csv to label properties

[will-moore]

Takes a csv file with 1 row per Mask (e.g. exported from OMERO with Batch_ROI_Export) and uses it to
add properties to the labels metadata in ome-zarr.
You need to specify which column of the csv contains an ID that matches a specified ID of each properties dict.

E.g. if you have exported labels from OMERO with ome/omero-cli-zarr#50 then each properties dict will have e.g. "omero:shapeId": 123 and this will correspond to the shape_id column of the Batch_ROI_Export.csv.

You also want to specify columns from the csv to use, e.g. "area (pixels),X,Y,Width,Height".
You can also specify the column types (as in https://github.com/ome/omero-metadata/) to specify the data-type for each column (string by default).

• d: DoubleColumn, for floating point numbers
• l: LongColumn, for integer numbers
• s: StringColumn, for text
• b: BoolColumn, for true/false

Use e.g. #d as a suffix in the column name to denote a float column, no spaces etc:

"area (pixels)#d,well_label#s,Width#l,Height#l"

If you have a Plate exported to ome-zarr as "251.zarr", then you can do this:

ome_zarr csv_to_labels plate251_ch1.csv shape_id "area (pixels)#d,well_label#s,Width#l,Height#l" 251.zarr omero:shapeId

Then you can open a Well (field 0) in napari, and the properties will be read by #61 cc @DragaDoncila and you will be able to see the properties from the csv (bottom left) when you mouse over a label

napari 251.zarr/A/1/0

You can then use the properties to update label colors:

layer = viewer.layers[-1]

for c, value in enumerate(layer.properties["area (pixels)"]):
    index = layer.properties["index"][c]
    if value > 2500:
        layer.color[index] = np.array([1, 0, 1, 1], dtype=np.float32)
    elif value < 2000:
        layer.color[index] = np.array([1, 1, 1, 1], dtype=np.float32)
    else:
        layer.color[index] = np.array([0, 1, 0, 1], dtype=np.float32)
   
# force refresh
layer.color_mode = "direct"

TODO:

• Also support single Images in ome-zarr instead of whole Plate
• Parse csv number columns as numbers

[joshmoore]

Something like this was needed to omit missing labels:

(o) [jamoore@pilot-zarr1-dev 2551.zarr]$ (cd /data/josh/ome-zarr-py/; git diff)
diff --git a/ome_zarr/csv.py b/ome_zarr/csv.py
index de287e3..bdcb012 100644
--- a/ome_zarr/csv.py
+++ b/ome_zarr/csv.py
@@ -127,7 +127,10 @@ def dict_to_zarr(

     for path_to_labels in labels_paths:

-        label_group = zarr_open(path_to_labels)
+        try:
+            label_group = zarr_open(path_to_labels)
+        except:
+            continue
         attrs = label_group.attrs.asdict()
         properties = attrs.get("image-label", {}).get("properties")
         if properties is None:

[will-moore]

Ah, Thanks. Yes, I've just viewed the plate with labels and noticed that some Wells are missing labels:

napari https://s3.embassy.ebi.ac.uk/idr/zarr/v0.1/plates/2551.zarr

[joshmoore]

Considering the test of 2551 successful since the source plate (2551 above) is also missing those labels. Merging for the next tag.