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Labeled Image Function in Python Mahotas
  • Last Updated : 22 Jun, 2020

In this article we will see how we can obtain a labeled function from a binary function in mahotas. 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. By convention, region 0 is the background and often handled differently.

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

Syntax : mahotas.label(regions)

Argument : It takes numpy.ndarray object as argument

Return : It returns numpy.ndarray object and integer value



Example 1:




# importing required libraries
import mahotas as mh
import numpy as np
from pylab import imshow, show
  
# creating region
# numpy.ndarray
regions = np.zeros((8, 8), bool)
  
# setting 1 value to the region
regions[:3, :3] = 1
regions[6:, 6:] = 1
  
# getting labeled function
labeled, nr_objects = mh.label(regions)
  
# showing the image with interpolation = 'nearest'
imshow(labeled, interpolation ='nearest')
show()

Output :

Example 2:




# importing required libraries
import mahotas as mh
import numpy as np
from pylab import imshow, show
  
# creating region
# numpy.ndarray
regions = np.zeros((10, 10), bool)
  
# setting 1 value in the region
regions[1, 1] = 1
regions[6, 6] = 1
regions[4, 4] = 1
regions[9, 9] = 1
  
# getting labeled function
labeled, nr_objects = mh.label(regions)
  
# showing the image with interpolation = 'nearest'
imshow(labeled, interpolation ='nearest')
show()

Output :

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