Mahotas – Getting Bounding Boxes of Labelled Image
In this article we will see how we can get the bounding boxes of all the objects in the labelled image in mahotas. 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
mahotas.demos.nuclear_image()
Below is the nuclear_image
In order to do this we will use mahotas.labelled.bbox method
Syntax : mahotas.labelled.bbox(labelled_image)
Argument : It takes numpy.ndarray object as argument i.e labelled image
Return : It returns numpy.ndarray object i.e bounding box image
Note : The input of the this should be the filtered image object which is labeled
In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this
image = image[:, :, 0]
Example 1 :
Python3
import mahotas
import numpy as np
from pylab import imshow, show
import os
f = mahotas.demos.load( 'nuclear' )
f = f[:, :, 0 ]
f = mahotas.gaussian_filter(f, 4 )
f = (f> f.mean())
labelled, n_nucleus = mahotas.label(f)
print ( "Labelled Image" )
imshow(labelled)
show()
relabeled = mahotas.labelled.bbox(labelled)
print ( "Bounding Boxes" )
imshow(relabelled)
show()
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Output :
Example 2 :
Python3
import numpy as np
import mahotas
from pylab import imshow, show
img = mahotas.imread( 'dog_image.png' )
img = img[:, :, 0 ]
gaussian = mahotas.gaussian_filter(img, 15 )
gaussian = (gaussian > gaussian.mean())
labelled, n_nucleus = mahotas.label(gaussian)
print ( "Labelled Image" )
imshow(labelled)
show()
relabelled = mahotas.labelled.bbox(labelled)
print ( "Bounding Boxes" )
imshow(relabelled)
show()
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Output :
Last Updated :
24 Feb, 2023
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