Labelled Image Function in Python Mahotas
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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