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Labelled Image Function in Python Mahotas

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  • Last Updated : 08 Jul, 2021

In this article we will see how we can obtain a labelled function from a binary function in mahotas. Labelled 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: 
 

Python3




# 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 labelled function
labelled, nr_objects = mh.label(regions)
 
# showing the image with interpolation = 'nearest'
imshow(labelled, interpolation ='nearest')
show()

Output : 
 

Example 2: 
 

Python3




# 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 labelled function
labelled, nr_objects = mh.label(regions)
 
# showing the image with interpolation = 'nearest'
imshow(labelled, interpolation ='nearest')
show()

Output : 
 

 


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