Join Labels with Napari¶

This function joins classes with the same label. This function would be run after classes are labeled with napari_label_classes.

plantcv.annotate.napari_join_labels(img, viewer)

returns relabeled mask, dictionary of masks for each class

• Parameters:

  • img - image data (compatible with gray, RGB, and hyperspectral data. If data is hyperspecral it should be the array e.g. hyperspectral.array_data)
  • viewer - viewer with labeled classes(likely created with napari_label_classes). If no points are selected for a class, data without labels will default to this class when napari_join_labels is run. If all classes have points labeled, any clusters not labeled will default to the last class in the list if napari_join_labels is run.

• Context:

  • This function would be run after labeling classes in Napari is complete.

• Example use:

  • Joining classes labeled as the same, for example for joining classes from output of kmeans clustering

import plantcv.plantcv as pcv 
import plantcv.annotate as pcvan
import napari

# Create an instance of the Points class
img, path, name = pcv.readimage("./grayimg.png")

viewer = pcvan.napari_label_classes(img=img, ['background', 'wing','seed'])

# Should open interactive napari viewer

labeledmask, mask_dict = pcvan.napari_join_lables(img=img, viewer=viewer)

Source Code: Here