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Key benefits

Explore the potential of computer vision with Raspberry Pi and Python programming

Perform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry Pi

Discover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications

Description

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.

What you will learn

Set up a Raspberry Pi for computer vision applications

Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV

Demonstrate arithmetical, logical, and other operations on images

Work with a USB webcam and the Raspberry Pi Camera Module

Implement low-pass and high-pass filters and understand their applications in image processing

Cover advanced techniques such as histogram equalization and morphological transformations

Create GUI apps with Python 3 and OpenCV

Perform machine learning with K-means clustering and image quantization

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Frequently bought together

Raspberry Pi Computer Vision Programming

$38.99

$51.99

Learning OpenCV 4 Computer Vision with Python 3

$49.99

Total $ 140.97

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Diane Lake Mar 17, 2021

I bought this book as an aid in a project I am developing using a Raspberry Pi. I chose the Pi because it is inexpensive but capable. My project is an automated telescope using the Pi and the Pi camera. I am new to the Pi and the Linux environment, but I have experience in software development.This book was very helpful for me because it covers a wide variety of computer vision topics and offers lots of well thought out code examples using Python, opencv, matplotlib, numpy and other computer vision software. I followed his examples on my RPi and found that they helped me get the format and arguments of opencv commands correctly to include little things like commas, parenthesis, brackets, optional arguments and the like. I have often noted that there is nothing as helpful in learning computer programming as a well commented simple example. Many books and user documents show code structure, but they are thin on examples or the examples are overly complex or arcane. The opencv documentation is not particularly friendly in those respects. He also has lots of tips for the user. I intend to use this book as a resource as I write the code for my project. He also helped me improve my basic understanding of the technical details of images and videos. So, thumbs up on a good and useful book.

Amazon Verified review

L. Bell Oct 30, 2020

This book was given to me by the publishing company in exchange for a fair review. I found that it is suitable for hobbyists or anyone looking to get started with Computer Vision on a Raspberry Pi, because it assumes no prior experience. The early chapters contain detailed instructions for installing and configuring Raspbian OS and OpenCV. The next several chapters teach the basics of OpenCV in detail, using algorithms that work well with constrained resources, as is the case when using a Raspberry Pi. The tutorial portion of the book concludes with some fun real-world projects including motion tracking and the chroma-key (i.e. green screen) effect. Attached are pictures from my implementation of those projects. The final chapter contains a discussion of Mahotas and Jupyter for readers who are still curious and want to expand their study of computer vision. Overall, the book contains a lot of code examples. The code is concise and easy to understand. There is link to the publisher’s GitHub repository where all of the code examples can be downloaded. The tutorials progress logically as each project builds on the concepts taught in previous tutorials. I did wish, however that the code had utilized color syntax highlighting, which would have made it easier to read. As a workaround, the reader can easily achieve this by viewing the code in an editor like Sublime or VS Code. I also wish there had been more real-word project examples as these projects are only contained in one of the final chapters. A similar book, Raspberry Pi for Computer Vision, from PyImageSearch has more real-world projects, but it is many times more expensive than this one. This book, therefore, offers good value for those who want to get started with Computer Vision on the Raspberry Pi, but not pay a lot of money up front.

Kindle Customer Sep 14, 2021

This book is OK, nothing special. Too much fluff at the beginning about the different versions of the Raspberry Pi and the basics of Python Programming. I also think the chapters on Raspberry PI GPIO pins and programming were unnecessary. There is so much more to Open CV that could have been covered in this book.

Justus Mar 26, 2022

I am really wondering who this book was written for.On its first pages, it tries to explain how to connect your system to the RPi. Considering the tons of different scenarios, i.e., which OS you are using and which cables you have at your hands, this in itself fills over 20 pages. But most notably, the author does not mention the ability to connect to the RPi without having it connected to a display once, which was the case for me (no cables and screen available). So a quick Google search helped me immediately; I should have spared myself these pages in the book in hindsight.This feeling of "I could have found that out more efficiently through another medium" spread through the book. Reasons are:-The author rarely explains algorithms and their underlying concepts, but just commands you to "use function X from library Y". Besides, the "programming" shown is superficial in itself.-In my paperback version, the images are not in color - what a no-go when trying to explain RGB computer vision algorithms!-The text is super repetitive and redundant, there are mistakes in code and language. Usually, when I prefer book over video, language is the key. This book doesn't prevail.In conclusion, you will not learn a lot from this book. Most of it could be covered in a 90-minutes computer science lecture. So, I advice you to better go ahead and look for a nice lecture; even a good youtube video will totally suffice to replace this book!And by the way, to answer my opening question, I just noticed that the Preface does give one:"This book is for Python 3 developers, computer vision professionals, and Raspberry Pi enthusiasts [...]" - Hell no, I couldn't agree less!

Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3 , Second Edition

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