Fix for yx images in Cellpose task

CHANGELOG.md

@@ -5,6 +5,7 @@
 * Tasks:
  * Fix issue with masked ROI & relabeling in Cellpose task (\#785).
  * Fix issue with masking ROI label types in masked_loading_wrapper for Cellpose task (\#785).
+ * Enable workaround to support yx images in Cellpose task (\#789).
 
 # 1.1.0
 

fractal_tasks_core/tasks/cellpose_segmentation.py

@@ -314,11 +314,21 @@ def cellpose_segmentation(
  output_label_name = f"label_{ind_channel}"
 
  # Load ZYX data
- data_zyx = da.from_zarr(f"{zarr_url}/{level}")[ind_channel]
+ # Workaround for #788: Only load channel index when there is a channel
+ # dimension
+ if ngff_image_meta.axes_names[0] != "c":
+ data_zyx = da.from_zarr(f"{zarr_url}/{level}")
+ if channel2.is_set():
+ raise ValueError(
+ "Dual channel input was specified for an OME-Zarr image "
+ "without a channel axis"
+ )
+ else:
+ data_zyx = da.from_zarr(f"{zarr_url}/{level}")[ind_channel]
+ if channel2.is_set():
+ data_zyx_c2 = da.from_zarr(f"{zarr_url}/{level}")[ind_channel_c2]
+ logger.info(f"Second channel: {data_zyx_c2.shape=}")
  logger.info(f"{data_zyx.shape=}")
- if channel2.is_set():
- data_zyx_c2 = da.from_zarr(f"{zarr_url}/{level}")[ind_channel_c2]
- logger.info(f"Second channel: {data_zyx_c2.shape=}")
 
  # Read ROI table
  ROI_table_path = f"{zarr_url}/tables/{input_ROI_table}"
@@ -365,18 +375,21 @@ def cellpose_segmentation(
  logger.info(f"Anisotropy: {advanced_cellpose_model_params.anisotropy}")
 
  # Rescale datasets (only relevant for level>0)
+ # Workaround for #788
  if ngff_image_meta.axes_names[0] != "c":
- raise ValueError(
- "Cannot set `remove_channel_axis=True` for multiscale "
- f"metadata with axes={ngff_image_meta.axes_names}. "
- 'First axis should have name "c".'
+ new_datasets = rescale_datasets(
+ datasets=[ds.dict() for ds in ngff_image_meta.datasets],
+ coarsening_xy=coarsening_xy,
+ reference_level=level,
+ remove_channel_axis=False,
+ )
+ else:
+ new_datasets = rescale_datasets(
+ datasets=[ds.dict() for ds in ngff_image_meta.datasets],
+ coarsening_xy=coarsening_xy,
+ reference_level=level,
+ remove_channel_axis=True,
  )
- new_datasets = rescale_datasets(
- datasets=[ds.dict() for ds in ngff_image_meta.datasets],
- coarsening_xy=coarsening_xy,
- reference_level=level,
- remove_channel_axis=True,
- )
 
  label_attrs = {
  "image-label": {