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Raspberry Pi Computer Vision Programming
Raspberry Pi Computer Vision Programming

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

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Profile Icon Ashwin Pajankar
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (4 Ratings)
Paperback Jun 2020 306 pages 2nd Edition
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Arrow left icon
Profile Icon Ashwin Pajankar
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (4 Ratings)
Paperback Jun 2020 306 pages 2nd Edition
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$17.99 $26.99
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Raspberry Pi Computer Vision Programming

Chapter 2: Preparing the Raspberry Pi for Computer Vision

In the previous chapter, we learned the fundamentals of single-board computers, computer vision, and OpenCV. We learned the detailed specifications of the Raspberry Pi (RPi) 4B and the RPi Zero W. We also learned how to set up Raspbian OS on all the RPi boards models in detail.

In this chapter, we will learn how to prepare our RPi board for computer vision. Continuing from where we left off in the previous chapter, we will start by installing the OpenCV library for computer vision and the other necessary software for remotely accessing the desktop, as well as Command Prompt. We will learn how to transfer files between an RPi and a Windows PC. We will also learn how to exploit the computation power of the RPi by overclocking it and installing a heatsink on it to reduce the temperature of the processor.

The topics that we'll cover in this chapter are as follows:

  • Remotely logging into the RPi with SSH
  • Remote...

Remotely logging into the RPi with SSH

We can remotely access the Command Prompt of the RPi board using various software from Windows. We can run all the Linux commands that do not involve the GUI remotely from Windows. As you may recall, we discussed how to enable SSH with the Raspberry Pi Configuration tool in Chapter 1, Introduction to Computer Vision and Raspberry Pi. It enables remote login through SSH.

In order to get started, follow these steps:

  1. First, we need to install any SSH software available for free. The most popular is PuTTY (https://www.putty.org/). I prefer to use another popular SSH client that comes with SFTP known as the Bitvise SSH client. You can download the installation file for Windows from https://www.bitvise.com/ssh-client-download and install it. After doing that, open the Bitvise SSH client. The following window will appear:

    Figure 2.1 – Bitwise Connection window

    Enter a hostname, username, and password. The hostname is nothing but the...

Remote desktop access

The Bitvise SSH client is great for file transfers and accessing the Command Prompt terminal of RPi. However, we need to use another piece of software to access the desktop of RPi remotely. There are two methods we can follow. The first one is VNC (we learned how to enable it in Chapter 1, Introduction to Computer Vision and Raspberry Pi, using the Raspberry Pi Configuration tool), while the other is using Windows' built-in Remote Desktop Connection utility. We can find it in the Windows search bar, as follows:


Figure 2.5 – Remote Desktop Connection option in the Windows search bar

But before we can use it, we need to install xrdp on the RPi. Installing it is very easy. We just need to run the following command at LXTerminal on the RPi:

sudo apt-get install xrdp -y

Information

You might want to read more about xrdp at http://xrdp.org/.

Once xrdp has been installed on the RPi, you need to follow these steps...

Installing OpenCV on an RPi board

Follow these steps to install OpenCV on the RPi:

  1. First, we need to install a few dependencies. Run the following command to install all these dependencies:
    sudo apt-get install -y libhdf5-dev libhdf5-serial-dev libatlas-base-dev libjasper-dev libqtgui4 libqt4-test
  2. Once the installation is successful, we can install OpenCV on the RPi:
    pip3 install opencv-python==4.0.1.24
  3. Once the installation of OpenCV is successful, we can verify it by running the following command:
    python3 -c "import cv2; print(cv2.__version__)"

    The following should be the output:

    4.0.1

This means that the installation is completed and that we can import OpenCV in our Python 3 programs.

Next, we will learn how to overclock the RPi 4B and how to install heatsink on it.

Heatsinks and overclocking RPi 4B

Overclocking means running the processors at higher speeds than those that are intended. When we overclock the processors, their temperature tends to rise and they radiate more heat. Raspberry Pi board models do not come with any built-in coolers. You can buy passive heatsinks from many online shops such as Amazon. The following is an example of a heatsink with a fan:

Figure 2.9 – Small heatsink for RPi

The heatsink fan can be powered by connecting it to a 5V or 3.3V power supply. The speed of the fan depends on the voltage, and we can connect it to the RPi power pins. We will learn more about the GPIO and the power pins of RPi in the next chapter. The best and the most effective heatsink that I found was the ICE Tower fan for the RPi 4B (https://www.seeedstudio.com/ICE-Tower-CPU-Cooling-Fan-for-Raspberry-pi-Support-Pi-4-p-4097.html).

The following is my own Pi with the ICE Tower mounted on it:

...

Summary

In this chapter, we learned how to remotely log into the RPi and how to access the RPi desktop remotely with RDP. We also learned how to install OpenCV and how to verify it. Also, we learned how to overclock an RPi board.

We will be using all the skills we learned in this chapter throughout this book for accessing the Command Prompt and desktop of Raspbian OS remotely while writing programs for computer vision. We will also use file transfer quite a few times, as well as the OpenCV library in most programs.

In the next chapter, we will learn the basics of Python, NumPy, matplotlib, and the RPi GPIO library. We will also learn about the SciPy ecosystem.

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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.

Who is this book for?

This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.

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

Product Details

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Publication date : Jun 29, 2020
Length: 306 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800207219
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Publication date : Jun 29, 2020
Length: 306 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800207219
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Table of Contents

14 Chapters
Chapter 1: Introduction to Computer Vision and the Raspberry Pi Chevron down icon Chevron up icon
Chapter 2: Preparing the Raspberry Pi for Computer Vision Chevron down icon Chevron up icon
Chapter 3: Introduction to Python Programming Chevron down icon Chevron up icon
Chapter 4: Getting Started with Computer Vision Chevron down icon Chevron up icon
Chapter 5: Basics of Image Processing Chevron down icon Chevron up icon
Chapter 6: Colorspaces, Transformations, and Thresholding Chevron down icon Chevron up icon
Chapter 7: Let's Make Some Noise Chevron down icon Chevron up icon
Chapter 8: High-Pass Filters and Feature Detection Chevron down icon Chevron up icon
Chapter 9: Image Restoration, Segmentation, and Depth Maps Chevron down icon Chevron up icon
Chapter 10: Histograms, Contours, and Morphological Transformations Chevron down icon Chevron up icon
Chapter 11: Real-Life Applications of Computer Vision Chevron down icon Chevron up icon
Chapter 12: Working with Mahotas and Jupyter Chevron down icon Chevron up icon
Chapter 13: Appendix Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8
(4 Ratings)
5 star 50%
4 star 0%
3 star 25%
2 star 25%
1 star 0%
Diane Lake Mar 17, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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 Amazon
L. Bell Oct 30, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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.
Amazon Verified review Amazon
Kindle Customer Sep 14, 2021
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
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.
Amazon Verified review Amazon
Justus Mar 26, 2022
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
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!
Amazon Verified review Amazon
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