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Mahotas – Getting Bounding Boxes of Labelled Image

  • Last Updated : 22 Apr, 2021

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 
 

mhotas.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 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




# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
 
# loading nuclear image
f = mahotas.demos.load('nuclear')
 
# setting filter to the image
f = f[:, :, 0]
 
# setting gaussian filter
f = mahotas.gaussian_filter(f, 4)
 
# setting threshold value
f = (f> f.mean())
 
# creating a labelled image
labelled, n_nucleus = mahotas.label(f)
 
 
# showing the labelled image
print("Labelled Image")
imshow(labelled)
show()
 
# getting bounding boxes
relabeled = mahotas.labelled.bbox(labelled)
 
# showing the image
print("Bounding Boxes")
imshow(relabelled)
show()

Output : 
 

Example 2 : 
 

Python3




# importing required libraries
import numpy as np
import mahotas
from pylab import imshow, show
  
# loading image
img = mahotas.imread('dog_image.png')
    
# filtering the image
img = img[:, :, 0]
     
# setting gaussian filter
gaussian = mahotas.gaussian_filter(img, 15)
  
# setting threshold value
gaussian = (gaussian > gaussian.mean())
  
# creating a labelled image
labelled, n_nucleus = mahotas.label(gaussian)
   
print("Labelled Image")
# showing the gaussian filter
imshow(labelled)
show()
  
# getting bounding boxes
relabelled = mahotas.labelled.bbox(labelled)
 
# showing the image
print("Bounding Boxes")
imshow(relabelled)
show()

Output : 
 

 

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