howeversome specialized equipment (mostly in scientific fieldscan take images with more bit resolution or bits are common mahotas can deal with all these typesincluding floating point images (not all operations make sense with floating point numbersbut when they domahotas supports themin many computationseven if the original data is composed of unsigned integersit is advantageous to convert to floating point numbers in order to simplify handling of rounding and overflow issues mahotas can use variety of different input/output backends unfortunatelynone of them can load all existing image formats (there are hundredswith several variations of eachhoweverloading png and jpeg images is supported by all of them we will focus on these common formats and refer you to the mahotas documentation on how to read uncommon formats the return value of mh imread is numpy array this means that you can use standard numpy functionalities to work with images for exampleit is often useful to subtract the mean value of the image from it this can help to normalize images taken under different lighting conditions and can be accomplished with the standard mean methodimage image image mean(we can display the image on screen using maplotlibthe plotting library we have already used several timesfrom matplotlib import pyplot as plt plt imshow(imageplt show(this shows the image using the convention that the first dimension is the height and the second the width it correctly handles color images as well when using python for numerical computationwe benefit from the whole ecosystem working well together basic image processing we will start with small dataset that was collected especially for this book it has three classesbuildingsnatural scenes (landscapes)and pictures of texts there are images in each categoryand they were all taken using cell phone camera with minimal compositionso the images are similar to those that would be uploaded to modern website this dataset is available from the book' website later in the we will look at harder dataset with more images and more categories