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
| # importing required librariesimportmahotasimportnumpy as npfrompylab importimshow, showimportos# loading nuclear imagef =mahotas.demos.load('nuclear')# setting filter to the imagef =f[:, :, 0]# setting gaussian filterf =mahotas.gaussian_filter(f, 4)# setting threshold valuef =(f> f.mean())# creating a labelled imagelabelled, n_nucleus =mahotas.label(f)# showing the labelled imageprint("Labelled Image")imshow(labelled)show()# getting bounding boxesrelabeled =mahotas.labelled.bbox(labelled)# showing the imageprint("Bounding Boxes")imshow(relabelled)show() | 
Output : 
 
Example 2 : 
 
Python3
| # importing required librariesimportnumpy as npimportmahotasfrompylab importimshow, show # loading imageimg =mahotas.imread('dog_image.png')   # filtering the imageimg =img[:, :, 0]    # setting gaussian filtergaussian =mahotas.gaussian_filter(img, 15) # setting threshold valuegaussian =(gaussian > gaussian.mean()) # creating a labelled imagelabelled, n_nucleus =mahotas.label(gaussian)  print("Labelled Image")# showing the gaussian filterimshow(labelled)show() # getting bounding boxesrelabelled =mahotas.labelled.bbox(labelled)# showing the imageprint("Bounding Boxes")imshow(relabelled)show() | 
Output : 
 
 
				 
					



