Book Image

Raspberry Pi Computer Vision Programming - Second Edition

By : Ashwin Pajankar
5 (1)
Book Image

Raspberry Pi Computer Vision Programming - Second Edition

5 (1)
By: Ashwin Pajankar

Overview of this book

Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects. At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision. By the end of this book, you'll be able to confidently build and deploy computer vision apps.
Table of Contents (15 chapters)

Summary

In this chapter, we explored the basics of Mahotas, which is a NumPy-based image processing library. We looked at a few image processing-related functions and learned how to combine Mahotas and OpenCV code for image processing. We also learned the names of other NumPy- and non-NumPy-based image processing libraries. You can explore those libraries further.

The last topic we learned about, the Jupyter Notebook, is very handy for quickly prototyping ideas and sharing code electronically. Many computer vision and data science professionals now use Jupyter notebooks for their Python programming projects.

In the Appendix section of this book, I have explained all the topics that I could not list under this chapter. These topics will be immensely useful to anyone who uses Raspberry Pi for various purposes.