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Mahotas – Full Histogram of Image
• Last Updated : 10 Jul, 2020

In this article we will see how we can histogram of the image in mahotas. An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance.

In this tutorial we will use “lena” image, below is the command to load it.

`mahotas.demos.load('lena')`

Below is the lena image In order to do this we will use `mahotas.fullhistogram` method

Syntax : mahotas.fullhistogram(img)

Argument : It takes image object as argument

Return : It returns ndarray of type np.uint32

Note : Input image should be filtered or should be loaded as grey

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]`

Below is the implementation

 `# importing required libraries``import` `mahotas``import` `mahotas.demos``from` `pylab ``import` `gray, imshow, show``import` `numpy as np``import` `matplotlib.pyplot as plt``   ` `# loading iamge``img ``=` `mahotas.demos.load(``'lena'``)`` ` ` ` `   ` `# filtering image``img ``=` `img.``max``(``2``)`` ` `print``(``"Image"``)``   ` `# showing image``imshow(img)``show()`` ` `# Computing histogram``value ``=` `mahotas.fullhistogram(img)``  ` `# showing histograph``plt.hist(value)`

Output :

`Image` ```(array([82., 50., 34., 21., 24., 16.,  9.,  6.,  9.,  5.]),
array([   0.,  391.9,  783.8, 1175.7, 1567.6, 1959.5, 2351.4, 2743.3,
3135.2, 3527.1, 3919. ]),
a list of 10 Patch objects)``` Another example

 `# importing required libraries``import` `mahotas``import` `numpy as np``from` `pylab ``import` `gray, imshow, show``import` `os``import` `matplotlib.pyplot as plt``  ` `# loading iamge``img ``=` `mahotas.imread(``'dog_image.png'``)`` ` ` ` `# fltering image``img ``=` `img[:, :, ``0``]``   ` `print``(``"Image"``)``   ` `# showing image``imshow(img)``show()`` ` `# Computing histogram``value ``=` `mahotas.fullhistogram(img)``  ` `# showing histograph``plt.hist(value)`

Output :

`Image` ```(array([27., 29., 56., 20., 23., 41., 21., 23., 10.,  6.]),
array([1.0000e+00, 4.4780e+02, 8.9460e+02, 1.3414e+03, 1.7882e+03,
2.2350e+03, 2.6818e+03, 3.1286e+03, 3.5754e+03, 4.0222e+03,
4.4690e+03]),
a list of 10 Patch objects>``` Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

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