fix ""Missing description"

Author: lorenzocerrone

src/ilastik_tasks/ilastik_pixel_classification_segmentation.py

@@ -172,34 +172,34 @@ def ilastik_pixel_classification_segmentation(
     """Run Ilastik Pixel Classification on a Zarr image.
 
     Args:
-    zarr_url: Path or url to the individual OME-Zarr image to be processed.
-            (standard argument for Fractal tasks, managed by Fractal server).
-    level: Pyramid level of the image to be segmented. Choose `0` to
-        process at full resolution.
-    channel: Primary channel for pixel classification; requires either
-        `wavelength_id` (e.g. `A01_C01`) or `label` (e.g. `DAPI`).
-    channel2: Second channel for pixel classification (in the same format as
-        `channel`). Use only if second channel has also been used during 
-        Ilastik model training.
-    input_ROI_table: Name of the ROI table over which the task loops to
-        apply Cellpose segmentation. Examples: `FOV_ROI_table` => loop over
-        the field of views, `organoid_ROI_table` => loop over the organoid
-        ROI table (generated by another task), `well_ROI_table` => process
-        the whole well as one image.
-    output_ROI_table: If provided, a ROI table with that name is created,
-        which will contain the bounding boxes of the newly segmented
-        labels. ROI tables should have `ROI` in their name.
-    output_label_name: Name of the output label image (e.g. `"embryo"`).
-    use_masks: If `True`, try to use masked loading and fall back to
-        `use_masks=False` if the ROI table is not suitable. Masked
-        loading is relevant when only a subset of the bounding box should
-        actually be processed (e.g. running within `emb_ROI_table`).
-    ilastik_model: Path to the Ilastik model (e.g. `"somemodel.ilp"`).
-    foreground_class: Class to be considered as foreground during
-        prediction thresholding.
-    threshold: Probabiltiy threshold for the Ilastik model.
-    min_size: Minimum size of the segmented objects (in pixels).
-    overwrite: If `True`, overwrite the task output.
+        zarr_url: Path or url to the individual OME-Zarr image to be processed.
+                (standard argument for Fractal tasks, managed by Fractal server).
+        level: Pyramid level of the image to be segmented. Choose `0` to
+            process at full resolution.
+        channel: Primary channel for pixel classification; requires either
+            `wavelength_id` (e.g. `A01_C01`) or `label` (e.g. `DAPI`).
+        channel2: Second channel for pixel classification (in the same format as
+            `channel`). Use only if second channel has also been used during 
+            Ilastik model training.
+        input_ROI_table: Name of the ROI table over which the task loops to
+            apply Cellpose segmentation. Examples: `FOV_ROI_table` => loop over
+            the field of views, `organoid_ROI_table` => loop over the organoid
+            ROI table (generated by another task), `well_ROI_table` => process
+            the whole well as one image.
+        output_ROI_table: If provided, a ROI table with that name is created,
+            which will contain the bounding boxes of the newly segmented
+            labels. ROI tables should have `ROI` in their name.
+        output_label_name: Name of the output label image (e.g. `"embryo"`).
+        use_masks: If `True`, try to use masked loading and fall back to
+            `use_masks=False` if the ROI table is not suitable. Masked
+            loading is relevant when only a subset of the bounding box should
+            actually be processed (e.g. running within `emb_ROI_table`).
+        ilastik_model: Path to the Ilastik model (e.g. `"somemodel.ilp"`).
+        foreground_class: Class to be considered as foreground during
+            prediction thresholding.
+        threshold: Probabiltiy threshold for the Ilastik model.
+        min_size: Minimum size of the segmented objects (in pixels).
+        overwrite: If `True`, overwrite the task output.
     """
     logger.info(f"Processing {zarr_url=}")