Merge branch 'main' into main

microsoft · Jan 22, 2025 · 99829ad · 99829ad
2 parents 63bbbd4 + ada5122
commit 99829ad
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diff --git a/.github/dependabot.yml b/.github/dependabot.yml
@@ -27,8 +27,6 @@ updates:
       # https://github.com/pytorch/pytorch_sphinx_theme/issues/175
       - dependency-name: 'sphinx'
         versions: '>=6'
-      # segmentation-models-pytorch pins timm, must update in unison
-      - dependency-name: 'timm'
   - package-ecosystem: 'npm'
     directory: '/'
     schedule:

diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml
@@ -34,8 +34,6 @@ jobs:
           path: ${{ env.pythonLocation }}
           key: ${{ runner.os }}-${{ runner.arch }}-Python-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('requirements/required.txt', 'requirements/datasets.txt', 'requirements/tests.txt') }}
         if: ${{ runner.os != 'macOS' }}
-      - name: Setup headless display for pyvista
-        uses: pyvista/setup-headless-display-action@v3
       - name: Install pip dependencies
         if: steps.cache.outputs.cache-hit != 'true'
         run: |
@@ -68,8 +66,6 @@ jobs:
         with:
           path: ${{ env.pythonLocation }}
           key: ${{ runner.os }}-${{ runner.arch }}-Python-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('requirements/min-reqs.old') }}
-      - name: Setup headless display for pyvista
-        uses: pyvista/setup-headless-display-action@v3
       - name: Install pip dependencies
         if: steps.cache.outputs.cache-hit != 'true'
         run: |

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -28,7 +28,6 @@ repos:
           - numpy>=1.22
           - pillow>=10.4.0
           - pytest>=6.1.2
-          - pyvista>=0.34.2
           - scikit-image>=0.22.0
           - torch>=2.3
           - torchmetrics>=0.10

diff --git a/docs/api/datasets/non_geo_datasets.csv b/docs/api/datasets/non_geo_datasets.csv
@@ -62,4 +62,4 @@ Dataset,Task,Source,License,# Samples,# Classes,Size (px),Resolution (m),Bands
 `VHR-10`_,I,"Google Earth, Vaihingen","MIT",800,10,"358--1,728",0.08--2,RGB
 `Western USA Live Fuel Moisture`_,R,"Landsat8, Sentinel-1","CC-BY-NC-ND-4.0",2615,-,-,-,-
 `xView2`_,CD,Maxar,"CC-BY-NC-SA-4.0","3,732",4,"1,024x1,024",0.8,RGB
-`ZueriCrop`_,"I, T",Sentinel-2,-,116K,48,24x24,10,MSI
+`ZueriCrop`_,"I, T",Sentinel-2,CC-BY-NC-4.0,116K,48,24x24,10,MSI
diff --git a/docs/conf.py b/docs/conf.py
@@ -115,7 +115,6 @@
     'numpy': ('https://numpy.org/doc/stable/', None),
     'python': ('https://docs.python.org/3', None),
     'lightning': ('https://lightning.ai/docs/pytorch/stable/', None),
-    'pyvista': ('https://docs.pyvista.org/version/stable/', None),
     'rasterio': ('https://rasterio.readthedocs.io/en/stable/', None),
     'rtree': ('https://rtree.readthedocs.io/en/stable/', None),
     'segmentation_models_pytorch': ('https://smp.readthedocs.io/en/stable/', None),

diff --git a/experiments/ssl4eo/flops.py b/experiments/ssl4eo/flops.py
@@ -17,7 +17,7 @@
 for model in models:
     print(f'Model: {model}')
 
-    m = timm.create_model(model, num_classes=num_classes, in_chans=in_channels)
+    m = timm.create_model(model, num_classes=num_classes, in_chans=in_channels)  # type: ignore[attr-defined]
 
     # Calculate memory requirements of model
     mem_params = sum([p.nelement() * p.element_size() for p in m.parameters()])

diff --git a/pyproject.toml b/pyproject.toml
@@ -93,8 +93,6 @@ datasets = [
     "pandas[parquet]>=2",
     # 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",
     # scikit-image 0.19+ required for Python 3.10 wheels
     "scikit-image>=0.19",
     # scipy 1.7.2+ required for Python 3.10 wheels

diff --git a/requirements/datasets.txt b/requirements/datasets.txt
@@ -1,9 +1,8 @@
 # datasets
 h5py==3.12.1
 laspy==2.5.4
-opencv-python==4.10.0.84
+opencv-python==4.11.0.86
 pandas[parquet]==2.2.3
 pycocotools==2.0.8
-pyvista==0.44.2
 scikit-image==0.25.0
 scipy==1.15.1
diff --git a/requirements/min-reqs.old b/requirements/min-reqs.old
@@ -27,10 +27,8 @@ laspy==2.0.0
 opencv-python==4.5.4.58
 pycocotools==2.0.7
 pyarrow==15.0.0  # Remove when we upgrade min version of pandas to `pandas[parquet]>=2`
-pyvista==0.34.2
 scikit-image==0.19.0
 scipy==1.7.2
-vtk==9.3.1  # PyVista is not yet compatible with VTK 9.4+
 
 # tests
 pytest==7.3.0

diff --git a/requirements/required.txt b/requirements/required.txt
@@ -5,18 +5,18 @@ setuptools==75.8.0
 einops==0.8.0
 fiona==1.10.1
 kornia==0.8.0
-lightly==1.5.16
+lightly==1.5.17
 lightning[pytorch-extra]==2.5.0.post0
 matplotlib==3.10.0
-numpy==2.2.1
+numpy==2.2.2
 pandas==2.2.3
 pillow==11.1.0
 pyproj==3.7.0
 rasterio==1.4.3
 rtree==1.3.0
-segmentation-models-pytorch==0.3.4
+segmentation-models-pytorch==0.4.0
 shapely==2.0.6
-timm==0.9.7
+timm==1.0.14
 torch==2.5.1
 torchmetrics==1.6.1
 torchvision==0.20.1
diff --git a/requirements/style.txt b/requirements/style.txt
@@ -1,3 +1,3 @@
 # style
 mypy==1.14.1
-ruff==0.9.1
+ruff==0.9.2
diff --git a/tests/datasets/test_idtrees.py b/tests/datasets/test_idtrees.py
@@ -95,11 +95,3 @@ def test_plot(self, dataset: IDTReeS) -> None:
             x['prediction_label'] = x['label']
             dataset.plot(x, show_titles=False)
             plt.close()
-
-    def test_plot_las(self, dataset: IDTReeS) -> None:
-        pyvista = pytest.importorskip('pyvista', minversion='0.34.2')
-        pyvista.OFF_SCREEN = True
-
-        # Test point cloud without colors
-        point_cloud = dataset.plot_las(index=0)
-        pyvista.plot(point_cloud, scalars=point_cloud.points, cpos='yz', cmap='viridis')
diff --git a/tests/datasets/test_zuericrop.py b/tests/datasets/test_zuericrop.py
@@ -18,17 +18,11 @@
 class TestZueriCrop:
     @pytest.fixture
     def dataset(self, monkeypatch: MonkeyPatch, tmp_path: Path) -> ZueriCrop:
-        data_dir = os.path.join('tests', 'data', 'zuericrop')
-        urls = [
-            os.path.join(data_dir, 'ZueriCrop.hdf5'),
-            os.path.join(data_dir, 'labels.csv'),
-        ]
-        md5s = ['1635231df67f3d25f4f1e62c98e221a4', '5118398c7a5bbc246f5f6bb35d8d529b']
-        monkeypatch.setattr(ZueriCrop, 'urls', urls)
-        monkeypatch.setattr(ZueriCrop, 'md5s', md5s)
+        url = os.path.join('tests', 'data', 'zuericrop') + os.sep
+        monkeypatch.setattr(ZueriCrop, 'url', url)
         root = tmp_path
         transforms = nn.Identity()
-        return ZueriCrop(root=root, transforms=transforms, download=True, checksum=True)
+        return ZueriCrop(root=root, transforms=transforms, download=True)
 
     def test_getitem(self, dataset: ZueriCrop) -> None:
         x = dataset[0]

diff --git a/tests/models/test_resnet.py b/tests/models/test_resnet.py
@@ -34,7 +34,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model('resnet18', in_chans=weights.meta['in_chans'])
+        model = timm.create_model('resnet18', in_chans=weights.meta['in_chans'])  # type: ignore[attr-defined]
         torch.save(model.state_dict(), path)
         try:
             monkeypatch.setattr(weights.value, 'url', str(path))
@@ -78,7 +78,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model('resnet50', in_chans=weights.meta['in_chans'])
+        model = timm.create_model('resnet50', in_chans=weights.meta['in_chans'])  # type: ignore[attr-defined]
         torch.save(model.state_dict(), path)
         try:
             monkeypatch.setattr(weights.value, 'url', str(path))
@@ -122,7 +122,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model('resnet152', in_chans=weights.meta['in_chans'])
+        model = timm.create_model('resnet152', in_chans=weights.meta['in_chans'])  # type: ignore[attr-defined]
         torch.save(model.state_dict(), path)
         try:
             monkeypatch.setattr(weights.value, 'url', str(path))

diff --git a/tests/models/test_vit.py b/tests/models/test_vit.py
@@ -27,7 +27,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_byol.py b/tests/trainers/test_byol.py
@@ -89,7 +89,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_classification.py b/tests/trainers/test_classification.py
@@ -126,7 +126,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_moco.py b/tests/trainers/test_moco.py
@@ -91,7 +91,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_regression.py b/tests/trainers/test_regression.py
@@ -115,7 +115,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)
@@ -273,7 +273,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_segmentation.py b/tests/trainers/test_segmentation.py
@@ -139,7 +139,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_simclr.py b/tests/trainers/test_simclr.py
@@ -89,7 +89,7 @@ def mocked_weights(
         load_state_dict_from_url: None,
     ) -> WeightsEnum:
         path = tmp_path / f'{weights}.pth'
-        model = timm.create_model(
+        model = timm.create_model(  # type: ignore[attr-defined]
             weights.meta['model'], in_chans=weights.meta['in_chans']
         )
         torch.save(model.state_dict(), path)

diff --git a/tests/trainers/test_utils.py b/tests/trainers/test_utils.py
@@ -34,7 +34,7 @@ def test_extract_backbone_unsupported_model(tmp_path: Path) -> None:
 
 
 def test_get_input_layer_name_and_module() -> None:
-    key, module = _get_input_layer_name_and_module(timm.create_model('resnet18'))
+    key, module = _get_input_layer_name_and_module(timm.create_model('resnet18'))  # type: ignore[attr-defined]
     assert key == 'conv1'
     assert isinstance(module, nn.Conv2d)
     assert module.in_channels == 3

diff --git a/torchgeo/datasets/idtrees.py b/torchgeo/datasets/idtrees.py
@@ -92,10 +92,9 @@ class IDTReeS(NonGeoDataset):
 
     * https://doi.org/10.1101/2021.08.06.453503
 
-    This dataset requires the following additional libraries to be installed:
+    This dataset requires the following additional library to be installed:
 
        * `laspy <https://pypi.org/project/laspy/>`_ to read lidar point clouds
-       * `pyvista <https://pypi.org/project/pyvista/>`_ to plot lidar point clouds
 
     .. versionadded:: 0.2
     """
@@ -552,36 +551,3 @@ def normalize(x: Tensor) -> Tensor:
             plt.suptitle(suptitle)
 
         return fig
-
-    def plot_las(self, index: int) -> 'pyvista.Plotter':  # type: ignore[name-defined] # noqa: F821
-        """Plot a sample point cloud at the index.
-
-        Args:
-            index: index to plot
-
-        Returns:
-            pyvista.PolyData object. Run pyvista.plot(point_cloud, ...) to display
-
-        Raises:
-            DependencyNotFoundError: If laspy or pyvista are not installed.
-
-        .. versionchanged:: 0.4
-           Ported from Open3D to PyVista, *colormap* parameter removed.
-        """
-        laspy = lazy_import('laspy')
-        pyvista = lazy_import('pyvista')
-        path = self.images[index]
-        path = path.replace('RGB', 'LAS').replace('.tif', '.las')
-        las = laspy.read(path)
-        points: np.typing.NDArray[np.int_] = np.stack(
-            [las.x, las.y, las.z], axis=0
-        ).transpose((1, 0))
-        point_cloud = pyvista.PolyData(points)
-
-        # Some point cloud files have no color->points mapping
-        if hasattr(las, 'red'):
-            colors = np.stack([las.red, las.green, las.blue], axis=0)
-            colors = colors.transpose((1, 0)) / np.iinfo(np.uint16).max
-            point_cloud['colors'] = colors
-
-        return point_cloud
diff --git a/torchgeo/datasets/satlas.py b/torchgeo/datasets/satlas.py
@@ -447,7 +447,7 @@ class _Task(TypedDict, total=False):
 class SatlasPretrain(NonGeoDataset):
     """SatlasPretrain dataset.
 
-    `SatlasPretrain <https://satlas-pretrain.allen.ai/>`_ is a large-scale pre-training
+    `SatlasPretrain <https://satlas-pretrain.allen.ai/>`__ is a large-scale pre-training
     dataset for tasks that involve understanding satellite images. Regularly-updated
     satellite data is publicly available for much of the Earth through sources such as
     Sentinel-2 and NAIP, and can inform numerous applications from tackling illegal

diff --git a/torchgeo/datasets/zuericrop.py b/torchgeo/datasets/zuericrop.py
@@ -52,10 +52,7 @@ class ZueriCrop(NonGeoDataset):
        * `h5py <https://pypi.org/project/h5py/>`_ to load the dataset
     """
 
-    urls = (
-        'https://polybox.ethz.ch/index.php/s/uXfdr2AcXE3QNB6/download',
-        'https://raw.githubusercontent.com/0zgur0/multi-stage-convSTAR-network/fa92b5b3cb77f5171c5c3be740cd6e6395cc29b6/labels.csv',
-    )
+    url = 'https://hf.co/datasets/torchgeo/zuericrop/resolve/8ac0f416fbaab032d8670cc55f984b9f079e86b2/'
     md5s = ('1635231df67f3d25f4f1e62c98e221a4', '5118398c7a5bbc246f5f6bb35d8d529b')
     filenames = ('ZueriCrop.hdf5', 'labels.csv')
 
@@ -221,11 +218,11 @@ def _verify(self) -> None:
 
     def _download(self) -> None:
         """Download the dataset."""
-        for url, filename, md5 in zip(self.urls, self.filenames, self.md5s):
+        for filename, md5 in zip(self.filenames, self.md5s):
             filepath = os.path.join(self.root, filename)
             if not os.path.exists(filepath):
                 download_url(
-                    url,
+                    self.url + filename,
                     self.root,
                     filename=filename,
                     md5=md5 if self.checksum else None,

diff --git a/torchgeo/models/resnet.py b/torchgeo/models/resnet.py
@@ -768,7 +768,7 @@ def resnet18(
     if weights:
         kwargs['in_chans'] = weights.meta['in_chans']
 
-    model: ResNet = timm.create_model('resnet18', *args, **kwargs)
+    model: ResNet = timm.create_model('resnet18', *args, **kwargs)  # type: ignore[attr-defined]
 
     if weights:
         missing_keys, unexpected_keys = model.load_state_dict(
@@ -803,7 +803,7 @@ def resnet50(
     if weights:
         kwargs['in_chans'] = weights.meta['in_chans']
 
-    model: ResNet = timm.create_model('resnet50', *args, **kwargs)
+    model: ResNet = timm.create_model('resnet50', *args, **kwargs)  # type: ignore[attr-defined]
 
     if weights:
         missing_keys, unexpected_keys = model.load_state_dict(
@@ -837,7 +837,7 @@ def resnet152(
     if weights:
         kwargs['in_chans'] = weights.meta['in_chans']
 
-    model: ResNet = timm.create_model('resnet152', *args, **kwargs)
+    model: ResNet = timm.create_model('resnet152', *args, **kwargs)  # type: ignore[attr-defined]
 
     if weights:
         missing_keys, unexpected_keys = model.load_state_dict(