3 support
@@ -50,24 +48,24 @@ dependencies = [
     "lightly>=1.4.4,!=1.4.26",
     # lightning 2+ required for LightningCLI args + sys.argv support
     "lightning[pytorch-extra]>=2",
-    # matplotlib 3.3.3+ required for Python 3.9 wheels
-    "matplotlib>=3.3.3",
-    # numpy 1.19.3+ required by Python 3.9 wheels
-    "numpy>=1.19.3",
-    # pandas 1.1.3+ required for Python 3.9 wheels
-    "pandas>=1.1.3",
-    # pillow 8+ required for Python 3.9 wheels
-    "pillow>=8",
-    # pyproj 3+ required for Python 3.9 wheels
-    "pyproj>=3",
-    # rasterio 1.2+ required for Python 3.9 wheels
-    "rasterio>=1.2",
-    # rtree 1+ required for len(index), index & index, index | index
+    # matplotlib 3.5+ required for Python 3.10 wheels
+    "matplotlib>=3.5",
+    # numpy 1.21.2+ required by Python 3.10 wheels
+    "numpy>=1.21.2",
+    # pandas 1.3.3+ required for Python 3.10 wheels
+    "pandas>=1.3.3",
+    # pillow 8.4+ required for Python 3.10 wheels
+    "pillow>=8.4",
+    # pyproj 3.3+ required for Python 3.10 wheels
+    "pyproj>=3.3",
+    # rasterio 1.3+ required for Python 3.10 wheels
+    "rasterio>=1.3",
+    # rtree 1+ required for Python 3.10 wheels
     "rtree>=1",
     # segmentation-models-pytorch 0.2+ required for smp.losses module
     "segmentation-models-pytorch>=0.2",
-    # shapely 1.7.1+ required for Python 3.9 wheels
-    "shapely>=1.7.1",
+    # shapely 1.8+ required for Python 3.10 wheels
+    "shapely>=1.8",
     # timm 0.4.12 required by segmentation-models-pytorch
     "timm>=0.4.12",
     # torch 1.13+ required by torchvision
@@ -81,27 +79,25 @@ dynamic = ["version"]
 
 [project.optional-dependencies]
 datasets = [
-    # h5py 3+ required for Python 3.9 wheels
-    "h5py>=3",
+    # h5py 3.6+ required for Python 3.10 wheels
+    "h5py>=3.6",
     # laspy 2+ required for laspy.read
     "laspy>=2",
-    # opencv-python 4.4.0.46+ required for Python 3.9 wheels
-    "opencv-python>=4.4.0.46",
-    # pycocotools 2.0.5+ required for cython 3+ support
-    "pycocotools>=2.0.5",
+    # opencv-python 4.5.4+ required for Python 3.10 wheels
+    "opencv-python>=4.5.4",
+    # pycocotools 2.0.7+ required for wheels
+    "pycocotools>=2.0.7",
     # pyvista 0.34.2+ required to avoid ImportError in CI
     "pyvista>=0.34.2",
     # radiant-mlhub 0.3+ required for newer tqdm support required by lightning
     "radiant-mlhub>=0.3",
     # rarfile 4+ required for wheels
     "rarfile>=4",
-    # scikit-image 0.18+ required for numpy 1.17+ compatibility
-    # https://github.com/scikit-image/scikit-image/issues/3655
-    "scikit-image>=0.18",
-    # scipy 1.6.2+ required for scikit-image 0.18+ compatibility
-    "scipy>=1.6.2",
-    # zipfile-deflate64 0.2+ required for extraction bugfix:
-    # https://github.com/brianhelba/zipfile-deflate64/issues/19
+    # scikit-image 0.19+ required for Python 3.10 wheels
+    "scikit-image>=0.19",
+    # scipy 1.7.2+ required for Python 3.10 wheels
+    "scipy>=1.7.2",
+    # zipfile-deflate64 0.2+ required for Python 3.10 wheels
     "zipfile-deflate64>=0.2",
 ]
 docs = [
@@ -126,7 +122,7 @@ style = [
     "isort[colors]>=5.8",
     # pydocstyle 6.1+ required for pyproject.toml support
     "pydocstyle[toml]>=6.1",
-    # pyupgrade 2.8+ required for --py39-plus flag
+    # pyupgrade 2.8+ required for --py310-plus flag
     "pyupgrade>=2.8",
 ]
 tests = [
@@ -151,7 +147,7 @@ Homepage = "https://github.com/microsoft/torchgeo"
 Documentation = "https://torchgeo.readthedocs.io"
 
 [tool.black]
-target-version = ["py39", "py310"]
+target-version = ["py310"]
 color = true
 skip_magic_trailing_comma = true
 
@@ -170,7 +166,7 @@ skip_gitignore = true
 color_output = true
 
 [tool.mypy]
-python_version = "3.9"
+python_version = "3.10"
 ignore_missing_imports = true
 show_error_codes = true
 exclude = "(build|data|dist|docs/src|images|logo|logs|output)/"

requirements/min-reqs.old

@@ -3,34 +3,34 @@ setuptools==61.0.0
 
 # install
 einops==0.3.0
-fiona==1.8.19
+fiona==1.8.21
 kornia==0.6.9
 lightly==1.4.4
 lightning[pytorch-extra]==2.0.0
-matplotlib==3.3.3
-numpy==1.19.3
-pandas==1.1.3
-pillow==8.0.0
-pyproj==3.0.0
-rasterio==1.2.0
+matplotlib==3.5.0
+numpy==1.21.2
+pandas==1.3.3
+pillow==8.4.0
+pyproj==3.3.0
+rasterio==1.3.0.post1
 rtree==1.0.0
 segmentation-models-pytorch==0.2.0
-shapely==1.7.1
+shapely==1.8.0
 timm==0.4.12
 torch==1.13.0
 torchmetrics==0.10.0
 torchvision==0.14.0
 
 # datasets
-h5py==3.0.0
+h5py==3.6.0
 laspy==2.0.0
-opencv-python==4.4.0.46
-pycocotools==2.0.5
+opencv-python==4.5.4.58
+pycocotools==2.0.7
 pyvista==0.34.2
 radiant-mlhub==0.3.0
 rarfile==4.0
-scikit-image==0.18.0
-scipy==1.6.2
+scikit-image==0.19.0
+scipy==1.7.2
 zipfile-deflate64==0.2.0
 
 # docs

tests/data/raster/data.py

@@ -2,7 +2,6 @@
 # Licensed under the MIT License.
 
 import os
-from typing import Optional
 
 import numpy as np
 import rasterio as rio
@@ -18,7 +17,7 @@ def write_raster(
     res: int = RES[0],
     epsg: int = EPSG[0],
     dtype: str = "uint8",
-    path: Optional[str] = None,
+    path: str | None = None,
 ) -> None:
     """Write a raster file.
 

tests/datasets/test_geo.py

@@ -5,7 +5,6 @@ import pickle
 import sys
 from collections.abc import Iterable
 from pathlib import Path
-from typing import Optional, Union
 
 import pytest
 import torch
@@ -35,7 +34,7 @@ class CustomGeoDataset(GeoDataset):
         bounds: BoundingBox = BoundingBox(0, 1, 2, 3, 4, 5),
         crs: CRS = CRS.from_epsg(4087),
         res: float = 1,
-        paths: Optional[Union[str, Iterable[str]]] = None,
+        paths: str | Iterable[str] | None = None,
     ) -> None:
         super().__init__()
         self.index.insert(0, tuple(bounds))
@@ -249,7 +248,7 @@ class TestRasterDataset:
             },
         ],
     )
-    def test_files(self, paths: Union[str, Iterable[str]]) -> None:
+    def test_files(self, paths: str | Iterable[str]) -> None:
         assert 1 <= len(NAIP(paths).files) <= 2
 
     def test_getitem_single_file(self, naip: NAIP) -> None:

tests/datasets/test_splits.py

@@ -3,7 +3,7 @@
 
 from collections.abc import Sequence
 from math import floor, isclose
-from typing import Any, Union
+from typing import Any
 
 import pytest
 from rasterio.crs import CRS
@@ -65,7 +65,7 @@ class CustomGeoDataset(GeoDataset):
     ],
 )
 def test_random_bbox_assignment(
-    lengths: Sequence[Union[int, float]], expected_lengths: Sequence[int]
+    lengths: Sequence[int | float], expected_lengths: Sequence[int]
 ) -> None:
     ds = CustomGeoDataset(
         [
@@ -255,8 +255,7 @@ def test_roi_split() -> None:
     ],
 )
 def test_time_series_split(
-    lengths: Sequence[Union[tuple[int, int], int, float]],
-    expected_lengths: Sequence[int],
+    lengths: Sequence[tuple[int, int] | int | float], expected_lengths: Sequence[int]
 ) -> None:
     ds = CustomGeoDataset(
         [

tests/models/test_api.py

@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 import enum
-from typing import Callable
+from collections.abc import Callable
 
 import pytest
 import torch.nn as nn

tests/samplers/test_utils.py

@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 import math
-from typing import Optional, Union
+from typing import Union
 
 import pytest
 
@@ -33,7 +33,7 @@ MAYBE_TUPLE = Union[float, tuple[float, float]]
     ],
 )
 def test_tile_to_chips(
-    size: MAYBE_TUPLE, stride: Optional[MAYBE_TUPLE], expected: MAYBE_TUPLE
+    size: MAYBE_TUPLE, stride: MAYBE_TUPLE | None, expected: MAYBE_TUPLE
 ) -> None:
     bounds = BoundingBox(0, 10, 20, 30, 40, 50)
     size = _to_tuple(size)

torchgeo/datamodules/agrifieldnet.py

@@ -3,7 +3,7 @@
 
 """AgriFieldNet datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -25,8 +25,8 @@ class AgriFieldNetDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 256,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 256,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/chesapeake.py

@@ -3,7 +3,7 @@
 
 """Chesapeake Bay High-Resolution Land Cover Project datamodule."""
 
-from typing import Any, Optional
+from typing import Any
 
 import kornia.augmentation as K
 import torch.nn as nn
@@ -63,7 +63,7 @@ class ChesapeakeCVPRDataModule(GeoDataModule):
         test_splits: list[str],
         batch_size: int = 64,
         patch_size: int = 256,
-        length: Optional[int] = None,
+        length: int | None = None,
         num_workers: int = 0,
         class_set: int = 7,
         use_prior_labels: bool = False,

torchgeo/datamodules/deepglobelandcover.py

@@ -3,7 +3,7 @@
 
 """DeepGlobe Land Cover Classification Challenge datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -24,7 +24,7 @@ class DeepGlobeLandCoverDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/geo.py

@@ -3,7 +3,8 @@
 
 """Base classes for all :mod:`torchgeo` data modules."""
 
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable
+from typing import Any, cast
 
 import kornia.augmentation as K
 import torch
@@ -55,27 +56,27 @@ class BaseDataModule(LightningDataModule):
         self.kwargs = kwargs
 
         # Datasets
-        self.dataset: Optional[Dataset[dict[str, Tensor]]] = None
-        self.train_dataset: Optional[Dataset[dict[str, Tensor]]] = None
-        self.val_dataset: Optional[Dataset[dict[str, Tensor]]] = None
-        self.test_dataset: Optional[Dataset[dict[str, Tensor]]] = None
-        self.predict_dataset: Optional[Dataset[dict[str, Tensor]]] = None
+        self.dataset: Dataset[dict[str, Tensor]] | None = None
+        self.train_dataset: Dataset[dict[str, Tensor]] | None = None
+        self.val_dataset: Dataset[dict[str, Tensor]] | None = None
+        self.test_dataset: Dataset[dict[str, Tensor]] | None = None
+        self.predict_dataset: Dataset[dict[str, Tensor]] | None = None
 
         # Data loaders
-        self.train_batch_size: Optional[int] = None
-        self.val_batch_size: Optional[int] = None
-        self.test_batch_size: Optional[int] = None
-        self.predict_batch_size: Optional[int] = None
+        self.train_batch_size: int | None = None
+        self.val_batch_size: int | None = None
+        self.test_batch_size: int | None = None
+        self.predict_batch_size: int | None = None
 
         # Data augmentation
         Transform = Callable[[dict[str, Tensor]], dict[str, Tensor]]
         self.aug: Transform = AugmentationSequential(
             K.Normalize(mean=self.mean, std=self.std), data_keys=["image"]
         )
-        self.train_aug: Optional[Transform] = None
-        self.val_aug: Optional[Transform] = None
-        self.test_aug: Optional[Transform] = None
-        self.predict_aug: Optional[Transform] = None
+        self.train_aug: Transform | None = None
+        self.val_aug: Transform | None = None
+        self.test_aug: Transform | None = None
+        self.predict_aug: Transform | None = None
 
     def prepare_data(self) -> None:
         """Download and prepare data.
@@ -141,7 +142,7 @@ class BaseDataModule(LightningDataModule):
 
         return batch
 
-    def plot(self, *args: Any, **kwargs: Any) -> Optional[Figure]:
+    def plot(self, *args: Any, **kwargs: Any) -> Figure | None:
         """Run the plot method of the validation dataset if one exists.
 
         Should only be called during 'fit' or 'validate' stages as ``val_dataset``
@@ -154,7 +155,7 @@ class BaseDataModule(LightningDataModule):
         Returns:
             A matplotlib Figure with the image, ground truth, and predictions.
         """
-        fig: Optional[Figure] = None
+        fig: Figure | None = None
         dataset = self.dataset or self.val_dataset
         if dataset is not None:
             if hasattr(dataset, "plot"):
@@ -172,8 +173,8 @@ class GeoDataModule(BaseDataModule):
         self,
         dataset_class: type[GeoDataset],
         batch_size: int = 1,
-        patch_size: Union[int, tuple[int, int]] = 64,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 64,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:
@@ -196,18 +197,18 @@ class GeoDataModule(BaseDataModule):
         self.collate_fn = stack_samples
 
         # Samplers
-        self.sampler: Optional[GeoSampler] = None
-        self.train_sampler: Optional[GeoSampler] = None
-        self.val_sampler: Optional[GeoSampler] = None
-        self.test_sampler: Optional[GeoSampler] = None
-        self.predict_sampler: Optional[GeoSampler] = None
+        self.sampler: GeoSampler | None = None
+        self.train_sampler: GeoSampler | None = None
+        self.val_sampler: GeoSampler | None = None
+        self.test_sampler: GeoSampler | None = None
+        self.predict_sampler: GeoSampler | None = None
 
         # Batch samplers
-        self.batch_sampler: Optional[BatchGeoSampler] = None
-        self.train_batch_sampler: Optional[BatchGeoSampler] = None
-        self.val_batch_sampler: Optional[BatchGeoSampler] = None
-        self.test_batch_sampler: Optional[BatchGeoSampler] = None
-        self.predict_batch_sampler: Optional[BatchGeoSampler] = None
+        self.batch_sampler: BatchGeoSampler | None = None
+        self.train_batch_sampler: BatchGeoSampler | None = None
+        self.val_batch_sampler: BatchGeoSampler | None = None
+        self.test_batch_sampler: BatchGeoSampler | None = None
+        self.predict_batch_sampler: BatchGeoSampler | None = None
 
     def setup(self, stage: str) -> None:
         """Set up datasets and samplers.

torchgeo/datamodules/gid15.py

@@ -3,7 +3,7 @@
 
 """GID-15 datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -26,7 +26,7 @@ class GID15DataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/inria.py

@@ -3,7 +3,7 @@
 
 """InriaAerialImageLabeling datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -26,7 +26,7 @@ class InriaAerialImageLabelingDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/l7irish.py

@@ -3,7 +3,7 @@
 
 """L7 Irish datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -25,8 +25,8 @@ class L7IrishDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 1,
-        patch_size: Union[int, tuple[int, int]] = 224,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 224,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/l8biome.py

@@ -3,7 +3,7 @@
 
 """L8 Biome datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -25,8 +25,8 @@ class L8BiomeDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 1,
-        patch_size: Union[int, tuple[int, int]] = 224,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 224,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/levircd.py

@@ -3,7 +3,7 @@
 
 """LEVIR-CD+ datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -25,7 +25,7 @@ class LEVIRCDDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 8,
-        patch_size: Union[tuple[int, int], int] = 256,
+        patch_size: tuple[int, int] | int = 256,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:
@@ -70,7 +70,7 @@ class LEVIRCDPlusDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 8,
-        patch_size: Union[tuple[int, int], int] = 256,
+        patch_size: tuple[int, int] | int = 256,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/naip.py

@@ -3,7 +3,7 @@
 
 """National Agriculture Imagery Program (NAIP) datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 from matplotlib.figure import Figure
@@ -23,8 +23,8 @@ class NAIPChesapeakeDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 256,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 256,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/oscd.py

@@ -3,7 +3,7 @@
 
 """OSCD datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -60,7 +60,7 @@ class OSCDDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/potsdam.py

@@ -3,7 +3,7 @@
 
 """Potsdam datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -26,7 +26,7 @@ class Potsdam2DDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/sentinel2_cdl.py

@@ -3,7 +3,7 @@
 
 """Sentinel-2 and CDL datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -26,8 +26,8 @@ class Sentinel2CDLDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 64,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 64,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/sentinel2_nccm.py

@@ -3,7 +3,7 @@
 
 """Sentinel-2 and NCCM datamodule."""
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -26,8 +26,8 @@ class Sentinel2NCCMDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 64,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 64,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/sentinel2_south_america_soybean.py

@@ -5,7 +5,7 @@
 """South America Soybean datamodule."""
 
 
-from typing import Any, Optional, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -28,8 +28,8 @@ class Sentinel2SouthAmericaSoybeanDataModule(GeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 64,
-        length: Optional[int] = None,
+        patch_size: int | tuple[int, int] = 64,
+        length: int | None = None,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/ssl4eo_benchmark.py

@@ -3,7 +3,7 @@
 
 """SSL4EO datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 from kornia.constants import DataKey, Resample
@@ -23,7 +23,7 @@ class SSL4EOLBenchmarkDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[int, tuple[int, int]] = 224,
+        patch_size: int | tuple[int, int] = 224,
         num_workers: int = 0,
         **kwargs: Any,
     ) -> None:

torchgeo/datamodules/utils.py

@@ -4,8 +4,8 @@
 """Common datamodule utilities."""
 
 import math
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import numpy as np
 import torch
@@ -103,9 +103,9 @@ def collate_fn_detection(batch: list[dict[str, Tensor]]) -> dict[str, Any]:
 
 
 def dataset_split(
-    dataset: Union[TensorDataset, NonGeoDataset],
+    dataset: TensorDataset | NonGeoDataset,
     val_pct: float,
-    test_pct: Optional[float] = None,
+    test_pct: float | None = None,
 ) -> list[Subset[Any]]:
     """Split a torch Dataset into train/val/test sets.
 
@@ -142,9 +142,9 @@ def dataset_split(
 
 def group_shuffle_split(
     groups: Iterable[Any],
-    train_size: Optional[float] = None,
-    test_size: Optional[float] = None,
-    random_state: Optional[int] = None,
+    train_size: float | None = None,
+    test_size: float | None = None,
+    random_state: int | None = None,
 ) -> tuple[list[int], list[int]]:
     """Method for performing a single group-wise shuffle split of data.
 

torchgeo/datamodules/vaihingen.py

@@ -3,7 +3,7 @@
 
 """Vaihingen datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 
@@ -26,7 +26,7 @@ class Vaihingen2DDataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 64,
+        patch_size: tuple[int, int] | int = 64,
         val_split_pct: float = 0.2,
         num_workers: int = 0,
         **kwargs: Any,

torchgeo/datamodules/vhr10.py

@@ -3,7 +3,7 @@
 
 """NWPU VHR-10 datamodule."""
 
-from typing import Any, Union
+from typing import Any
 
 import kornia.augmentation as K
 import torch
@@ -26,7 +26,7 @@ class VHR10DataModule(NonGeoDataModule):
     def __init__(
         self,
         batch_size: int = 64,
-        patch_size: Union[tuple[int, int], int] = 512,
+        patch_size: tuple[int, int] | int = 512,
         num_workers: int = 0,
         val_split_pct: float = 0.2,
         test_split_pct: float = 0.2,

torchgeo/datasets/advance.py

@@ -5,7 +5,8 @@
 
 import glob
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -87,7 +88,7 @@ class ADVANCE(NonGeoDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -228,7 +229,7 @@ class ADVANCE(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/agb_live_woody_density.py

@@ -5,8 +5,8 @@
 
 import json
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -56,10 +56,10 @@ class AbovegroundLiveWoodyBiomassDensity(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
         cache: bool = True,
     ) -> None:
@@ -121,7 +121,7 @@ class AbovegroundLiveWoodyBiomassDensity(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/agrifieldnet.py

@@ -5,8 +5,8 @@
 
 import os
 import re
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 import torch
@@ -113,11 +113,11 @@ class AgriFieldNet(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         classes: list[int] = list(cmap.keys()),
         bands: Sequence[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new AgriFieldNet dataset instance.
@@ -218,7 +218,7 @@ class AgriFieldNet(RasterDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/airphen.py

@@ -3,7 +3,7 @@
 
 """Airphen dataset."""
 
-from typing import Any, Optional
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -46,7 +46,7 @@ class Airphen(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/astergdem.py

@@ -3,7 +3,8 @@
 
 """Aster Global Digital Elevation Model dataset."""
 
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -46,10 +47,10 @@ class AsterGDEM(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, list[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | list[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new Dataset instance.
@@ -89,7 +90,7 @@ class AsterGDEM(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/benin_cashews.py

@@ -5,8 +5,8 @@
 
 import json
 import os
+from collections.abc import Callable
 from functools import lru_cache
-from typing import Callable, Optional
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -182,9 +182,9 @@ class BeninSmallHolderCashews(NonGeoDataset):
         chip_size: int = 256,
         stride: int = 128,
         bands: tuple[str, ...] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
         verbose: bool = False,
     ) -> None:
@@ -408,7 +408,7 @@ class BeninSmallHolderCashews(NonGeoDataset):
 
         return images and targets
 
-    def _download(self, api_key: Optional[str] = None) -> None:
+    def _download(self, api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -434,7 +434,7 @@ class BeninSmallHolderCashews(NonGeoDataset):
         sample: dict[str, Tensor],
         show_titles: bool = True,
         time_step: int = 0,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/bigearthnet.py

@@ -6,7 +6,7 @@
 import glob
 import json
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -275,7 +275,7 @@ class BigEarthNet(NonGeoDataset):
         split: str = "train",
         bands: str = "all",
         num_classes: int = 19,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -533,7 +533,7 @@ class BigEarthNet(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/biomassters.py

@@ -5,7 +5,6 @@
 
 import os
 from collections.abc import Sequence
-from typing import Optional
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -219,7 +218,7 @@ class BioMassters(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cbf.py

@@ -4,8 +4,8 @@
 """Canadian Building Footprints dataset."""
 
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -61,10 +61,10 @@ class CanadianBuildingFootprints(VectorDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         res: float = 0.00001,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -127,7 +127,7 @@ class CanadianBuildingFootprints(VectorDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cdl.py

@@ -4,8 +4,8 @@
 """CDL dataset."""
 
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import torch
@@ -206,12 +206,12 @@ class CDL(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         years: list[int] = [2023],
         classes: list[int] = list(cmap.keys()),
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -336,7 +336,7 @@ class CDL(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/chabud.py

@@ -4,7 +4,7 @@
 """ChaBuD dataset."""
 
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -77,7 +77,7 @@ class ChaBuD(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         bands: list[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -235,7 +235,7 @@ class ChaBuD(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/chesapeake.py

@@ -6,8 +6,8 @@
 import abc
 import os
 import sys
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, cast
 
 import fiona
 import matplotlib.pyplot as plt
@@ -90,10 +90,10 @@ class Chesapeake(RasterDataset, abc.ABC):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -170,7 +170,7 @@ class Chesapeake(RasterDataset, abc.ABC):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -512,7 +512,7 @@ class ChesapeakeCVPR(GeoDataset):
         root: str = "data",
         splits: Sequence[str] = ["de-train"],
         layers: Sequence[str] = ["naip-new", "lc"],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -711,7 +711,7 @@ class ChesapeakeCVPR(GeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cloud_cover.py

@@ -5,8 +5,8 @@
 
 import json
 import os
-from collections.abc import Sequence
-from typing import Any, Callable, Optional
+from collections.abc import Callable, Sequence
+from typing import Any
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -111,9 +111,9 @@ class CloudCoverDetection(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         bands: Sequence[str] = band_names,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initiatlize a new Cloud Cover Detection Dataset instance.
@@ -329,7 +329,7 @@ class CloudCoverDetection(NonGeoDataset):
 
         return images and targets
 
-    def _download(self, api_key: Optional[str] = None) -> None:
+    def _download(self, api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -355,7 +355,7 @@ class CloudCoverDetection(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cms_mangrove_canopy.py

@@ -4,7 +4,8 @@
 """CMS Global Mangrove Canopy dataset."""
 
 import os
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -167,12 +168,12 @@ class CMSGlobalMangroveCanopy(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, list[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | list[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         measurement: str = "agb",
         country: str = all_countries[0],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         checksum: bool = False,
     ) -> None:
@@ -250,7 +251,7 @@ class CMSGlobalMangroveCanopy(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cowc.py

@@ -6,7 +6,8 @@
 import abc
 import csv
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -65,7 +66,7 @@ class COWC(NonGeoDataset, abc.ABC):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -192,7 +193,7 @@ class COWC(NonGeoDataset, abc.ABC):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cropharvest.py

@@ -6,7 +6,7 @@
 import glob
 import json
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -96,7 +96,7 @@ class CropHarvest(NonGeoDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -293,7 +293,7 @@ class CropHarvest(NonGeoDataset):
         features_path = os.path.join(self.root, self.file_dict["features"]["filename"])
         extract_archive(features_path)
 
-    def plot(self, sample: dict[str, Tensor], subtitle: Optional[str] = None) -> Figure:
+    def plot(self, sample: dict[str, Tensor], subtitle: str | None = None) -> Figure:
         """Plot a sample from the dataset using bands for Agriculture RGB composite.
 
         Args:

torchgeo/datasets/cv4a_kenya_crop_type.py

@@ -5,8 +5,8 @@
 
 import csv
 import os
+from collections.abc import Callable
 from functools import lru_cache
-from typing import Callable, Optional
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -125,9 +125,9 @@ class CV4AKenyaCropType(NonGeoDataset):
         chip_size: int = 256,
         stride: int = 128,
         bands: tuple[str, ...] = band_names,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
         verbose: bool = False,
     ) -> None:
@@ -388,7 +388,7 @@ class CV4AKenyaCropType(NonGeoDataset):
 
         return train_field_ids, test_field_ids
 
-    def _download(self, api_key: Optional[str] = None) -> None:
+    def _download(self, api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -411,7 +411,7 @@ class CV4AKenyaCropType(NonGeoDataset):
         sample: dict[str, Tensor],
         show_titles: bool = True,
         time_step: int = 0,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/cyclone.py

@@ -5,8 +5,9 @@
 
 import json
 import os
+from collections.abc import Callable
 from functools import lru_cache
-from typing import Any, Callable, Optional
+from typing import Any
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -73,9 +74,9 @@ class TropicalCyclone(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new Tropical Cyclone Wind Estimation Competition Dataset.
@@ -204,7 +205,7 @@ class TropicalCyclone(NonGeoDataset):
                     return False
         return True
 
-    def _download(self, api_key: Optional[str] = None) -> None:
+    def _download(self, api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -227,7 +228,7 @@ class TropicalCyclone(NonGeoDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/deepglobelandcover.py

@@ -4,7 +4,7 @@
 """DeepGlobe Land Cover Classification Challenge dataset."""
 
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -102,7 +102,7 @@ class DeepGlobeLandCover(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new DeepGlobeLandCover dataset instance.
@@ -229,7 +229,7 @@ class DeepGlobeLandCover(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
         alpha: float = 0.5,
     ) -> Figure:
         """Plot a sample from the dataset.

torchgeo/datasets/dfc2022.py

@@ -5,8 +5,7 @@
 
 import glob
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional
+from collections.abc import Callable, Sequence
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -144,7 +143,7 @@ class DFC2022(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new DFC2022 dataset instance.
@@ -229,7 +228,7 @@ class DFC2022(NonGeoDataset):
 
         return files
 
-    def _load_image(self, path: str, shape: Optional[Sequence[int]] = None) -> Tensor:
+    def _load_image(self, path: str, shape: Sequence[int] | None = None) -> Tensor:
         """Load a single image.
 
         Args:
@@ -296,7 +295,7 @@ class DFC2022(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/enviroatlas.py

@@ -5,8 +5,8 @@
 
 import os
 import sys
-from collections.abc import Sequence
-from typing import Any, Callable, Optional, cast
+from collections.abc import Callable, Sequence
+from typing import Any, cast
 
 import fiona
 import matplotlib.pyplot as plt
@@ -255,7 +255,7 @@ class EnviroAtlas(GeoDataset):
         root: str = "data",
         splits: Sequence[str] = ["pittsburgh_pa-2010_1m-train"],
         layers: Sequence[str] = ["naip", "prior"],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         prior_as_input: bool = False,
         cache: bool = True,
         download: bool = False,
@@ -445,7 +445,7 @@ class EnviroAtlas(GeoDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/esri2020.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -68,10 +68,10 @@ class Esri2020(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -138,7 +138,7 @@ class Esri2020(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/etci2021.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -82,7 +82,7 @@ class ETCI2021(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -255,7 +255,7 @@ class ETCI2021(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/eudem.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -83,10 +83,10 @@ class EUDEM(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         checksum: bool = False,
     ) -> None:
@@ -140,7 +140,7 @@ class EUDEM(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/eurocrops.py

@@ -5,8 +5,8 @@
 
 import csv
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import fiona
 import matplotlib.pyplot as plt
@@ -88,11 +88,11 @@ class EuroCrops(VectorDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
+        paths: str | Iterable[str] = "data",
         crs: CRS = CRS.from_epsg(4326),
         res: float = 0.00001,
-        classes: Optional[list[str]] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        classes: list[str] | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -166,7 +166,7 @@ class EuroCrops(VectorDataset):
                 self.base_url + fname, self.paths, md5=md5 if self.checksum else None
             )
 
-    def _load_class_map(self, classes: Optional[list[str]]) -> None:
+    def _load_class_map(self, classes: list[str] | None) -> None:
         """Load map from HCAT class codes to class indices.
 
         If classes is provided, then we simply use those codes. Otherwise, we load
@@ -221,7 +221,7 @@ class EuroCrops(VectorDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/eurosat.py

@@ -4,8 +4,8 @@
 """EuroSAT dataset."""
 
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional, cast
+from collections.abc import Callable, Sequence
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -106,7 +106,7 @@ class EuroSAT(NonGeoClassificationDataset):
         root: str = "data",
         split: str = "train",
         bands: Sequence[str] = BAND_SETS["all"],
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -247,7 +247,7 @@ class EuroSAT(NonGeoClassificationDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/fair1m.py

@@ -5,7 +5,8 @@
 
 import glob
 import os
-from typing import Any, Callable, Optional, cast
+from collections.abc import Callable
+from typing import Any, cast
 from xml.etree.ElementTree import Element, parse
 
 import matplotlib.patches as patches
@@ -230,7 +231,7 @@ class FAIR1M(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -382,7 +383,7 @@ class FAIR1M(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/fire_risk.py

@@ -4,7 +4,8 @@
 """FireRisk dataset."""
 
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -68,7 +69,7 @@ class FireRisk(NonGeoClassificationDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -136,7 +137,7 @@ class FireRisk(NonGeoClassificationDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/forestdamage.py

@@ -5,7 +5,8 @@
 
 import glob
 import os
-from typing import Any, Callable, Optional
+from collections.abc import Callable
+from typing import Any
 from xml.etree import ElementTree
 
 import matplotlib.patches as patches
@@ -110,7 +111,7 @@ class ForestDamage(NonGeoDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -259,7 +260,7 @@ class ForestDamage(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/geo.py

@@ -10,8 +10,8 @@ import os
 import re
 import sys
 import warnings
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, cast
 
 import fiona
 import fiona.transform
@@ -83,7 +83,7 @@ class GeoDataset(Dataset[dict[str, Any]], abc.ABC):
        dataset = landsat7 | landsat8
     """
 
-    paths: Union[str, Iterable[str]]
+    paths: str | Iterable[str]
     _crs = CRS.from_epsg(4326)
     _res = 0.0
 
@@ -108,7 +108,7 @@ class GeoDataset(Dataset[dict[str, Any]], abc.ABC):
     __add__ = None  # type: ignore[assignment]
 
     def __init__(
-        self, transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None
+        self, transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None
     ) -> None:
         """Initialize a new GeoDataset instance.
 
@@ -190,9 +190,7 @@ class GeoDataset(Dataset[dict[str, Any]], abc.ABC):
     # NOTE: This hack should be removed once the following issue is fixed:
     # https://github.com/Toblerity/rtree/issues/87
 
-    def __getstate__(
-        self,
-    ) -> tuple[dict[str, Any], list[tuple[Any, Any, Optional[Any]]]]:
+    def __getstate__(self) -> tuple[dict[str, Any], list[tuple[Any, Any, Any | None]]]:
         """Define how instances are pickled.
 
         Returns:
@@ -388,11 +386,11 @@ class RasterDataset(GeoDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        bands: Optional[Sequence[str]] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        bands: Sequence[str] | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new RasterDataset instance.
@@ -539,7 +537,7 @@ class RasterDataset(GeoDataset):
         self,
         filepaths: Sequence[str],
         query: BoundingBox,
-        band_indexes: Optional[Sequence[int]] = None,
+        band_indexes: Sequence[int] | None = None,
     ) -> Tensor:
         """Load and merge one or more files.
 
@@ -612,11 +610,11 @@ class VectorDataset(GeoDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         res: float = 0.0001,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
-        label_name: Optional[str] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
+        label_name: str | None = None,
     ) -> None:
         """Initialize a new VectorDataset instance.
 
@@ -809,9 +807,9 @@ class NonGeoClassificationDataset(NonGeoDataset, ImageFolder):  # type: ignore[m
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
-        loader: Optional[Callable[[str], Any]] = pil_loader,
-        is_valid_file: Optional[Callable[[str], bool]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
+        loader: Callable[[str], Any] | None = pil_loader,
+        is_valid_file: Callable[[str], bool] | None = None,
     ) -> None:
         """Initialize a new NonGeoClassificationDataset instance.
 
@@ -909,7 +907,7 @@ class IntersectionDataset(GeoDataset):
         collate_fn: Callable[
             [Sequence[dict[str, Any]]], dict[str, Any]
         ] = concat_samples,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
     ) -> None:
         """Initialize a new IntersectionDataset instance.
 
@@ -1067,7 +1065,7 @@ class UnionDataset(GeoDataset):
         collate_fn: Callable[
             [Sequence[dict[str, Any]]], dict[str, Any]
         ] = merge_samples,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
     ) -> None:
         """Initialize a new UnionDataset instance.
 

torchgeo/datasets/gid15.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -89,7 +89,7 @@ class GID15(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -234,7 +234,7 @@ class GID15(NonGeoDataset):
             md5=self.md5 if self.checksum else None,
         )
 
-    def plot(self, sample: dict[str, Tensor], suptitle: Optional[str] = None) -> Figure:
+    def plot(self, sample: dict[str, Tensor], suptitle: str | None = None) -> Figure:
         """Plot a sample from the dataset.
 
         Args:

torchgeo/datasets/globbiomass.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 import torch
@@ -119,11 +119,11 @@ class GlobBiomass(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         measurement: str = "agb",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         checksum: bool = False,
     ) -> None:
@@ -225,7 +225,7 @@ class GlobBiomass(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/idtrees.py

@@ -5,7 +5,8 @@
 
 import glob
 import os
-from typing import Any, Callable, Optional, cast, overload
+from collections.abc import Callable
+from typing import Any, cast, overload
 
 import fiona
 import matplotlib.pyplot as plt
@@ -148,7 +149,7 @@ class IDTReeS(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         task: str = "task1",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -333,7 +334,7 @@ class IDTReeS(NonGeoDataset):
 
     def _load(
         self, root: str
-    ) -> tuple[list[str], Optional[dict[int, dict[str, Any]]], Any]:
+    ) -> tuple[list[str], dict[int, dict[str, Any]] | None, Any]:
         """Load files, geometries, and labels.
 
         Args:
@@ -419,8 +420,8 @@ class IDTReeS(NonGeoDataset):
         image_size: tuple[int, int],
         min_size: int,
         boxes: Tensor,
-        labels: Optional[Tensor],
-    ) -> tuple[Tensor, Optional[Tensor]]:
+        labels: Tensor | None,
+    ) -> tuple[Tensor, Tensor | None]:
         """Clip boxes to image size and filter boxes with sides less than ``min_size``.
 
         Args:
@@ -477,7 +478,7 @@ class IDTReeS(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
         hsi_indices: tuple[int, int, int] = (0, 1, 2),
     ) -> Figure:
         """Plot a sample from the dataset.

torchgeo/datasets/inria.py

@@ -6,7 +6,8 @@
 import glob
 import os
 import re
-from typing import Any, Callable, Optional
+from collections.abc import Callable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -64,7 +65,7 @@ class InriaAerialImageLabeling(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new InriaAerialImageLabeling Dataset instance.
@@ -200,7 +201,7 @@ class InriaAerialImageLabeling(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/l7irish.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -97,11 +97,11 @@ class L7Irish(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = CRS.from_epsg(3857),
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = CRS.from_epsg(3857),
+        res: float | None = None,
         bands: Sequence[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -221,7 +221,7 @@ class L7Irish(RasterDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/l8biome.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -96,11 +96,11 @@ class L8Biome(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]],
-        crs: Optional[CRS] = CRS.from_epsg(3857),
-        res: Optional[float] = None,
+        paths: str | Iterable[str],
+        crs: CRS | None = CRS.from_epsg(3857),
+        res: float | None = None,
         bands: Sequence[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -217,7 +217,7 @@ class L8Biome(RasterDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/landcoverai.py

@@ -6,8 +6,9 @@ import abc
 import glob
 import hashlib
 import os
+from collections.abc import Callable
 from functools import lru_cache
-from typing import Any, Callable, Optional, cast
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -152,7 +153,7 @@ class LandCoverAIBase(Dataset[dict[str, Any]], abc.ABC):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -209,9 +210,9 @@ class LandCoverAIGeo(LandCoverAIBase, RasterDataset):
     def __init__(
         self,
         root: str = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        crs: CRS | None = None,
+        res: float | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -299,7 +300,7 @@ class LandCoverAI(LandCoverAIBase, NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:

torchgeo/datasets/landsat.py

@@ -4,8 +4,8 @@
 """Landsat datasets."""
 
 import abc
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -59,11 +59,11 @@ class Landsat(RasterDataset, abc.ABC):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
-        bands: Optional[Sequence[str]] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
+        bands: Sequence[str] | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new Dataset instance.
@@ -94,7 +94,7 @@ class Landsat(RasterDataset, abc.ABC):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/levircd.py

@@ -6,7 +6,7 @@
 import abc
 import glob
 import os
-from typing import Callable, Optional, Union
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -29,14 +29,14 @@ class LEVIRCDBase(NonGeoDataset, abc.ABC):
     .. versionadded:: 0.6
     """
 
-    splits: Union[list[str], dict[str, dict[str, str]]]
+    splits: list[str] | dict[str, dict[str, str]]
     directories = ["A", "B", "label"]
 
     def __init__(
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -135,7 +135,7 @@ class LEVIRCDBase(NonGeoDataset, abc.ABC):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/loveda.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -93,7 +93,7 @@ class LoveDA(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         scene: list[str] = ["urban", "rural"],
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -256,7 +256,7 @@ class LoveDA(NonGeoDataset):
             md5=self.md5 if self.checksum else None,
         )
 
-    def plot(self, sample: dict[str, Tensor], suptitle: Optional[str] = None) -> Figure:
+    def plot(self, sample: dict[str, Tensor], suptitle: str | None = None) -> Figure:
         """Plot a sample from the dataset.
 
         Args:

torchgeo/datasets/mapinwild.py

@@ -6,7 +6,7 @@
 import os
 import shutil
 from collections import defaultdict
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -111,7 +111,7 @@ class MapInWild(NonGeoDataset):
         root: str = "data",
         modality: list[str] = ["mask", "esa_wc", "viirs", "s2_summer"],
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -223,7 +223,7 @@ class MapInWild(NonGeoDataset):
             tensor = torch.from_numpy(array).float()
             return tensor
 
-    def _verify(self, url: str, md5: Optional[str] = None) -> None:
+    def _verify(self, url: str, md5: str | None = None) -> None:
         """Verify the integrity of the dataset.
 
         Args:
@@ -258,7 +258,7 @@ class MapInWild(NonGeoDataset):
         if not url.endswith(".csv"):
             self._extract(url)
 
-    def _download(self, url: str, md5: Optional[str]) -> None:
+    def _download(self, url: str, md5: str | None) -> None:
         """Downloads a modality.
 
         Args:
@@ -330,7 +330,7 @@ class MapInWild(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/millionaid.py

@@ -4,7 +4,8 @@
 """Million-AID dataset."""
 import glob
 import os
-from typing import Any, Callable, Optional, cast
+from collections.abc import Callable
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -191,7 +192,7 @@ class MillionAID(NonGeoDataset):
         root: str = "data",
         task: str = "multi-class",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new MillionAID dataset instance.
@@ -332,7 +333,7 @@ class MillionAID(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/naip.py

@@ -3,7 +3,7 @@
 
 """National Agriculture Imagery Program (NAIP) dataset."""
 
-from typing import Any, Optional
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -52,7 +52,7 @@ class NAIP(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/nasa_marine_debris.py

@@ -4,7 +4,7 @@
 """NASA Marine Debris dataset."""
 
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -66,9 +66,9 @@ class NASAMarineDebris(NonGeoDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
         verbose: bool = False,
     ) -> None:
@@ -224,7 +224,7 @@ class NASAMarineDebris(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/nccm.py

@@ -3,8 +3,8 @@
 
 """Northeastern China Crop Map Dataset."""
 
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import torch
@@ -82,11 +82,11 @@ class NCCM(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         years: list[int] = [2019],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -170,7 +170,7 @@ class NCCM(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/nlcd.py

@@ -5,8 +5,8 @@
 
 import glob
 import os
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import torch
@@ -107,12 +107,12 @@ class NLCD(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         years: list[int] = [2019],
         classes: list[int] = list(cmap.keys()),
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -230,7 +230,7 @@ class NLCD(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/openbuildings.py

@@ -7,8 +7,8 @@ import glob
 import json
 import os
 import sys
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable
+from typing import Any, cast
 
 import fiona
 import fiona.transform
@@ -206,10 +206,10 @@ class OpenBuildings(VectorDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         res: float = 0.0001,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new Dataset instance.
@@ -413,7 +413,7 @@ class OpenBuildings(VectorDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/oscd.py

@@ -5,8 +5,7 @@
 
 import glob
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional, Union
+from collections.abc import Callable, Sequence
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -103,7 +102,7 @@ class OSCD(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         bands: Sequence[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -164,7 +163,7 @@ class OSCD(NonGeoDataset):
         """
         return len(self.files)
 
-    def _load_files(self) -> list[dict[str, Union[str, Sequence[str]]]]:
+    def _load_files(self) -> list[dict[str, str | Sequence[str]]]:
         regions = []
         labels_root = os.path.join(
             self.root,
@@ -284,7 +283,7 @@ class OSCD(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
         alpha: float = 0.5,
     ) -> Figure:
         """Plot a sample from the dataset.

torchgeo/datasets/pastis.py

@@ -4,8 +4,7 @@
 """PASTIS dataset."""
 
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional
+from collections.abc import Callable, Sequence
 
 import fiona
 import matplotlib.pyplot as plt
@@ -132,7 +131,7 @@ class PASTIS(NonGeoDataset):
         folds: Sequence[int] = (1, 2, 3, 4, 5),
         bands: str = "s2",
         mode: str = "semantic",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -347,7 +346,7 @@ class PASTIS(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/patternnet.py

@@ -4,7 +4,8 @@
 """PatternNet dataset."""
 
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -84,7 +85,7 @@ class PatternNet(NonGeoClassificationDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -145,7 +146,7 @@ class PatternNet(NonGeoClassificationDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/potsdam.py

@@ -4,7 +4,7 @@
 """Potsdam dataset."""
 
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -123,7 +123,7 @@ class Potsdam2D(NonGeoDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new Potsdam dataset instance.
@@ -240,7 +240,7 @@ class Potsdam2D(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
         alpha: float = 0.5,
     ) -> Figure:
         """Plot a sample from the dataset.

torchgeo/datasets/prisma.py

@@ -3,7 +3,7 @@
 
 """PRISMA datasets."""
 
-from typing import Any, Optional
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -81,7 +81,7 @@ class PRISMA(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/reforestree.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.patches as patches
 import matplotlib.pyplot as plt
@@ -69,7 +69,7 @@ class ReforesTree(NonGeoDataset):
     def __init__(
         self,
         root: str = "data",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -209,7 +209,7 @@ class ReforesTree(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/resisc45.py

@@ -4,7 +4,8 @@
 """RESISC45 dataset."""
 
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -112,7 +113,7 @@ class RESISC45(NonGeoClassificationDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -193,7 +194,7 @@ class RESISC45(NonGeoClassificationDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/rwanda_field_boundary.py

@@ -4,8 +4,7 @@
 """Rwanda Field Boundary Competition dataset."""
 
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional
+from collections.abc import Callable, Sequence
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -91,9 +90,9 @@ class RwandaFieldBoundary(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         bands: Sequence[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new RwandaFieldBoundary instance.
@@ -258,7 +257,7 @@ class RwandaFieldBoundary(NonGeoDataset):
         sample: dict[str, Tensor],
         show_titles: bool = True,
         time_step: int = 0,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/seasonet.py

@@ -6,7 +6,6 @@
 import os
 import random
 from collections.abc import Callable, Collection, Iterable
-from typing import Optional
 
 import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
@@ -219,7 +218,7 @@ class SeasoNet(NonGeoDataset):
         bands: Iterable[str] = all_bands,
         grids: Iterable[int] = [1, 2],
         concat_seasons: int = 1,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -405,7 +404,7 @@ class SeasoNet(NonGeoDataset):
         sample: dict[str, Tensor],
         show_titles: bool = True,
         show_legend: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/seco.py

@@ -5,7 +5,7 @@
 
 import os
 import random
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -79,7 +79,7 @@ class SeasonalContrastS2(NonGeoDataset):
         version: str = "100k",
         seasons: int = 1,
         bands: list[str] = rgb_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -231,7 +231,7 @@ class SeasonalContrastS2(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/sen12ms.py

@@ -4,8 +4,7 @@
 """SEN12MS dataset."""
 
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional
+from collections.abc import Callable, Sequence
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -173,7 +172,7 @@ class SEN12MS(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         bands: Sequence[str] = BAND_SETS["all"],
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SEN12MS dataset instance.
@@ -320,7 +319,7 @@ class SEN12MS(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/sentinel.py

@@ -3,8 +3,8 @@
 
 """Sentinel datasets."""
 
-from collections.abc import Iterable, Sequence
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any
 
 import matplotlib.pyplot as plt
 import torch
@@ -141,11 +141,11 @@ class Sentinel1(Sentinel):
 
     def __init__(
         self,
-        paths: Union[str, list[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | list[str] = "data",
+        crs: CRS | None = None,
         res: float = 10,
         bands: Sequence[str] = ["VV", "VH"],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new Dataset instance.
@@ -194,7 +194,7 @@ To create a dataset containing both, use:
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -297,11 +297,11 @@ class Sentinel2(Sentinel):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         res: float = 10,
-        bands: Optional[Sequence[str]] = None,
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        bands: Sequence[str] | None = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
     ) -> None:
         """Initialize a new Dataset instance.
@@ -333,7 +333,7 @@ class Sentinel2(Sentinel):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/skippd.py

@@ -4,7 +4,8 @@
 """SKy Images and Photovoltaic Power Dataset (SKIPP'D)."""
 
 import os
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -74,7 +75,7 @@ class SKIPPD(NonGeoDataset):
         root: str = "data",
         split: str = "trainval",
         task: str = "nowcast",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -133,7 +134,7 @@ class SKIPPD(NonGeoDataset):
 
         return num_datapoints
 
-    def __getitem__(self, index: int) -> dict[str, Union[str, Tensor]]:
+    def __getitem__(self, index: int) -> dict[str, str | Tensor]:
         """Return an index within the dataset.
 
         Args:
@@ -142,7 +143,7 @@ class SKIPPD(NonGeoDataset):
         Returns:
             data and label at that index
         """
-        sample: dict[str, Union[str, Tensor]] = {"image": self._load_image(index)}
+        sample: dict[str, str | Tensor] = {"image": self._load_image(index)}
         sample.update(self._load_features(index))
 
         if self.transforms is not None:
@@ -176,7 +177,7 @@ class SKIPPD(NonGeoDataset):
         tensor = torch.from_numpy(arr).to(torch.float32)
         return tensor
 
-    def _load_features(self, index: int) -> dict[str, Union[str, Tensor]]:
+    def _load_features(self, index: int) -> dict[str, str | Tensor]:
         """Load label.
 
         Args:
@@ -195,7 +196,7 @@ class SKIPPD(NonGeoDataset):
         path = os.path.join(self.root, f"times_{self.split}_{self.task}.npy")
         datestring = np.load(path, allow_pickle=True)[index].strftime(self.dateformat)
 
-        features: dict[str, Union[str, Tensor]] = {
+        features: dict[str, str | Tensor] = {
             "label": torch.tensor(label, dtype=torch.float32),
             "date": datestring,
         }
@@ -241,7 +242,7 @@ class SKIPPD(NonGeoDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/so2sat.py

@@ -4,8 +4,8 @@
 """So2Sat dataset."""
 
 import os
-from collections.abc import Sequence
-from typing import Callable, Optional, cast
+from collections.abc import Callable, Sequence
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -196,7 +196,7 @@ class So2Sat(NonGeoDataset):
         version: str = "2",
         split: str = "train",
         bands: Sequence[str] = BAND_SETS["all"],
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new So2Sat dataset instance.
@@ -340,7 +340,7 @@ class So2Sat(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/south_africa_crop_type.py

@@ -5,8 +5,8 @@
 
 import os
 import re
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union, cast
+from collections.abc import Callable, Iterable
+from typing import Any, cast
 
 import matplotlib.pyplot as plt
 import torch
@@ -98,11 +98,11 @@ class SouthAfricaCropType(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
         classes: list[int] = list(cmap.keys()),
         bands: list[str] = all_bands,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
     ) -> None:
         """Initialize a new South Africa Crop Type dataset instance.
 
@@ -224,7 +224,7 @@ class SouthAfricaCropType(RasterDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/south_america_soybean.py

@@ -3,8 +3,8 @@
 
 """South America Soybean Dataset."""
 
-from collections.abc import Iterable
-from typing import Any, Callable, Optional, Union
+from collections.abc import Callable, Iterable
+from typing import Any
 
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
@@ -71,11 +71,11 @@ class SouthAmericaSoybean(RasterDataset):
 
     def __init__(
         self,
-        paths: Union[str, Iterable[str]] = "data",
-        crs: Optional[CRS] = None,
-        res: Optional[float] = None,
+        paths: str | Iterable[str] = "data",
+        crs: CRS | None = None,
+        res: float | None = None,
         years: list[int] = [2021],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         cache: bool = True,
         download: bool = False,
         checksum: bool = False,
@@ -133,7 +133,7 @@ class SouthAmericaSoybean(RasterDataset):
         self,
         sample: dict[str, Any],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/spacenet.py

@@ -9,7 +9,8 @@ import glob
 import math
 import os
 import re
-from typing import Any, Callable, Optional
+from collections.abc import Callable
+from typing import Any
 
 import fiona
 import matplotlib.pyplot as plt
@@ -81,9 +82,9 @@ class SpaceNet(NonGeoDataset, abc.ABC):
         root: str,
         image: str,
         collections: list[str] = [],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet Dataset instance.
@@ -274,7 +275,7 @@ class SpaceNet(NonGeoDataset, abc.ABC):
 
         return to_be_downloaded
 
-    def _download(self, collections: list[str], api_key: Optional[str] = None) -> None:
+    def _download(self, collections: list[str], api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -299,7 +300,7 @@ class SpaceNet(NonGeoDataset, abc.ABC):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -398,9 +399,9 @@ class SpaceNet1(SpaceNet):
         self,
         root: str = "data",
         image: str = "rgb",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 1 Dataset instance.
@@ -514,9 +515,9 @@ class SpaceNet2(SpaceNet):
         root: str = "data",
         image: str = "PS-RGB",
         collections: list[str] = [],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 2 Dataset instance.
@@ -633,11 +634,11 @@ class SpaceNet3(SpaceNet):
         self,
         root: str = "data",
         image: str = "PS-RGB",
-        speed_mask: Optional[bool] = False,
+        speed_mask: bool | None = False,
         collections: list[str] = [],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 3 Dataset instance.
@@ -733,7 +734,7 @@ class SpaceNet3(SpaceNet):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -884,9 +885,9 @@ class SpaceNet4(SpaceNet):
         root: str = "data",
         image: str = "PS-RGBNIR",
         angles: list[str] = [],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 4 Dataset instance.
@@ -1051,11 +1052,11 @@ class SpaceNet5(SpaceNet3):
         self,
         root: str = "data",
         image: str = "PS-RGB",
-        speed_mask: Optional[bool] = False,
+        speed_mask: bool | None = False,
         collections: list[str] = [],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 5 Dataset instance.
@@ -1183,9 +1184,9 @@ class SpaceNet6(SpaceNet):
         self,
         root: str = "data",
         image: str = "PS-RGB",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
     ) -> None:
         """Initialize a new SpaceNet 6 Dataset instance.
 
@@ -1212,7 +1213,7 @@ class SpaceNet6(SpaceNet):
 
         self.files = self._load_files(os.path.join(root, self.dataset_id))
 
-    def __download(self, api_key: Optional[str] = None) -> None:
+    def __download(self, api_key: str | None = None) -> None:
         """Download the dataset and extract it.
 
         Args:
@@ -1281,9 +1282,9 @@ class SpaceNet7(SpaceNet):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
-        api_key: Optional[str] = None,
+        api_key: str | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SpaceNet 7 Dataset instance.

torchgeo/datasets/splits.py

@@ -7,7 +7,7 @@ from collections.abc import Sequence
 from copy import deepcopy
 from itertools import accumulate
 from math import floor, isclose
-from typing import Optional, Union, cast
+from typing import cast
 
 from rtree.index import Index, Property
 from torch import Generator, default_generator, randint, randperm
@@ -50,7 +50,7 @@ def _fractions_to_lengths(fractions: Sequence[float], total: int) -> Sequence[in
 def random_bbox_assignment(
     dataset: GeoDataset,
     lengths: Sequence[float],
-    generator: Optional[Generator] = default_generator,
+    generator: Generator | None = default_generator,
 ) -> list[GeoDataset]:
     """Split a GeoDataset randomly assigning its index's BoundingBoxes.
 
@@ -104,7 +104,7 @@ def random_bbox_assignment(
 def random_bbox_splitting(
     dataset: GeoDataset,
     fractions: Sequence[float],
-    generator: Optional[Generator] = default_generator,
+    generator: Generator | None = default_generator,
 ) -> list[GeoDataset]:
     """Split a GeoDataset randomly splitting its index's BoundingBoxes.
 
@@ -172,7 +172,7 @@ def random_grid_cell_assignment(
     dataset: GeoDataset,
     fractions: Sequence[float],
     grid_size: int = 6,
-    generator: Optional[Generator] = default_generator,
+    generator: Generator | None = default_generator,
 ) -> list[GeoDataset]:
     """Overlays a grid over a GeoDataset and randomly assigns cells to new GeoDatasets.
 
@@ -289,7 +289,7 @@ def roi_split(dataset: GeoDataset, rois: Sequence[BoundingBox]) -> list[GeoDatas
 
 
 def time_series_split(
-    dataset: GeoDataset, lengths: Sequence[Union[float, tuple[float, float]]]
+    dataset: GeoDataset, lengths: Sequence[float | tuple[float, float]]
 ) -> list[GeoDataset]:
     """Split a GeoDataset on its time dimension to create non-overlapping GeoDatasets.
 

torchgeo/datasets/ssl4eo.py

@@ -6,7 +6,8 @@
 import glob
 import os
 import random
-from typing import Callable, Optional, TypedDict
+from collections.abc import Callable
+from typing import TypedDict
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -163,7 +164,7 @@ class SSL4EOL(NonGeoDataset):
         root: str = "data",
         split: str = "oli_sr",
         seasons: int = 1,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -285,7 +286,7 @@ class SSL4EOL(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 
@@ -405,7 +406,7 @@ class SSL4EOS12(NonGeoDataset):
         root: str = "data",
         split: str = "s2c",
         seasons: int = 1,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         checksum: bool = False,
     ) -> None:
         """Initialize a new SSL4EOS12 instance.
@@ -500,7 +501,7 @@ class SSL4EOS12(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/ssl4eo_benchmark.py

@@ -5,7 +5,7 @@
 
 import glob
 import os
-from typing import Callable, Optional
+from collections.abc import Callable
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -110,8 +110,8 @@ class SSL4EOLBenchmark(NonGeoDataset):
         sensor: str = "oli_sr",
         product: str = "cdl",
         split: str = "train",
-        classes: Optional[list[int]] = None,
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        classes: list[int] | None = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -327,7 +327,7 @@ class SSL4EOLBenchmark(NonGeoDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/sustainbench_crop_yield.py

@@ -4,7 +4,8 @@
 """SustainBench Crop Yield dataset."""
 
 import os
-from typing import Any, Callable, Optional
+from collections.abc import Callable
+from typing import Any
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -60,7 +61,7 @@ class SustainBenchCropYield(NonGeoDataset):
         root: str = "data",
         split: str = "train",
         countries: list[str] = ["usa"],
-        transforms: Optional[Callable[[dict[str, Any]], dict[str, Any]]] = None,
+        transforms: Callable[[dict[str, Any]], dict[str, Any]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -195,7 +196,7 @@ class SustainBenchCropYield(NonGeoDataset):
         sample: dict[str, Any],
         band_idx: int = 0,
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.
 

torchgeo/datasets/ucmerced.py

@@ -3,7 +3,8 @@
 
 """UC Merced dataset."""
 import os
-from typing import Callable, Optional, cast
+from collections.abc import Callable
+from typing import cast
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -85,7 +86,7 @@ class UCMerced(NonGeoClassificationDataset):
         self,
         root: str = "data",
         split: str = "train",
-        transforms: Optional[Callable[[dict[str, Tensor]], dict[str, Tensor]]] = None,
+        transforms: Callable[[dict[str, Tensor]], dict[str, Tensor]] | None = None,
         download: bool = False,
         checksum: bool = False,
     ) -> None:
@@ -190,7 +191,7 @@ class UCMerced(NonGeoClassificationDataset):
         self,
         sample: dict[str, Tensor],
         show_titles: bool = True,
-        suptitle: Optional[str] = None,
+        suptitle: str | None = None,
     ) -> Figure:
         """Plot a sample from the dataset.