In this article, we will see how we can check if the two images represent the same labeling 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.labeled.is_same_labeling method
Syntax : mahotas.labeled.is_same_labeling(label1. labeled2)
Argument : It takes two labelled image as argument
Return : It returns bool
Note: The input of 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 libraries import mahotas import numpy as np from pylab import imshow, show import os # loading nuclear image f1 = mahotas.demos.load( 'nuclear' ) # setting filter to the image f1 = f1[:, :, 0 ] # setting gaussian filter f1 = mahotas.gaussian_filter(f1, 4 ) # setting threshold value f1 = (f1> f1.mean()) # creating a labeled image labeled1, n_nucleus1 = mahotas.label(f1) # showing the labeled image print ( "Labelled 1 Image" ) imshow(labeled1) show() # loading nuclear image f2 = mahotas.demos.load( 'nuclear' ) # setting filter to the image f2 = f2[:, :, 0 ] # setting gaussian filter f2 = mahotas.gaussian_filter(f2, 4 ) # setting threshold value f2 = (f2> f2.mean()) # creating a labeled image labeled2, n_nucleus2 = mahotas.label(f2) # showing the labeled image print ( "Labelled 2 Image" ) imshow(labeled2) show() # checking if both the labeled images are same check = mahotas.labeled.is_same_labeling(labeled1, labeled2) # printing check print ( "Same Labelling : " + str (check)) |
Output :
Same Labelling : True
Example 2 :
Python3
# importing required libraries import mahotas import numpy as np from pylab import imshow, show import os # loading nuclear image f1 = mahotas.demos.load( 'nuclear' ) # setting filter to the image f1 = f1[:, :, 0 ] # setting gaussian filter f1 = mahotas.gaussian_filter(f1, 4 ) # setting threshold value f1 = (f1> f1.mean()) # creating a labeled image labeled1, n_nucleus1 = mahotas.label(f1) # showing the labeled image print ( "Labelled 1 Image" ) imshow(labeled1) show() # loading nuclear image f2 = mahotas.demos.load( 'nuclear' ) # setting filter to the image f2 = f2[:, :, 0 ] # setting gaussian filter f2 = mahotas.gaussian_filter(f2, 4 ) # setting threshold value f2 = (f2> f2.mean()) # creating a labeled image labeled2, n_nucleus2 = mahotas.label(f2) # removing border labeled2 = mahotas.labeled.remove_bordering(labeled2) # showing the labeled image print ( "Labelled 2 Image" ) imshow(labeled2) show() # checking if both the labeled images are same check = mahotas.labeled.is_same_labeling(labeled1, labeled2) # printing check print ( "Same Labelling : " + str (check)) |
Output :
Same Labelling : False