comment out cyto_dl for ci

src/allencell_ml_segmenter/_tests/prediction/test_file_input_widget.py

@@ -90,12 +90,13 @@ def test_preprocessing_method(
     # ASSERT 2
     assert file_input_widget._model.get_preprocessing_method() is None
 
-def test_populate_input_channel_combobox(
-    qtbot: QtBot
-) -> None:
+
+def test_populate_input_channel_combobox(qtbot: QtBot) -> None:
     # Arrange
     prediction_model: PredictionModel = PredictionModel()
-    prediction_file_input: PredictionFileInput = PredictionFileInput(prediction_model)
+    prediction_file_input: PredictionFileInput = PredictionFileInput(
+        prediction_model
+    )
     prediction_model.set_max_channels(6)
 
     # Act

src/allencell_ml_segmenter/_tests/prediction/test_model.py

@@ -31,6 +31,7 @@ def test_input_image_paths(prediction_model: PredictionModel) -> None:
     # ASSERT
     assert prediction_model.get_input_image_dir() == dummy_paths
 
+
 def test_image_input_channel_index(prediction_model: PredictionModel) -> None:
     """
     Tests that the channel index is set and retrieved properly.

src/allencell_ml_segmenter/_tests/prediction/test_model_file_service.py

@@ -15,12 +15,30 @@ def test_extract_num_channels_in_a_folder() -> None:
     model_file_service: ModelFileService = ModelFileService(prediction_model)
 
     # Act / Assert
-    assert model_file_service.extract_num_channels_in_folder(Path(allencell_ml_segmenter.__file__).parent / "_tests" / "test_files" / "images") == 3
+    assert (
+        model_file_service.extract_num_channels_in_folder(
+            Path(allencell_ml_segmenter.__file__).parent
+            / "_tests"
+            / "test_files"
+            / "images"
+        )
+        == 3
+    )
+
 
 def test_extract_num_channels_from_csv() -> None:
     # Arrange
     prediction_model: PredictionModel = PredictionModel()
     model_file_service: ModelFileService = ModelFileService(prediction_model)
 
     # Act / Assert
-    assert model_file_service.extract_num_channels_from_csv(Path(allencell_ml_segmenter.__file__).parent / "_tests" / "test_files" / "csv" / "test_csv.csv") == 3
+    assert (
+        model_file_service.extract_num_channels_from_csv(
+            Path(allencell_ml_segmenter.__file__).parent
+            / "_tests"
+            / "test_files"
+            / "csv"
+            / "test_csv.csv"
+        )
+        == 3
+    )

src/allencell_ml_segmenter/prediction/file_input_widget.py

@@ -118,9 +118,7 @@ def __init__(self, model: PredictionModel):
 
         self._browse_dir_edit: InputButton = InputButton(
             self._model,
-            lambda dir: self._model.set_input_image_dir(
-                Path(dir)
-            ),
+            lambda dir: self._model.set_input_image_dir(Path(dir)),
             "Select directory...",
             FileInputMode.DIRECTORY_OR_CSV,
         )
@@ -140,13 +138,16 @@ def __init__(self, model: PredictionModel):
         self._channel_select_dropdown.setPlaceholderText(
             "select a channel index"
         )
-        self._channel_select_dropdown.currentIndexChanged.connect(self._model.set_image_input_channel_index)
+        self._channel_select_dropdown.currentIndexChanged.connect(
+            self._model.set_image_input_channel_index
+        )
         self._channel_select_dropdown.setEnabled(False)
         # Event to trigger combobox populate on input image directory selection
-        self._model.subscribe(Event.ACTION_PREDICTION_INPUT_PATH_SELECTED,
-                              self,
-                              self._populate_input_channel_combobox)
-
+        self._model.subscribe(
+            Event.ACTION_PREDICTION_INPUT_PATH_SELECTED,
+            self,
+            self._populate_input_channel_combobox,
+        )
 
         output_dir_label: LabelWithHint = LabelWithHint("Output directory")
         output_dir_label.set_hint("Location to save segmentations.")
@@ -180,8 +181,8 @@ def _from_directory_slot(self) -> None:
         self._browse_dir_edit.setEnabled(True)
 
     def _populate_input_channel_combobox(self, event: Event = None) -> None:
-        values_range: List[str] = [str(i) for i in range(self._model.get_max_channels())]
+        values_range: List[str] = [
+            str(i) for i in range(self._model.get_max_channels())
+        ]
         self._channel_select_dropdown.addItems(values_range)
         self._channel_select_dropdown.setEnabled(True)
-
-

src/allencell_ml_segmenter/prediction/service.py

@@ -27,7 +27,11 @@ def __init__(self, model: PredictionModel):
         self._model.subscribe(
             Event.ACTION_PREDICTION_EXTRACT_CHANNELS,
             self,
-            lambda e: self._model.set_max_channels(self._determine_input_selection_type(self._model.get_input_image_dir()))
+            lambda e: self._model.set_max_channels(
+                self._determine_input_selection_type(
+                    self._model.get_input_image_dir()
+                )
+            ),
         )
 
     def handle_event(self, event: Event) -> None:
@@ -47,10 +51,10 @@ def extract_num_channels_in_folder(self, path: Path) -> int:
         # we expect user to have the same number of channels for all images in their folders
         # and that only images are stored in those folders
         # Get first image path
-        path_generator: Generator[Path] = path.glob('*')
+        path_generator: Generator[Path] = path.glob("*")
         first_image: Path = next(path_generator)
         # ignore hidden files
-        while str(first_image.name).split('.')[0] == "":
+        while str(first_image.name).split(".")[0] == "":
             first_image = next(path_generator)
 
         img: AICSImage = AICSImage(str(first_image.resolve()))
@@ -61,7 +65,7 @@ def extract_num_channels_from_csv(self, path: Path):
             reader: csv.reader = csv.reader(file)
             # skip heading
             next(reader)
-            line_data_path:str = next(reader)[1]
+            line_data_path: str = next(reader)[1]
             img: AICSImage = AICSImage(str(line_data_path))
             return img.dims.C
 
@@ -74,6 +78,3 @@ def _determine_input_selection_type(self, path: Path):
 
         # for testing current api
         return self.extract_num_channels_from_csv(path / "train.csv")
-
-
-

src/allencell_ml_segmenter/services/prediction_service.py

@@ -9,7 +9,7 @@
 from pathlib import Path
 from typing import Union, Dict
 
-from cyto_dl.api.model import CytoDLModel
+# from cyto_dl.api.model import CytoDLModel
 from napari.utils.notifications import show_warning
 
 

src/allencell_ml_segmenter/services/training_service.py

@@ -3,7 +3,7 @@
 from allencell_ml_segmenter.core.subscriber import Subscriber
 from allencell_ml_segmenter.core.event import Event
 
-from cyto_dl.api.model import CytoDLModel
+# from cyto_dl.api.model import CytoDLModel
 
 # from lightning.pytorch.callbacks import Callback