Fix GH Actions tests

.github/workflows/Conda-app.yml

@@ -14,7 +14,6 @@ jobs:
       fail-fast: false
       matrix:
         python-version:
-          - "3.x"
           - "3.12"
           - "3.11"
           - "3.10"
@@ -33,21 +32,29 @@ jobs:
       - name: "Checkout code"
         uses: "actions/checkout@v4"
 
+      - name: Install opencv dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y libgl1-mesa-glx libegl1-mesa
+          sudo apt-get install -y python3-opencv
+
       - name: Install Conda environment with Micromamba
         uses: mamba-org/setup-micromamba@v1
         with:
           environment-name: DeepForest
           environment-file: environment.yml
-          extra-specs: "python=${{ matrix.python-version }}"
-          cache-env: true
+          create-args: "python=${{ matrix.python-version }}"
+          cache-environment: true
           cache-downloads: true
 
-      - name: Run pytest, test style, and notebooks
-        run: |
-          pip install -e .
-          pytest -v
-          yapf -d --recursive deepforest/ --style=.style.yapf
-          pytest --nbmake docs/*.ipynb
+      - name: Run pytest
+        run: pytest -v
+
+      - name: Check style
+        run: yapf -d --recursive deepforest/ --style=.style.yapf
+
+      - name: Check notebook build
+        run: pytest --nbmake docs/*.ipynb
 
       - name: Test Docs
         run: |

deepforest/models/FasterRCNN.py

@@ -13,7 +13,8 @@ def __init__(self, config, **kwargs):
 
     def load_backbone(self):
         """A torch vision retinanet model"""
-        backbone = torchvision.models.detection.fasterrcnn_resnet50_fpn(weights='FasterRCNN_ResNet50_FPN_Weights.COCO_V1')
+        backbone = torchvision.models.detection.fasterrcnn_resnet50_fpn(
+            weights='FasterRCNN_ResNet50_FPN_Weights.COCO_V1')
         return backbone
 
     def create_model(self, backbone=None):
@@ -24,7 +25,8 @@ def create_model(self, backbone=None):
             model: a pytorch nn module
         """
         # load Faster RCNN pre-trained model
-        model = torchvision.models.detection.fasterrcnn_resnet50_fpn(weights='FasterRCNN_ResNet50_FPN_Weights.COCO_V1')
+        model = torchvision.models.detection.fasterrcnn_resnet50_fpn(
+            weights='FasterRCNN_ResNet50_FPN_Weights.COCO_V1')
 
         # get the number of input features
         in_features = model.roi_heads.box_predictor.cls_score.in_features

deepforest/preprocess.py

@@ -78,15 +78,13 @@ def select_annotations(annotations, windows, index, allow_empty=False):
     offset = 40
     selected_annotations = annotations[(annotations.xmin > (window_xmin - offset)) &
                                        (annotations.xmin < (window_xmax)) &
-                                       (annotations.xmax >
-                                        (window_xmin)) & (annotations.ymin >
-                                                          (window_ymin - offset)) &
+                                       (annotations.xmax > (window_xmin)) &
+                                       (annotations.ymin > (window_ymin - offset)) &
                                        (annotations.xmax < (window_xmax + offset)) &
-                                       (annotations.ymin <
-                                        (window_ymax)) & (annotations.ymax >
-                                                          (window_ymin)) &
-                                       (annotations.ymax <
-                                        (window_ymax + offset))].copy(deep=True)
+                                       (annotations.ymin < (window_ymax)) &
+                                       (annotations.ymax > (window_ymin)) &
+                                       (annotations.ymax < (window_ymax + offset))].copy(
+                                           deep=True)
     # change the image name
     image_basename = os.path.splitext("{}".format(annotations.image_path.unique()[0]))[0]
     selected_annotations.image_path = "{}_{}.png".format(image_basename, index)

deepforest/utilities.py

@@ -298,8 +298,9 @@ def shapefile_to_annotations(shapefile,
     if gdf.crs:
         # Check matching the crs
         if not gdf.crs.to_string() == raster_crs.to_string():
-            raise ValueError("The shapefile crs {} does not match the image crs {}".format(
-                gdf.crs, src.crs))
+            raise ValueError(
+                "The shapefile crs {} does not match the image crs {}".format(
+                    gdf.crs, src.crs))
 
     # Transform project coordinates to image coordinates
     df["tile_xmin"] = (df.minx - left) / resolution

environment.yml

@@ -17,7 +17,6 @@ dependencies:
   - pandas
   - pillow>6.2.0
   - pip
-  - pycocotools
   - psutil
   - pytest
   - pytest-profiling
@@ -28,11 +27,12 @@ dependencies:
   - recommonmark
   - rtree
   - slidingwindow
-  - setuptools<=59.2.0
+  - setuptools
   - sphinx
   - sphinx_rtd_theme
   - pytorch::torchvision
   - tqdm
+  - tensorboard
   - twine
   - xmltodict
   - yapf
@@ -41,4 +41,4 @@ dependencies:
     - imagecodecs
     - albumentations>=1.0.0
     - comet_ml
-
+    - pycocotools