Book Image

Mastering Python 2E - Second Edition

By : Rick van Hattem
5 (1)
Book Image

Mastering Python 2E - Second Edition

5 (1)
By: Rick van Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
19
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Index

Image processing

Image processing is an essential part of many types of machine learning, such as computer vision (CV), so it is essential that we show you a few of the options and their possibilities here. These range from image-only libraries to libraries that have full machine learning capabilities while also supporting image inputs.

scikit-image

The scikit-image (skimage) library is part of the scikit project with the main project being scikit-learn (sklearn), covered later in this chapter. It offers a range of functions for reading, processing, transforming, and generating images. The library builds on scipy.ndimage, which provides several image processing options as well.

We need to talk about what an image is in terms of these Python libraries first. In the case of scipy (and consequently, skimage), an image is a numpy.ndarray object with 2 or more dimensions. The conventions are:

  • 2D grayscale: Row, column
  • 2D color (for example, RGB): Row, column...