Add Landsat tests

tests/datasets/test_landsat.py

@@ -0,0 +1,40 @@
+import os
+from pathlib import Path
+
+import pytest
+import torch
+from rasterio.crs import CRS
+
+from torchgeo.datasets import BoundingBox, Landsat8, ZipDataset
+from torchgeo.transforms import Identity
+
+
+class TestLandsat8:
+    @pytest.fixture
+    def dataset(self) -> Landsat8:
+        root = os.path.join("tests", "data")
+        bands = ["B4", "B3", "B2"]
+        transforms = Identity()
+        return Landsat8(root, bands=bands, transforms=transforms)
+
+    def test_getitem(self, dataset: Landsat8) -> None:
+        print(dataset.bounds.intersects(dataset.bounds))
+        x = dataset[dataset.bounds]
+        assert isinstance(x, dict)
+        assert isinstance(x["crs"], CRS)
+        assert isinstance(x["image"], torch.Tensor)
+
+    def test_add(self, dataset: Landsat8) -> None:
+        ds = dataset + dataset
+        assert isinstance(ds, ZipDataset)
+
+    def test_no_data(self, tmp_path: Path) -> None:
+        with pytest.raises(FileNotFoundError, match="No Landsat data was found in "):
+            Landsat8(str(tmp_path))
+
+    def test_invalid_query(self, dataset: Landsat8) -> None:
+        query = BoundingBox(0, 0, 0, 0, 0, 0)
+        with pytest.raises(
+            IndexError, match="query: .* is not within bounds of the index:"
+        ):
+            dataset[query]

torchgeo/datasets/landsat.py

@@ -58,6 +58,9 @@ class Landsat(GeoDataset, abc.ABC):
             bands: bands to return (defaults to all bands)
             transforms: a function/transform that takes input sample and its target as
                 entry and returns a transformed version
+
+        Raises:
+            FileNotFoundError: if no files are found in ``root``
         """
         self.root = root
         self.crs = crs
@@ -66,7 +69,8 @@ class Landsat(GeoDataset, abc.ABC):
 
         # Create an R-tree to index the dataset
         self.index = Index(interleaved=False, properties=Property(dimension=3))
-        fileglob = os.path.join(root, self.base_folder, f"**_{self.bands[0]}.TIF")
+        path = os.path.join(root, self.base_folder)
+        fileglob = os.path.join(path, f"**_{self.bands[0]}.TIF")
         for i, filename in enumerate(glob.iglob(fileglob)):
             # https://www.usgs.gov/faqs/what-naming-convention-landsat-collections-level-1-scenes
             # https://www.usgs.gov/faqs/what-naming-convention-landsat-collection-2-level-1-and-level-2-scenes
@@ -78,6 +82,9 @@ class Landsat(GeoDataset, abc.ABC):
             coords = (minx, maxx, miny, maxy, timestamp, timestamp)
             self.index.insert(i, coords, filename)
 
+        if "filename" not in locals():
+            raise FileNotFoundError(f"No Landsat data was found in '{path}'")
+
     def __getitem__(self, query: BoundingBox) -> Dict[str, Any]:
         """Retrieve image and metadata indexed by query.
 
@@ -113,11 +120,16 @@ class Landsat(GeoDataset, abc.ABC):
             data_list.append(image)
         image = np.concatenate(data_list)  # type: ignore[no-untyped-call]
         image = image.astype(np.int32)
-        return {
+        sample = {
             "image": torch.tensor(image),  # type: ignore[attr-defined]
             "crs": self.crs,
         }
 
+        if self.transforms is not None:
+            sample = self.transforms(sample)
+
+        return sample
+
 
 class Landsat8(Landsat):
     """Landsat 8-9 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS)."""