Mahotas – Re-Labeling

In this article we will see how we can relabel the labelled image in mahotas. Relabeling is used to label the already labelled image, this is required becuase some times there are mane labels which user deletes so when that image get relabel, we get the new label number as well. We use mahotas.label method to label the image

For this we are going to use the fluorescent microscopy image from a nuclear segmentation benchmark. We can get the image with the help of command given below

mhotas.demos.nuclear_image()

Below is the nuclear_image

Labeled images are integer images where the values correspond to different regions. I.e., region 1 is all of the pixels which have value 1, region two is the pixels with value 2, and so on

In order to do this we will use mahotas.relabel method



Syntax : mahotas.relabel(labeled)

Argument : It takes labeled image object as argument

Return : It returns the labelled image and integer i.e number of labels

Example 1:

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# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
  
# loading nuclear image
f = mahotas.demos.load('nuclear')
  
# setting filter to the image
f = f[:, :, 0]
  
# setting gaussian filter
f = mahotas.gaussian_filter(f, 4)
  
# setting threshold value
f = (f> f.mean())
  
# creating a labeled image
labeled, n_nucleus = mahotas.label(f)
  
# printing number of labels
print("Count : " + str(n_nucleus))
  
# showing the labeleed image
print("Labelled Image")
imshow(labeled)
show()
  
# removing border labels
labeled = mh.labeled.remove_bordering(labeled)
  
# relabling the labeled image
relabeled, n_left = mahotas.labeled.relabel(labeled)
  
# showing number of labels
print("Count : " + str(n_left))
  
# showing the image
print("No border Label")
imshow(relabeled)
show()

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Output :

Example 2:

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# importing required libraries
import numpy as np
import mahotas
from pylab import imshow, show
  
# loading iamge
img = mahotas.imread('dog_image.png')
    
# filtering the imagwe
img = img[:, :, 0]
     
# setting gaussian filter
gaussian = mahotas.gaussian_filter(img, 15)
  
# setting threshold value
gaussian = (gaussian > gaussian.mean())
  
# creating a labeled image
labeled, n_nucleus = mahotas.label(gaussian)
  
# printing number of labels
print("Count : " + str(n_nucleus))
   
print("Labelled Image")
# showing the gaussian filter
imshow(labeled)
show()
  
# removing border labels
labeled = mh.labeled.remove_bordering(labeled)
  
# relabling the labeled image
relabeled, n_left = mahotas.labeled.relabel(labeled)
  
# showing number of labels
print("Count : " + str(n_left))
  
# showing the image
print("No border Label")
imshow(relabeled)
show()

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Output :

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