Add own plot method and data.py to CBF

tests/data/cbf/Alberta.geojson

@@ -1,7 +1 @@
-{
-"type": "FeatureCollection",
-"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
-"features": [
-{ "type": "Feature", "properties": { }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 0.0, 0.0 ], [ 0.0, 1.0 ], [ 1.0, 1.0 ], [ 1.0, 0.0 ], [ 0.0, 0.0 ] ] ] } }
-]
-}
+{"type": "FeatureCollection", "crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"}}, "features": [{"type": "Feature", "properties": {}, "geometry": {"type": "Polygon", "coordinates": [[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0], [1.0, 0.0], [0.0, 0.0]]]}}]}

tests/data/cbf/data.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import hashlib
+import json
+import os
+import shutil
+
+
+def create_geojson():
+    geojson = {
+        "type": "FeatureCollection",
+        "crs": {
+            "type": "name",
+            "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"},
+        },
+        "features": [
+            {
+                "type": "Feature",
+                "properties": {},
+                "geometry": {
+                    "type": "Polygon",
+                    "coordinates": [
+                        [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0], [1.0, 0.0], [0.0, 0.0]]
+                    ],
+                },
+            }
+        ],
+    }
+    return geojson
+
+
+if __name__ == "__main__":
+    filename = "Alberta.zip"
+    geojson = create_geojson()
+
+    with open(filename.replace(".zip", ".geojson"), "w") as f:
+        json.dump(geojson, f)
+
+    # compress single file directly with no directory
+    shutil.make_archive(
+        filename.replace(".zip", ""),
+        "zip",
+        os.getcwd(),
+        filename.replace(".zip", ".geojson"),
+    )
+
+    # Compute checksums
+    with open(filename, "rb") as f:
+        md5 = hashlib.md5(f.read()).hexdigest()
+        print(f"{filename}: {md5}")

tests/datasets/test_cbf.py

@@ -31,22 +31,12 @@ def dataset(
         self, monkeypatch: MonkeyPatch, tmp_path: Path
     ) -> CanadianBuildingFootprints:
         monkeypatch.setattr(torchgeo.datasets.utils, "download_url", download_url)
-        md5s = [
-            "8a4a0a57367f67c69608d1452e30df13",
-            "1829f4054a9a81bb23871ca797a3895c",
-            "4358a0076fd43e9a2f436e74348813b0",
-            "ae3726b1263727d72565ecacfed56fb8",
-            "6861876d3a3ca7e79b28c61ab5906de4",
-            "d289c9ea49801bb287ddbde1ea5f31ef",
-            "3a940288297631b4e6a365266bfb949a",
-            "6b43b3632b165ff79c1ca0c693a61398",
-            "36283e0b29088ec281e77c989cbee100",
-            "773da9d33e3766b7237a1d7db0811832",
-            "cc833a65137c8a046c8f45bb695092b1",
-            "067664d066c4152fb96a5c129cbabadf",
-            "474bc084bc41b124aa4919e7a37a9648",
-        ]
-        monkeypatch.setattr(CanadianBuildingFootprints, "md5s", md5s)
+        monkeypatch.setattr(
+            CanadianBuildingFootprints, "provinces_territories", ["Alberta"]
+        )
+        monkeypatch.setattr(
+            CanadianBuildingFootprints, "md5s", ["25091d1f051baa30d8f2026545cfb696"]
+        )
         url = os.path.join("tests", "data", "cbf") + os.sep
         monkeypatch.setattr(CanadianBuildingFootprints, "url", url)
         monkeypatch.setattr(plt, "show", lambda *args: None)
@@ -76,7 +66,13 @@ def test_already_downloaded(self, dataset: CanadianBuildingFootprints) -> None:
     def test_plot(self, dataset: CanadianBuildingFootprints) -> None:
         query = dataset.bounds
         x = dataset[query]
-        dataset.plot(x["mask"])
+        dataset.plot(x, suptitle="Test")
+
+    def test_plot_prediction(self, dataset: CanadianBuildingFootprints) -> None:
+        query = dataset.bounds
+        x = dataset[query]
+        x["prediction"] = x["mask"].clone()
+        dataset.plot(x, suptitle="Prediction")
 
     def test_not_downloaded(self, tmp_path: Path) -> None:
         with pytest.raises(RuntimeError, match="Dataset not found or corrupted."):

torchgeo/datasets/cbf.py

@@ -6,6 +6,7 @@
 import os
 from typing import Any, Callable, Dict, Optional
 
+import matplotlib.pyplot as plt
 from rasterio.crs import CRS
 
 from .geo import VectorDataset
@@ -120,3 +121,52 @@ def _download(self) -> None:
                 self.root,
                 md5=md5 if self.checksum else None,
             )
+
+    def plot(
+        self,
+        sample: Dict[str, Any],
+        show_titles: bool = True,
+        suptitle: Optional[str] = None,
+    ) -> plt.Figure:
+        """Plot a sample from the dataset.
+
+        Args:
+            sample: a sample returned by :meth:`VectorDataset.__getitem__`
+            show_titles: flag indicating whether to show titles above each panel
+            suptitle: optional string to use as a suptitle
+
+        Returns:
+            a matplotlib Figure with the rendered sample
+
+        .. versionchanged:: 0.3
+            Method now takes a sample dict, not a Tensor. Additionally, it is possible
+            to show subplot titles and/or use a custom suptitle.
+        """
+        image = sample["mask"].squeeze(0)
+        ncols = 1
+
+        showing_prediction = "prediction" in sample
+        if showing_prediction:
+            pred = sample["prediction"].squeeze(0)
+            ncols = 2
+
+        fig, axs = plt.subplots(nrows=1, ncols=ncols, figsize=(4, 4))
+
+        if showing_prediction:
+            axs[0].imshow(image)
+            axs[0].axis("off")
+            axs[1].imshow(pred)
+            axs[1].axis("off")
+            if show_titles:
+                axs[0].set_title("Mask")
+                axs[1].set_title("Prediction")
+        else:
+            axs.imshow(image)
+            axs.axis("off")
+            if show_titles:
+                axs.set_title("Mask")
+
+        if suptitle is not None:
+            plt.suptitle(suptitle)
+
+        return fig

torchgeo/datasets/geo.py

@@ -677,21 +677,6 @@ def __getitem__(self, query: BoundingBox) -> Dict[str, Any]:
 
         return sample
 
-    def plot(self, data: Tensor) -> None:
-        """Plot a data sample.
-
-        Args:
-            data: the data to plot
-        """
-        array = data.squeeze().numpy()
-
-        # Plot the image
-        ax = plt.axes()
-        ax.imshow(array)
-        ax.axis("off")
-        plt.show()
-        plt.close()
-
 
 class VisionDataset(Dataset[Dict[str, Any]], abc.ABC):
     """Abstract base class for datasets lacking geospatial information.

torchgeo/datasets/openbuildings.py

@@ -421,7 +421,7 @@ def _verify(self) -> None:
             "have manually downloaded the dataset as suggested in the documentation."
         )
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,