def find_merge_error(self, image, prob, segmentation, label):
'''
Find a merge error in a segment.
This generates 50 borders within the segment and ranks them
using the CNN.
Returns
The corrected segment.
and
Rank (1-p) for the found merge error.
1 If confident
..
0 If uncertain
or
-1 If there was a problem.
'''
# create binary mask
binary = Util.threshold(segmentation, label)
# here potential boundaries are generated and ranked by the CNN
results = Legacy.fix_single_merge(self._cnn,
image,
prob,
binary,
N=50,
erode=True,
invert=True,
dilate=True,
border_seeds=True,
oversampling=False)
if len(results) > 0:
# sort the prediction/border tuples (prediction, border)-tupels
sorted_pred = sorted(results, key=lambda x: x[0])
lowest_rank = sorted_pred[0][0]
border = sorted_pred[0][1]
corrected = Legacy.correct_merge(segmentation, label, border)
return corrected, 1. - lowest_rank
else:
return -1
