You're reading from Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

Product type Paperback

Published in May 2022

Last Updated in May 2022

Publisher Packt

ISBN-13 9781800207721

Length 710 pages

Edition 2nd Edition

Languages

Python

Tools

Dask

Concepts

Programming Language

Author (1):

Rick Hattem

View More author details

Table of Contents (21) Chapters

Preface

1. Getting Started – One Environment per Project FREE CHAPTER

2. Interactive Python Interpreters

3. Pythonic Syntax and Common Pitfalls

4. Pythonic Design Patterns

5. Functional Programming – Readability Versus Brevity

6. Decorators – Enabling Code Reuse by Decorating

7. Generators and Coroutines – Infinity, One Step at a Time

8. Metaclasses – Making Classes (Not Instances) Smarter

9. Documentation – How to Use Sphinx and reStructuredText

10. Testing and Logging – Preparing for Bugs

11. Debugging – Solving the Bugs

12. Performance – Tracking and Reducing Your Memory and CPU Usage

13. asyncio – Multithreading without Threads

14. Multiprocessing – When a Single CPU Core Is Not Enough

15. Scientific Python and Plotting

16. Artificial Intelligence

17. Extensions in C/C++, System Calls, and C/C++ Libraries

18. Packaging – Creating Your Own Libraries or Applications

19. Other Books You May Enjoy

20. 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...