Merge pull request #4 from rhornb/bug_fix

Fixes to pixel classification task

Author: lorenzocerrone

.gitignore

@@ -109,4 +109,8 @@ ENV/
 
 # IDE settings
 .vscode/
-.idea/
+.idea/
+
+*.zarr
+# Test data loaded via pooch
+/tests/data/10_5281_zenodo_14883998

create_env_script.sh

@@ -19,7 +19,7 @@ $COMMMAND run $COMMMAND create $LOCATION \
                                --override-channels \
                                -c pytorch \
                                -c ilastik-forge \
-                               -c conda-forge $PYTHON ilastik \
+                               -c conda-forge $PYTHON ilastik vigra \
                                --no-channel-priority --yes
 
 echo "Installing ilastik-tasks version $VERSION"

src/ilastik_tasks/__FRACTAL_MANIFEST__.json

@@ -37,62 +37,77 @@
           "zarr_url": {
             "title": "Zarr Url",
             "type": "string",
-            "description": "URL of the Zarr image."
+            "description": "Path or url to the individual OME-Zarr image to be processed. (standard argument for Fractal tasks, managed by Fractal server)."
           },
           "level": {
             "title": "Level",
             "type": "integer",
-            "description": "Level of the Zarr image to process."
+            "description": "Pyramid level of the image to be segmented. Choose `0` to process at full resolution."
           },
           "channel": {
             "$ref": "#/$defs/ChannelInputModel",
             "title": "Channel",
-            "description": "Channel input model."
+            "description": "Primary channel for pixel classification; requires either `wavelength_id` (e.g. `A01_C01`) or `label` (e.g. `DAPI`)."
           },
-          "ilastik_model": {
-            "title": "Ilastik Model",
-            "type": "string",
-            "description": "Path to the Ilastik model."
+          "channel2": {
+            "allOf": [
+              {
+                "$ref": "#/$defs/ChannelInputModel"
+              }
+            ],
+            "title": "Channel2",
+            "description": "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": {
             "default": "FOV_ROI_table",
             "title": "Input Roi Table",
             "type": "string",
-            "description": "Name of the input ROI table."
+            "description": "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": {
             "title": "Output Roi Table",
             "type": "string",
-            "description": "Name of the output ROI table."
+            "description": "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": {
             "title": "Output Label Name",
             "type": "string",
-            "description": "Name of the output label."
+            "description": "Name of the output label image (e.g. `\"embryo\"`)."
+          },
+          "use_masks": {
+            "default": true,
+            "title": "Use Masks",
+            "type": "boolean",
+            "description": "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": {
+            "title": "Ilastik Model",
+            "type": "string",
+            "description": "Path to the Ilastik model (e.g. `\"somemodel.ilp\"`)."
+          },
+          "foreground_class": {
+            "default": 0,
+            "title": "Foreground Class",
+            "type": "integer",
+            "description": "Class to be considered as foreground during prediction thresholding."
           },
           "threshold": {
-            "default": 10000,
+            "default": 0.5,
             "title": "Threshold",
-            "type": "integer",
-            "description": "Threshold for the Ilastik model."
+            "type": "number",
+            "description": "Probabiltiy threshold for the Ilastik model."
           },
           "min_size": {
-            "default": 3,
+            "default": 15,
             "title": "Min Size",
             "type": "integer",
-            "description": "Minimum size for the Ilastik model."
-          },
-          "use_masks": {
-            "default": true,
-            "title": "Use Masks",
-            "type": "boolean",
-            "description": "Whether to use masks."
+            "description": "Minimum size of the segmented objects (in pixels)."
           },
           "overwrite": {
             "default": true,
             "title": "Overwrite",
             "type": "boolean",
-            "description": "Whether to overwrite existing data."
+            "description": "If `True`, overwrite the task output."
           }
         },
         "required": [

src/ilastik_tasks/__init__.py

@@ -1,9 +1,8 @@
-"""
-Collection of Fractal task to run Headless ilastik workflows
-"""
+"""Collection of Fractal task to run Headless ilastik workflows"""
+
 from importlib.metadata import PackageNotFoundError, version
 
 try:
     __version__ = version("ilastik-tasks")
 except PackageNotFoundError:
-    __version__ = "uninstalled"
+    __version__ = "uninstalled"

src/ilastik_tasks/dev/create_manifest.py

@@ -1,7 +1,5 @@
-"""
-Generate JSON schemas for task arguments afresh, and write them
-to the package manifest.
-"""
+"""Generate JSON schemas for task arguments."""
+
 from fractal_tasks_core.dev.create_manifest import create_manifest
 
 if __name__ == "__main__":