Update dependencies

.github/workflows/changelog.yml

@@ -11,6 +11,6 @@ jobs:
     name: Check Changelog Action
     runs-on: ubuntu-latest
     steps:
-      - uses: tarides/changelog-check-action@v2
+      - uses: tarides/changelog-check-action@v4
         with:
           changelog: CHANGELOG.md

.github/workflows/dependapot-review.yml

@@ -9,6 +9,6 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: 'Checkout Repository'
-        uses: actions/checkout@v4
+        uses: actions/checkout@v7
       - name: 'Dependency Review'
         uses: actions/dependency-review-action@v4

.github/workflows/joss-draft-pdf.yml

@@ -6,15 +6,15 @@ jobs:
     name: Paper Draft
     steps:
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v7
       - name: Build draft PDF
         uses: openjournals/openjournals-draft-action@master
         with:
           journal: joss
           # This should be the path to the paper within your repo.
           paper-path: paper/paper.md
       - name: Upload
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v7
         with:
           name: paper
           # This is the output path where Pandoc will write the compiled

.github/workflows/mr_ci.yml

@@ -21,12 +21,12 @@ jobs:
 
     runs-on: ${{ matrix.os }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v7
         with:
           fetch-depth: 2
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v7
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/mr_ci_text_spotting.yml

@@ -25,7 +25,7 @@ jobs:
 
     runs-on: ${{ matrix.os }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v7
         with:
           fetch-depth: 2
 
@@ -40,7 +40,7 @@ jobs:
           df -h
 
       - name: Set up Python 3.11
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v7
         with:
           python-version: 3.11
 
@@ -57,7 +57,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --no-cache-dir wheel
-          python -m pip install --no-cache-dir numpy==1.26.4 torch==2.2.2 torchvision==0.17.2 -f https://download.pytorch.org/whl/torch_stable.html
+          python -m pip install --no-cache-dir numpy==1.26.4 torch==2.12.0 torchvision==0.27.0 -f https://download.pytorch.org/whl/torch_stable.html
           python -m pip install --no-cache-dir ".[dev]"
           python -m pip install --no-cache-dir pytest-cov
           python -m pip install --no-cache-dir --no-build-isolation 'git+https://github.com/facebookresearch/detectron2.git'
@@ -79,10 +79,10 @@ jobs:
 
       - name: Hugging Face CLI
         run: |
-          pip install -U "huggingface-hub[cli]>=0.30.0,<0.34.0"
-          huggingface-cli download rwood-97/DPText_DETR_ArT_R_50_poly art_final.pth --local-dir .
-          huggingface-cli download rwood-97/DeepSolo_ic15_res50 ic15_res50_finetune_synth-tt-mlt-13-15-textocr.pth --local-dir .
-          huggingface-cli download rwood-97/MapTextPipeline_rumsey rumsey-finetune.pth --local-dir .
+          pip install -U "huggingface-hub[cli]>=0.34.0,<1.0.0"
+          hf download rwood-97/DPText_DETR_ArT_R_50_poly art_final.pth --local-dir .
+          hf download rwood-97/DeepSolo_ic15_res50 ic15_res50_finetune_synth-tt-mlt-13-15-textocr.pth --local-dir .
+          hf download rwood-97/MapTextPipeline_rumsey rumsey-finetune.pth --local-dir .
 
       - name: Test with pytest
         run: |

.github/workflows/mr_pip_ci.yml

@@ -19,12 +19,12 @@ jobs:
 
     runs-on: ${{ matrix.os }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v7
         with:
           fetch-depth: 2
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v7
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/publish-to-conda-forge.yml

@@ -26,13 +26,13 @@ jobs:
       run:
         shell: bash -l {0}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v7
         with:
           # Fetch all history so that versioneer can determine the version number
           fetch-depth: 0
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v7
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/publish-to-pypi.yml

@@ -15,11 +15,11 @@ jobs:
     name: Publish Tagged Python 🐍 distributions 📦 to PyPI
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v7
       with:
         fetch-depth: 0
     - name: Set up Python 3.11
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v7
       with:
         python-version: '3.11'
     - name: Install dependencies

.github/workflows/publish-to-test-pypi.yml

@@ -13,11 +13,11 @@ jobs:
     name: Publish all Python 🐍 distributions 📦 to Test PyPI
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v7
       with:
         fetch-depth: 0
     - name: Set up Python 3.11
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v7
       with:
         python-version: '3.11'
     - name: Install dependencies

CHANGELOG.md

@@ -17,6 +17,8 @@ _Add new changes here_
 ### Fixed
 
 - Fixes the `model_summary` method in the `ClassifierContainer` class ([#574](https://github.com/maps-as-data/MapReader/pull/574))
+- Update `AutoFeaturExtractor` to `AutoImageProcessor` to match updated transformers library ([#581](https://github.com/maps-as-data/MapReader/pull/581))
+- Update dependencies ([#581](https://github.com/maps-as-data/MapReader/pull/581))
 
 ## [v1.8.2](https://github.com/Living-with-machines/MapReader/releases/tag/v1.8.2) (2025-12-19)
 

mapreader/annotate/annotator.py

@@ -477,7 +477,7 @@ def _get_queue(
         """
 
         def check_eligibility(row):
-            if row.label not in [np.NaN, None]:
+            if row.label not in [np.nan, None]:
                 return False
 
             if self._filter_for is None:
@@ -546,7 +546,7 @@ def get_square(image_path, dim=True, border=False):
 
             # Dim the image
             if dim in ["True", True]:
-                im_array = np.array(im)
+                im_array = np.array(im, dtype=np.float32)
                 im_array = 256 - (256 - im_array) * 0.4  # lighten image
                 im = Image.fromarray(im_array.astype(np.uint8))
 

mapreader/classify/classifier.py

@@ -1770,7 +1770,7 @@ def load(
         par_name = os.path.dirname(load_path)
         base_name = os.path.basename(load_path)
         path2model = os.path.join(par_name, f"model_{base_name}")
-        self.model = torch.load(path2model, map_location=mydevice)
+        self.model = torch.load(path2model, map_location=mydevice, weights_only=False)
 
         try:
             self.device = mydevice

mapreader/classify/load_annotations.py

@@ -869,7 +869,7 @@ def _define_sampler(self):
             value_counts = (
                 datasets["train"].patch_df[self.label_col].value_counts().to_list()
             )
-            weights = np.reciprocal(Tensor(value_counts))
+            weights = Tensor(value_counts).reciprocal()
             weights = weights.double()
             sampler = WeightedRandomSampler(
                 weights[datasets["train"].patch_df["label_index"].tolist()],

mapreader/download/sheet_downloader.py

@@ -170,7 +170,7 @@ def get_merged_polygon(self) -> None:
         """
         Creates a multipolygon representing all maps in metadata.
         """
-        self.merged_polygon = self.metadata["geometry"].unary_union
+        self.merged_polygon = self.metadata["geometry"].union_all()
 
     def get_minmax_latlon(self) -> None:
         """

mapreader/load/images.py

@@ -897,7 +897,7 @@ def _infer_parent_coords_from_patches_id(
                 self._add_patch_coords_id(patch_id, verbose)
 
         if isinstance(patch_df, gpd.GeoDataFrame):
-            parent_polygon = patch_df.unary_union
+            parent_polygon = patch_df.union_all()
             parent_coords = parent_polygon.bounds
 
             self.parents[image_id]["coordinates"] = parent_coords

mapreader/process/occlusion_analysis.py

@@ -110,7 +110,7 @@ def __len__(self):
         return len(self.patch_df)
 
     def _load_model(self, model_path: str) -> nn.Module:
-        model = torch.load(model_path, map_location=self.device)
+        model = torch.load(model_path, map_location=self.device, weights_only=False)
         return model
 
     def add_loss_fn(
@@ -284,7 +284,7 @@ def _generate_area_importance_heatmap_with_occlusions(
                 # preprocess the occluded image and get the prediction
                 image_tensor = self._preprocess_image(occluded_image)
                 prediction = self.model(image_tensor)
-                loss = round(float(self.loss_fn(prediction, gt_prediction)), 4)
+                loss = round(float(self.loss_fn(prediction, gt_prediction).detach()), 4)
 
                 # store the loss in the heatmap
                 heatmap[row, column] = loss

setup.py

@@ -29,50 +29,50 @@
     python_requires=">=3.9",
     install_requires=[
         "matplotlib>=3.5.0,<4.0.0",
-        "numpy>=1.21.5,<2.0.0",
-        "pandas>=2.0.0",
+        "numpy>=1.21.5,<3.0.0",
+        "pandas>=2.0.0,<3.0.0",
         "pyproj>=3.2.0,<4.0.0",
         "azure-storage-blob>=12.9.0,<13.0.0",
         "aiohttp>=3.8.1,<4.0.0",
         "Shapely>=2.0.0,<3.0.0",
         "nest-asyncio>=1.5.1,<2.0.0",
         "scikit-image>=0.18.3",
         "scikit-learn>=1.0.1,<2.0.0",
-        "torch>=1.10.0,<=2.2.2",
-        "torchvision>=0.11.1,<=0.17.2",
+        "torch>=1.10.0,<=2.12.0",
+        "torchvision>=0.11.1,<=0.27.0",
         "jupyter>=1.0.0,<2.0.0",
-        "ipykernel>=6.5.1,<7.0.0",
+        "ipykernel>=6.5.1,<8.0.0",
         "ipywidgets>=8.0.0,<9.0.0",
         "ipyannotate==0.1.0-beta.0",
-        "Cython>=0.29.24,<0.30.0",
+        "Cython>=0.29.24,<4.0.0",
         "PyYAML>=6.0,<7.0",
         "tensorboard>=2.7.0,<3.0.0",
         "parhugin>=0.0.3,<0.0.4",
-        "geopy==2.1.0",
+        "geopy>=2.1.0,<3.0.0",
         "rasterio>=1.2.10,<2.0.0",
         "simplekml>=1.3.6,<2.0.0",
         "versioneer>=0.28",
         "tqdm<5.0.0",
         "torchinfo<2.0.0",
         "openpyxl>=3.1.2,<4.0.0",
-        "geopandas<1.0.0",
+        "geopandas>=1.0.0,<2.0.0",
         "pyogrio>=0.7.2",
         "cartopy>=0.22.0",
         "joblib>=1.4.0",
         "opencv-python>=4.8.1.78,<5.0.0.0",
         "folium>=0.12,<1.0.0",
         "mapclassify>=2.0.0,<3.0.0",
-        "xyzservices==2024.9.0",
+        "xyzservices>=2024.9.0",
         "piffle>=0.7.0",
         "lxml",
     ],
     extras_require={
         "dev": [
-            "pytest<9.0.0",
-            "pytest-cov>=4.1.0,<6.0.0",
-            "timm<1.0.0",
-            "transformers<4.51.3, !=4.50.0",
-            "black>=23.7.0,<25.0.0",
+            "pytest<10.0.0",
+            "pytest-cov>=4.1.0,<8.0.0",
+            "timm<2.0.0",
+            "transformers>=4.26.0,<5.0.0,!=4.50.0",
+            "black>=23.7.0,<27.0.0",
             "flake8>=6.0.0,<8.0.0",
         ],
     },

tests/test_classify/test_classifier.py

@@ -10,7 +10,7 @@
 import torch
 import transformers
 from torchvision import models
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from transformers import AutoImageProcessor, AutoModelForImageClassification
 
 from mapreader import AnnotationsLoader, ClassifierContainer
 from mapreader.classify.datasets import PatchDataset
@@ -22,7 +22,6 @@ def sample_dir():
 
 
 @pytest.fixture
-@pytest.mark.dependency(depends=["load_annots_csv", "dataloaders"], scope="session")
 def inputs(sample_dir):
     annots = AnnotationsLoader()
     annots.load(
@@ -110,7 +109,7 @@ def test_init_resnet18_torch(inputs):
 
 def test_init_resnet18_pickle(inputs, sample_dir):
     annots, dataloaders = inputs
-    my_model = torch.load(f"{sample_dir}/model_test.pkl")
+    my_model = torch.load(f"{sample_dir}/model_test.pkl", weights_only=False)
     assert isinstance(my_model, models.ResNet)  # sanity check
     classifier = ClassifierContainer(
         my_model, labels_map=annots.labels_map, dataloaders=dataloaders
@@ -128,7 +127,7 @@ def test_init_resnet18_pickle(inputs, sample_dir):
 @pytest.mark.dependency(name="hf_models", scope="session")
 def test_init_resnet18_hf(inputs):
     annots, dataloaders = inputs
-    AutoFeatureExtractor.from_pretrained("microsoft/resnet-18")
+    AutoImageProcessor.from_pretrained("microsoft/resnet-18")
     my_model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-18")
     model_type = transformers.models.resnet.ResNetForImageClassification
     assert isinstance(my_model, model_type)  # sanity check
@@ -387,7 +386,7 @@ def test_infer_models_by_string(inputs, infer_inputs):
 @pytest.mark.dependency(depends=["hf_models"], scope="session")
 def test_infer_hf_models(inputs, infer_inputs):
     annots, dataloaders = inputs
-    AutoFeatureExtractor.from_pretrained("microsoft/resnet-18")
+    AutoImageProcessor.from_pretrained("microsoft/resnet-18")
     my_model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-18")
     classifier = ClassifierContainer(
         my_model, labels_map=annots.labels_map, dataloaders=dataloaders