Add docs info & improve output filter setting of 2d to 3d task

.copier-answers.yml

@@ -1,5 +1,5 @@
 # Do not edit - changes here will be overwritten by Copier
-_commit: v0.4.4
+_commit: v0.4.5
 _src_path: gh:fractal-analytics-platform/fractal-tasks-template
 author_email: [email protected]
 author_name: Joel Luethi

pyproject.toml

@@ -27,7 +27,7 @@ authors = [
 # Required Python version and dependencies
 requires-python = ">=3.9"
 dependencies = [
-    "fractal-tasks-core==1.3.3"
+    "fractal-tasks-core==1.3.4"
 ]
 
 # Optional dependencies (e.g. for `pip install -e ".[dev]"`, see

src/fractal_helper_tasks/__FRACTAL_MANIFEST__.json

@@ -9,6 +9,7 @@
       "tags": [
         "Singleton time dimension"
       ],
+      "docs_info": "### Purpose\n- Removes a **singleton time (T) dimension** from an OME-Zarr image.  \n- Creates a new OME-Zarr image with updated metadata and dimensions.\n- Optionally overwrites the input image if `overwrite_input` is set to True.\n\n### Outputs\n- A **new Zarr image** without the singleton T-dimension, stored with a configurable suffix.  \n\n### Limitations\n- Only processes OME-Zarr images where the **T-axis is the first axis**.  \n- Assumes the T-dimension is **singleton**; does not process non-singleton time axes.  \n- Does not copy associated **label images** or **ROI tables** to the new Zarr structure.  ",
       "executable_non_parallel": "drop_t_dimension.py",
       "meta_non_parallel": {
         "cpus_per_task": 2,
@@ -41,7 +42,6 @@
         "type": "object",
         "title": "DropTDimension"
       },
-      "docs_info": "## drop_t_dimension\nDrops singleton t dimension.\n",
       "docs_link": "https://github.com/jluethi/fractal-helper-tasks"
     },
     {
@@ -53,6 +53,7 @@
         "Mixed modality",
         "2D to 3D workflows"
       ],
+      "docs_info": "### Purpose\n- Converts a **2D segmentation** image into a **3D segmentation** by replicating the 2D segmentation across Z-slices.  \n- Supports OME-Zarr datasets where **2D and 3D images** share the same base name but differ by suffixes.  \n- Optionally copies associated ROI tables and adjusts them to align with the replicated Z-dimensions.  \n\n### Outputs\n- A **3D segmentation label image** saved with a new name.  \n- Updated **ROI tables** adjusted for Z-dimensions (optional).  \n\n### Limitations\n- Only supports **same-base 2D and 3D Zarr names**; full flexibility in file names is not yet implemented.  \n- Assumes **2D OME-Zarr images** and corresponding 3D images are stored in the same base folder and just differ with a suffix before the .zarr.  \n",
       "executable_parallel": "convert_2D_segmentation_to_3D.py",
       "meta_parallel": {
         "cpus_per_task": 2,
@@ -126,7 +127,6 @@
         "type": "object",
         "title": "Convert2dSegmentationTo3d"
       },
-      "docs_info": "## convert_2D_segmentation_to_3D\nConvert 2D segmentation to 3D segmentation.\n\nThis task loads the 2D segmentation, replicates it along the Z slice and\nstores it back into the 3D OME-Zarr image.\n\nThis is a temporary workaround task, as long as we store 2D data in\na separate OME-Zarr file from the 3D data. If the 2D & 3D OME-Zarr images\nhave different suffixes in their name, use `image_suffix_2D_to_remove` &\n`image_suffix_3D_to_add`. If their base names are different, this task\ndoes not support processing them at the moment.\n\nIt makes the assumption that the 3D OME-Zarrs are stored in the same place\nas the 2D OME-Zarrs (same based folder).\n",
       "docs_link": "https://github.com/jluethi/fractal-helper-tasks"
     }
   ],

src/fractal_helper_tasks/convert_2D_segmentation_to_3D.py

@@ -247,10 +247,15 @@ def convert_2D_segmentation_to_3D(
                 table_attrs=table_attrs,
             )
 
-    # FIXME: Set a filter for is_3D = True
-
     logger.info("Finished 2D to 3D conversion")
 
+    output_dict = dict(
+        filters=dict(
+            types=dict(is_3D=True),
+        )
+    )
+    return output_dict
+
 
 if __name__ == "__main__":
     from fractal_tasks_core.tasks._utils import run_fractal_task

src/fractal_helper_tasks/dev/docs_info/2d_to_3d.md

@@ -0,0 +1,12 @@
+### Purpose
+- Converts a **2D segmentation** image into a **3D segmentation** by replicating the 2D segmentation across Z-slices.  
+- Supports OME-Zarr datasets where **2D and 3D images** share the same base name but differ by suffixes.  
+- Optionally copies associated ROI tables and adjusts them to align with the replicated Z-dimensions.  
+
+### Outputs
+- A **3D segmentation label image** saved with a new name.  
+- Updated **ROI tables** adjusted for Z-dimensions (optional).  
+
+### Limitations
+- Only supports **same-base 2D and 3D Zarr names**; full flexibility in file names is not yet implemented.  
+- Assumes **2D OME-Zarr images** and corresponding 3D images are stored in the same base folder and just differ with a suffix before the .zarr.  

src/fractal_helper_tasks/dev/docs_info/drop_t_dimension.md

@@ -0,0 +1,12 @@
+### Purpose
+- Removes a **singleton time (T) dimension** from an OME-Zarr image.  
+- Creates a new OME-Zarr image with updated metadata and dimensions.
+- Optionally overwrites the input image if `overwrite_input` is set to True.
+
+### Outputs
+- A **new Zarr image** without the singleton T-dimension, stored with a configurable suffix.  
+
+### Limitations
+- Only processes OME-Zarr images where the **T-axis is the first axis**.  
+- Assumes the T-dimension is **singleton**; does not process non-singleton time axes.  
+- Does not copy associated **label images** or **ROI tables** to the new Zarr structure.  

src/fractal_helper_tasks/dev/task_list.py

@@ -9,6 +9,7 @@
         meta={"cpus_per_task": 2, "mem": 8000},
         output_types=dict(has_t=False),
         tags=["Singleton time dimension"],
+        docs_info="file:docs_info/drop_t_dimension.md",
     ),
     ParallelTask(
         input_types=dict(is_3D=False),
@@ -19,5 +20,6 @@
             "Mixed modality",
             "2D to 3D workflows",
         ],
+        docs_info="file:docs_info/2d_to_3d.md",
     ),
 ]