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Some of the networks we have in plantseg output foreground probability maps together with boundary predictions. This can be used in the segmentation post-processing step in order to filter background instances (i.e. assign 0-label to pixels not belonging to foreground).
The easiest way to implement it as discussed with @lorenzocerrone and @qin-yu would be to add additional argument to segmentation functions in plantseg/segmentation/functional/segmentation.py called foreground_pmaps and apply filtering the output segmentation if the argument is present. Then support this parameter it in the config, legacy and napari GUI.
The text was updated successfully, but these errors were encountered:
I doubt if this is a good idea. If we are providing this option in each segmentation method, then testing different threshold requires re-runs of the whole segmentation algorithm.
For Napari interface, I would make it a widget similar to widget_fix_over_under_segmentation_from_nuclei() and put it in the same menu, "Extra-Seg".
Some of the networks we have in plantseg output foreground probability maps together with boundary predictions. This can be used in the segmentation post-processing step in order to filter background instances (i.e. assign 0-label to pixels not belonging to foreground).
The easiest way to implement it as discussed with @lorenzocerrone and @qin-yu would be to add additional argument to segmentation functions in
plantseg/segmentation/functional/segmentation.py
calledforeground_pmaps
and apply filtering the output segmentation if the argument is present. Then support this parameter it in the config, legacy and napari GUI.The text was updated successfully, but these errors were encountered: