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Labeled Image Function in Python Mahotas
• Last Updated : 22 Jun, 2020

In this article we will see how we can obtain a labeled function from a binary function in mahotas. Labeled images are integer images where the values correspond to different regions. I.e., region 1 is all of the pixels which have value 1, region two is the pixels with value 2, and so on. By convention, region 0 is the background and often handled differently.

In order to do this we will use `mahotas.label` method

Syntax : mahotas.label(regions)

Argument : It takes numpy.ndarray object as argument

Return : It returns numpy.ndarray object and integer value

Example 1:

 `# importing required libraries``import` `mahotas as mh``import` `numpy as np``from` `pylab ``import` `imshow, show`` ` `# creating region``# numpy.ndarray``regions ``=` `np.zeros((``8``, ``8``), ``bool``)`` ` `# setting 1 value to the region``regions[:``3``, :``3``] ``=` `1``regions[``6``:, ``6``:] ``=` `1`` ` `# getting labeled function``labeled, nr_objects ``=` `mh.label(regions)`` ` `# showing the image with interpolation = 'nearest'``imshow(labeled, interpolation ``=``'nearest'``)``show()`

Output : Example 2:

 `# importing required libraries``import` `mahotas as mh``import` `numpy as np``from` `pylab ``import` `imshow, show`` ` `# creating region``# numpy.ndarray``regions ``=` `np.zeros((``10``, ``10``), ``bool``)`` ` `# setting 1 value in the region``regions[``1``, ``1``] ``=` `1``regions[``6``, ``6``] ``=` `1``regions[``4``, ``4``] ``=` `1``regions[``9``, ``9``] ``=` `1`` ` `# getting labeled function``labeled, nr_objects ``=` `mh.label(regions)`` ` `# showing the image with interpolation = 'nearest'``imshow(labeled, interpolation ``=``'nearest'``)``show()`

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