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.labeled.bbox method
Syntax : mahotas.labeled.bbox(labeled_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
iamge = image[:, :, 0]
Example 1 :
# 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 labeled image labeled, n_nucleus = mahotas.label(f) # showing the labeleed image print("Labelled Image") imshow(labeled) show() # getting bounding boxes relabeled = mahotas.labeled.bbox(labeled) # showing the image print("Bounding Boxes") imshow(relabeled) show() |
Output :
Example 2 :
# importing required libraries import numpy as np import mahotas from pylab import imshow, show # loading iamge img = mahotas.imread('dog_image.png') # filtering the imagwe img = img[:, :, 0] # setting gaussian filter gaussian = mahotas.gaussian_filter(img, 15) # setting threshold value gaussian = (gaussian > gaussian.mean()) # creating a labeled image labeled, n_nucleus = mahotas.label(gaussian) print("Labelled Image") # showing the gaussian filter imshow(labeled) show() # getting bounding boxes relabeled = mahotas.labeled.bbox(labeled) # showing the image print("Bounding Boxes") imshow(relabeled) show() |
Output :
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