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Practical OpenCV (Technology in Action) [Kindle Edition]

Samarth Brahmbhatt

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is a hands-on project book that shows you how to get the best results
from OpenCV, the open-source computer vision library.

Computer vision is key to technologies like object recognition, shape
detection, and depth estimation. OpenCV is an open-source library with over
2500 algorithms that you can use to do all of these, as well as track
moving objects, extract 3D models, and overlay augmented reality. It's
used by major companies like Google (in its autonomous car), Intel, and
Sony; and it is the backbone of the Robot Operating System’s computer vision capability.
In short, if you're working with computer vision at all, you need to know

With Practical OpenCV, you'll be able to:

  • Get OpenCV up and running on Windows
    or Linux.

  • Use OpenCV to control the camera board and
    run vision algorithms on Raspberry Pi.

  • Understand what goes on behind the
    scenes in computer vision applications like object detection, image stitching,
    filtering, stereo vision, and more.

  • Code complex computer vision
    projects for your class/hobby/robot/job, many of which can execute in real time
    on off-the-shelf processors.

  • Combine different modules that you
    develop to create your own interactive computer vision app.

What you’ll learn

  • The ins and outs of OpenCV programming on Windows and Linux

  • Transforming and filtering images

  • Detecting corners, edges, lines, and circles in images and video

  • Detecting pre-trained objects in images and video

  • Making panoramas by stitching images together

  • Getting depth information by using stereo cameras

  • Basic machine learning techniques

  • BONUS: Learn how to run OpenCV on Raspberry Pi

Who this book is for

This book is for programmers and makers with little or no previous exposure to computer vision. Some proficiency with C++ is required.


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Die hilfreichsten Kundenrezensionen auf (beta) 4.3 von 5 Sternen  6 Rezensionen
9 von 10 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A simple, concise and clear approach to OpenCV 23. Dezember 2013
Von Rudra - Veröffentlicht auf
Exactly what I needed!

I'm a hardcore MATlab user, and one of the few problems faced by people like me is computational time which is why I decided to shift to OpenCV.

I found this book to be extremely handy since a major portion of the book explains the programming with code, pictures and expected areas of failure. The best part is that the author has also provided sections on "Getting comfortable with OpenCV" and "Setting up OpenCV on your system". This makes things a whole easier. Let me tell you, installing OpenCV is a major blockade, and this book explains every single step in an orderly fashion.

Excellent job, Author, you have my thanks.
4 von 5 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen Very sloppy work. Not worth the cost. 17. Oktober 2014
Von Tom - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
Very disappointed by this book. Way over priced for the amount of information presented. However, what really gets to me is that while one can download all the code presented in the book, you find that it is a complete mess.

I tried to use the code given in chapter 11 of the book (for the raspberry pi) and first found it was miss-labeled as chapter 10, and then not only was the "cap.h" header file missing but the code for the first example (i.e. code10-1.cpp - which should be code11-1.cpp) not only doesn't compile but it references the OpenCV VideoCapture interface and not the PiCapture.cpp code. I mean did anyone even look it over. Feel completely ripped off!
2 von 2 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Very good cook book 29. Mai 2014
Von Andre L. B. Cunha - Veröffentlicht auf
Format:Taschenbuch|Verifizierter Kauf
It's a very good cookbook. The author shows all the essencial in Computer Vision using OpenCV, specially installing it. There are a lot of code in book, it's awesome! I recommended this book to beginner and intermediate level.
3 von 4 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Very useful and concise guide to OpenCV! 29. Januar 2014
Von Richa - Veröffentlicht auf
Format:Kindle Edition
The installation of OpenCV on Linux is quite challenging. There are numerous articles and blogs online, but its so hard to find one that works perfectly. Samarth explains OpenCV installation in detail, including one without super user privilege - a big plus!, alongside 32/64 bit installations. Highly commendable.
Even though OpenCV is optimized for Vision and is excruciatingly fast, especially compared to MATLAB, but due to its steep learning curve, there aren't many takers. This book covers most of the common Computer Vision problems, right from blurring Images to segmentation to Stereo Vision, with ample examples and code snippets. It definitely makes one comfortable to start programming with the OpenCV library. Chapter on Raspberry Pi is an added feature, for Raspberry Pi enthusiasts.
I will highly recommend this book for someone looking to get his hands dirty on OpenCV or for broadening the area or even as a quick reference.
1 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Intuitive even for a Non-comp science major student 7. März 2014
Von alok - Veröffentlicht auf
For any starter into the world of image processing, for fun or for research purposes, OpenCV invariably takes utmost importance and for very same reasons this book is invaluable. Being a mechanical engineering student, the book proved integral right from setting up OpenCV (trust me you may find related information in thousand of forums, but it wouldn't get any simpler than what's included in the text) to grasping concepts on stereo-vision. The layout of concepts and included programming tips (and sample codes) makes it incredibly intuitive to learn the fundamentals and I'm already seeing progress in implementing the same in my research. Specially, the section on embedded OpenCV using Raspberry pi has been wonderful to learn about practical considerations while taking your algorithm to the target system.
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