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
import mahotas as mh
import numpy as np
from pylab import imshow, show
regions = np.zeros(( 8 , 8 ), bool )
regions[: 3 , : 3 ] = 1
regions[ 6 :, 6 :] = 1
labelled, nr_objects = mh.label(regions)
imshow(labelled, interpolation = 'nearest' )
show()
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Output :
Example 2:
Python3
import mahotas as mh
import numpy as np
from pylab import imshow, show
regions = np.zeros(( 10 , 10 ), bool )
regions[ 1 , 1 ] = 1
regions[ 6 , 6 ] = 1
regions[ 4 , 4 ] = 1
regions[ 9 , 9 ] = 1
labelled, nr_objects = mh.label(regions)
imshow(labelled, interpolation = 'nearest' )
show()
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Output :
Last Updated :
08 Jul, 2021
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