Rename VisionDataset to NonGeoDataset (#627)

* Rename VisionDataset to NonGeoDataset

* Keep VisionDataset but add DeprecationWarning

* mypy fix

* More fixes

* More fixes

* cast types

* Undo cast

* Fix usage in test

* No idea why...

* Update more datasets

docs/api/datasets.rst

@@ -129,7 +129,7 @@ Sentinel
 Non-geospatial Datasets
 -----------------------
 
-:class:`VisionDataset` is designed for datasets that lack geospatial information. These datasets can still be combined using :class:`ConcatDataset <torch.utils.data.ConcatDataset>`.
+:class:`NonGeoDataset` is designed for datasets that lack geospatial information. These datasets can still be combined using :class:`ConcatDataset <torch.utils.data.ConcatDataset>`.
 
 .. csv-table:: C = classification,  R = regression, S = semantic segmentation, I = instance segmentation, T = time series, CD = change detection, OD = object detection
    :widths: 15 7 15 12 11 12 15 13
@@ -342,15 +342,15 @@ VectorDataset
 
 .. autoclass:: VectorDataset
 
-VisionDataset
+NonGeoDataset
 ^^^^^^^^^^^^^
 
-.. autoclass:: VisionDataset
+.. autoclass:: NonGeoDataset
 
-VisionClassificationDataset
+NonGeoClassificationDataset
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. autoclass:: VisionClassificationDataset
+.. autoclass:: NonGeoClassificationDataset
 
 IntersectionDataset
 ^^^^^^^^^^^^^^^^^^^

docs/api/samplers.rst

@@ -6,7 +6,7 @@ torchgeo.samplers
 Samplers
 --------
 
-Samplers are used to index a dataset, retrieving a single query at a time. For :class:`~torchgeo.datasets.VisionDataset`, dataset objects can be indexed with integers, and PyTorch's builtin samplers are sufficient. For :class:`~torchgeo.datasets.GeoDataset`, dataset objects require a bounding box for indexing. For this reason, we define our own :class:`GeoSampler` implementations below. These can be used like so:
+Samplers are used to index a dataset, retrieving a single query at a time. For :class:`~torchgeo.datasets.NonGeoDataset`, dataset objects can be indexed with integers, and PyTorch's builtin samplers are sufficient. For :class:`~torchgeo.datasets.GeoDataset`, dataset objects require a bounding box for indexing. For this reason, we define our own :class:`GeoSampler` implementations below. These can be used like so:
 
 .. code-block:: python
 

docs/user/contributing.rst

@@ -165,7 +165,7 @@ Datasets
 
 A major component of TorchGeo is the large collection of :mod:`torchgeo.datasets` that have been implemented. Adding new datasets to this list is a great way to contribute to the library. A brief checklist to follow when implementing a new dataset:
 
-* Implement the dataset extending either :class:`~torchgeo.datasets.GeoDataset` or :class:`~torchgeo.datasets.VisionDataset`
+* Implement the dataset extending either :class:`~torchgeo.datasets.GeoDataset` or :class:`~torchgeo.datasets.NonGeoDataset`
 * Add the dataset definition to ``torchgeo/datasets/__init__.py``
 * Add a ``data.py`` script to ``tests/data/<new dataset>/`` that generates test data with the same directory structure/file naming conventions as the new dataset
 * Add appropriate tests with 100% test coverage to ``tests/datasets/``

tests/data/README.md

@@ -46,9 +46,9 @@ rec = {"type": "Feature", "id": "0", "properties": OrderedDict(), "geometry": {"
 dst.write(rec)
 ```
 
-## VisionDataset
+## NonGeoDataset
 
-VisionDataset data can be created like so.
+NonGeoDataset data can be created like so.
 
 ### RGB images
 

tests/datasets/test_geo.py

@@ -18,6 +18,8 @@
     BoundingBox,
     GeoDataset,
     IntersectionDataset,
+    NonGeoClassificationDataset,
+    NonGeoDataset,
     RasterDataset,
     Sentinel2,
     UnionDataset,
@@ -47,6 +49,14 @@ class CustomVectorDataset(VectorDataset):
     filename_glob = "*.geojson"
 
 
+class CustomNonGeoDataset(NonGeoDataset):
+    def __getitem__(self, index: int) -> Dict[str, int]:
+        return {"index": index}
+
+    def __len__(self) -> int:
+        return 2
+
+
 class CustomVisionDataset(VisionDataset):
     def __getitem__(self, index: int) -> Dict[str, int]:
         return {"index": index}
@@ -137,8 +147,8 @@ def test_abstract(self) -> None:
         with pytest.raises(TypeError, match="Can't instantiate abstract class"):
             GeoDataset()  # type: ignore[abstract]
 
-    def test_and_vision(self, dataset: GeoDataset) -> None:
-        ds2 = CustomVisionDataset()
+    def test_and_nongeo(self, dataset: GeoDataset) -> None:
+        ds2 = CustomNonGeoDataset()
         with pytest.raises(
             ValueError, match="IntersectionDataset only supports GeoDatasets"
         ):
@@ -227,100 +237,116 @@ def test_no_data(self, tmp_path: Path) -> None:
             VectorDataset(str(tmp_path))
 
 
-class TestVisionDataset:
+class TestNonGeoDataset:
     @pytest.fixture(scope="class")
-    def dataset(self) -> VisionDataset:
-        return CustomVisionDataset()
+    def dataset(self) -> NonGeoDataset:
+        return CustomNonGeoDataset()
 
-    def test_getitem(self, dataset: VisionDataset) -> None:
+    def test_getitem(self, dataset: NonGeoDataset) -> None:
         assert dataset[0] == {"index": 0}
 
-    def test_len(self, dataset: VisionDataset) -> None:
+    def test_len(self, dataset: NonGeoDataset) -> None:
         assert len(dataset) == 2
 
     def test_add_two(self) -> None:
-        ds1 = CustomVisionDataset()
-        ds2 = CustomVisionDataset()
+        ds1 = CustomNonGeoDataset()
+        ds2 = CustomNonGeoDataset()
         dataset = ds1 + ds2
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 4
 
     def test_add_three(self) -> None:
-        ds1 = CustomVisionDataset()
-        ds2 = CustomVisionDataset()
-        ds3 = CustomVisionDataset()
+        ds1 = CustomNonGeoDataset()
+        ds2 = CustomNonGeoDataset()
+        ds3 = CustomNonGeoDataset()
         dataset = ds1 + ds2 + ds3
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 6
 
     def test_add_four(self) -> None:
-        ds1 = CustomVisionDataset()
-        ds2 = CustomVisionDataset()
-        ds3 = CustomVisionDataset()
-        ds4 = CustomVisionDataset()
+        ds1 = CustomNonGeoDataset()
+        ds2 = CustomNonGeoDataset()
+        ds3 = CustomNonGeoDataset()
+        ds4 = CustomNonGeoDataset()
         dataset = (ds1 + ds2) + (ds3 + ds4)
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 8
 
-    def test_str(self, dataset: VisionDataset) -> None:
-        assert "type: VisionDataset" in str(dataset)
+    def test_str(self, dataset: NonGeoDataset) -> None:
+        assert "type: NonGeoDataset" in str(dataset)
         assert "size: 2" in str(dataset)
 
     def test_abstract(self) -> None:
         with pytest.raises(TypeError, match="Can't instantiate abstract class"):
-            VisionDataset()  # type: ignore[abstract]
+            NonGeoDataset()  # type: ignore[abstract]
 
 
-class TestVisionClassificationDataset:
+class TestVisionDataset:
+    def test_deprecation(self) -> None:
+        match = "VisionDataset is deprecated, use NonGeoDataset instead."
+        with pytest.warns(DeprecationWarning, match=match):
+            CustomVisionDataset()
+
+
+class TestNonGeoClassificationDataset:
     @pytest.fixture(scope="class")
-    def dataset(self, root: str) -> VisionClassificationDataset:
+    def dataset(self, root: str) -> NonGeoClassificationDataset:
         transforms = nn.Identity()
-        return VisionClassificationDataset(root, transforms=transforms)
+        return NonGeoClassificationDataset(root, transforms=transforms)
 
     @pytest.fixture(scope="class")
     def root(self) -> str:
-        root = os.path.join("tests", "data", "visionclassificationdataset")
+        root = os.path.join("tests", "data", "nongeoclassification")
         return root
 
-    def test_getitem(self, dataset: VisionClassificationDataset) -> None:
+    def test_getitem(self, dataset: NonGeoClassificationDataset) -> None:
         x = dataset[0]
         assert isinstance(x, dict)
         assert isinstance(x["image"], torch.Tensor)
         assert isinstance(x["label"], torch.Tensor)
         assert x["image"].shape[0] == 3
 
-    def test_len(self, dataset: VisionClassificationDataset) -> None:
+    def test_len(self, dataset: NonGeoClassificationDataset) -> None:
         assert len(dataset) == 2
 
     def test_add_two(self, root: str) -> None:
-        ds1 = VisionClassificationDataset(root)
-        ds2 = VisionClassificationDataset(root)
+        ds1 = NonGeoClassificationDataset(root)
+        ds2 = NonGeoClassificationDataset(root)
         dataset = ds1 + ds2
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 4
 
     def test_add_three(self, root: str) -> None:
-        ds1 = VisionClassificationDataset(root)
-        ds2 = VisionClassificationDataset(root)
-        ds3 = VisionClassificationDataset(root)
+        ds1 = NonGeoClassificationDataset(root)
+        ds2 = NonGeoClassificationDataset(root)
+        ds3 = NonGeoClassificationDataset(root)
         dataset = ds1 + ds2 + ds3
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 6
 
     def test_add_four(self, root: str) -> None:
-        ds1 = VisionClassificationDataset(root)
-        ds2 = VisionClassificationDataset(root)
-        ds3 = VisionClassificationDataset(root)
-        ds4 = VisionClassificationDataset(root)
+        ds1 = NonGeoClassificationDataset(root)
+        ds2 = NonGeoClassificationDataset(root)
+        ds3 = NonGeoClassificationDataset(root)
+        ds4 = NonGeoClassificationDataset(root)
         dataset = (ds1 + ds2) + (ds3 + ds4)
         assert isinstance(dataset, ConcatDataset)
         assert len(dataset) == 8
 
-    def test_str(self, dataset: VisionClassificationDataset) -> None:
-        assert "type: VisionDataset" in str(dataset)
+    def test_str(self, dataset: NonGeoClassificationDataset) -> None:
+        assert "type: NonGeoDataset" in str(dataset)
         assert "size: 2" in str(dataset)
 
 
+class TestVisionClassificationDataset:
+    def test_deprecation(self) -> None:
+        root = os.path.join("tests", "data", "nongeoclassification")
+        match = "VisionClassificationDataset is deprecated, "
+        match += "use NonGeoClassificationDataset instead."
+        with pytest.warns(DeprecationWarning, match=match):
+            VisionClassificationDataset(root)
+
+
 class TestIntersectionDataset:
     @pytest.fixture(scope="class")
     def dataset(self) -> IntersectionDataset:
@@ -341,9 +367,9 @@ def test_str(self, dataset: IntersectionDataset) -> None:
         assert "bbox: BoundingBox" in out
         assert "size: 1" in out
 
-    def test_vision_dataset(self) -> None:
-        ds1 = CustomVisionDataset()
-        ds2 = CustomVisionDataset()
+    def test_nongeo_dataset(self) -> None:
+        ds1 = CustomNonGeoDataset()
+        ds2 = CustomNonGeoDataset()
         with pytest.raises(
             ValueError, match="IntersectionDataset only supports GeoDatasets"
         ):
@@ -395,9 +421,9 @@ def test_str(self, dataset: UnionDataset) -> None:
         assert "bbox: BoundingBox" in out
         assert "size: 2" in out
 
-    def test_vision_dataset(self) -> None:
-        ds1 = CustomVisionDataset()
-        ds2 = CustomVisionDataset()
+    def test_nongeo_dataset(self) -> None:
+        ds1 = CustomNonGeoDataset()
+        ds2 = CustomNonGeoDataset()
         with pytest.raises(ValueError, match="UnionDataset only supports GeoDatasets"):
             UnionDataset(ds1, ds2)  # type: ignore[arg-type]
 

torchgeo/datamodules/__init__.py

@@ -30,7 +30,7 @@
     # GeoDataset
     "ChesapeakeCVPRDataModule",
     "NAIPChesapeakeDataModule",
-    # VisionDataset
+    # NonGeoDataset
     "BigEarthNetDataModule",
     "COWCCountingDataModule",
     "DeepGlobeLandCoverDataModule",

torchgeo/datamodules/utils.py

@@ -7,11 +7,11 @@
 
 from torch.utils.data import Subset, TensorDataset, random_split
 
-from ..datasets import VisionDataset
+from ..datasets import NonGeoDataset
 
 
 def dataset_split(
-    dataset: Union[TensorDataset, VisionDataset],
+    dataset: Union[TensorDataset, NonGeoDataset],
     val_pct: float,
     test_pct: Optional[float] = None,
 ) -> List[Subset[Any]]:

torchgeo/datasets/__init__.py

@@ -41,6 +41,8 @@
 from .geo import (
     GeoDataset,
     IntersectionDataset,
+    NonGeoClassificationDataset,
+    NonGeoDataset,
     RasterDataset,
     UnionDataset,
     VectorDataset,
@@ -143,7 +145,7 @@
     "OpenBuildings",
     "Sentinel",
     "Sentinel2",
-    # VisionDataset
+    # NonGeoDataset
     "ADVANCE",
     "BeninSmallHolderCashews",
     "BigEarthNet",
@@ -191,11 +193,13 @@
     # Base classes
     "GeoDataset",
     "IntersectionDataset",
+    "NonGeoClassificationDataset",
+    "NonGeoDataset",
     "RasterDataset",
     "UnionDataset",
     "VectorDataset",
-    "VisionDataset",
     "VisionClassificationDataset",
+    "VisionDataset",
     # Utilities
     "BoundingBox",
     "concat_samples",

torchgeo/datasets/advance.py

@@ -13,11 +13,11 @@
 from PIL import Image
 from torch import Tensor
 
-from .geo import VisionDataset
+from .geo import NonGeoDataset
 from .utils import download_and_extract_archive
 
 
-class ADVANCE(VisionDataset):
+class ADVANCE(NonGeoDataset):
     """ADVANCE dataset.
 
     The `ADVANCE <https://akchen.github.io/ADVANCE-DATASET/>`__

torchgeo/datasets/benin_cashews.py

@@ -16,12 +16,12 @@
 from rasterio.crs import CRS
 from torch import Tensor
 
-from .geo import VisionDataset
+from .geo import NonGeoDataset
 from .utils import check_integrity, download_radiant_mlhub_dataset, extract_archive
 
 
 # TODO: read geospatial information from stac.json files
-class BeninSmallHolderCashews(VisionDataset):
+class BeninSmallHolderCashews(NonGeoDataset):
     r"""Smallholder Cashew Plantations in Benin dataset.
 
     This dataset contains labels for cashew plantations in a 120 km\ :sup:`2`\  area

torchgeo/datasets/bigearthnet.py

@@ -15,11 +15,11 @@
 from rasterio.enums import Resampling
 from torch import Tensor
 
-from .geo import VisionDataset
+from .geo import NonGeoDataset
 from .utils import download_url, extract_archive, sort_sentinel2_bands
 
 
-class BigEarthNet(VisionDataset):
+class BigEarthNet(NonGeoDataset):
     """BigEarthNet dataset.
 
     The `BigEarthNet <https://bigearth.net/>`__

torchgeo/datasets/cowc.py

@@ -14,11 +14,11 @@
 from PIL import Image
 from torch import Tensor
 
-from .geo import VisionDataset
+from .geo import NonGeoDataset
 from .utils import check_integrity, download_and_extract_archive
 
 
-class COWC(VisionDataset, abc.ABC):
+class COWC(NonGeoDataset, abc.ABC):
     """Abstract base class for the COWC dataset.
 
     The `Cars Overhead With Context (COWC) <https://gdo152.llnl.gov/cowc/>`_ data set