OpenCV with Python Blueprints: Design and develop advanced computer vision projects using OpenCV with Python

Michael Beyeler (USD)

Michael Beyeler

$24.99 ~~$35.99~~

4.4 (10 Ratings)

eBook Oct 2015 230 pages 1st Edition

Michael Beyeler (USD)

Michael Beyeler

$24.99 ~~$35.99~~

4.4 (10 Ratings)

eBook Oct 2015 230 pages 1st Edition

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Design and develop advanced computer vision projects using OpenCV with Python About This Book Program advanced computer vision applications in Python using different features of the OpenCV library Practical end-to-end project covering an important computer vision problem All projects in the book include a step-by-step guide to create computer vision applications Who This Book Is For This book is for intermediate users of OpenCV who aim to master their skills by developing advanced practical applications. Readers are expected to be familiar with OpenCV’s concepts and Python libraries. Basic knowledge of Python programming is expected and assumed. What You Will Learn Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor Learn feature extraction and feature matching for tracking arbitrary objects of interest Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques Track visually salient objects by searching for and focusing on important regions of an image Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs) Recognize street signs using a multi-class adaptation of support vector machines (SVMs) Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features In Detail OpenCV is a native cross platform C++ Library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android. Developers using OpenCV build applications to process visual data; this can include live streaming data from a device like a camera, such as photographs or videos. OpenCV offers extensive libraries with over 500 functions This book demonstrates how to develop a series of intermediate to advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this book teach the reader how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization. By the end of this book, readers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications. Style and approach This book covers independent hands-on projects that teach important computer vision concepts like image processing and machine learning for OpenCV with multiple examples.

Who is this book for?

This book is for intermediate users of OpenCV who aim to master their skills by developing advanced practical applications. Readers are expected to be familiar with OpenCV&apos

What you will learn

Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning
Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor
Learn feature extraction and feature matching for tracking arbitrary objects of interest
Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques
Track visually salient objects by searching for and focusing on important regions of an image
Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs)
Recognize street signs using a multi-class adaptation of support vector machines (SVMs)
Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Amazon Customer May 17, 2016

"OpenCV with Python Blueprints" is a great introduction to intermediate and advanced OpenCV concepts. Technical, but not too much. It's really helpful if you want to build your own functional apps.The book focuses on the practical side of things: Every chapter describes a dedicated, stand-alone project from A-Z. I'm big on 3D scene reconstruction, so I really enjoyed the chapter about optic flow and structure-from-motion. For a book that has to cover a lot of breadth, I was impressed by how much detail was contained in just one chapter. You get a really good value here.I also liked the structure of the book a lot: At the beginning of a chapter, the author tells you the goal of the project and outlines how exactly to get there step-by-step. If there is some theory or background information you need, he will introduce the concepts and explain them using a simple example. Very easy to follow. Every chapter finishes with the finished app, so you know exactly what you'll get in the end.I highly recommend this book to anyone with the requisite background trying to get a better understanding of the more advanced OpenCV tools.

Amazon Verified review

Nick Nov 17, 2015

This book covers multiple computer vision algorithms used in the industry today. Beyeler focuses on a practical approach by providing detailed Python code to perform image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization.I particularly liked the last chapter on facial expression recognition using Haar Cascade Classifiers and multi-layer perceptrons, where the authors described very clearly their implementation and usage with openCV. Finally, having access to all the source code on Github is great and really useful in order to quickly test the models, and modify them yourself.I recommend this book for people who already have some experience with computer vision and who want to improve their skills by developing advanced practical applications with OpenCV.

charliesixpack Jun 13, 2016

I cannot get the code to work with either of the platforms I have tried. These are common platforms I would expect the code to be compatible with.Macbook Pro running OS X 10.11.5: The code in the book requires the wxPython package. The download "wxPython3.0-osx-3.0.2.0-cocoa-py2.7.dmg" simply does not install. This problem is documented and unresolved. An error message appears during install about the downloaded software not being found by the installer. Without this package the code is useless. This is not a problem with the book but without the package the book is useless.Raspberry Pi 3 with raspberry pi camera: The opencv function VideoCapture(0) does not work with the Raspberry Pi camera. So I spent a couple of days trying to get the equivalent picamera.capture in conjunction with picamera.array.PiRGBArray to work with the code by producing an equivalent numpy three dimensional array for the frame the code would work with. My syntax and data types check out but I get a runtime error "Failed to gain raw access to bitmap data." What does that mean?I am frustrated and disappointed that neither of my platforms can use the code in the book. If the book code worked with tweaking I would give it 5 stars.Update: I have finally gotten a wxPython frame to display from the pi camera on the Raspberry Pi by using the hint from G10DRAS on [...]So I am off and running and have revised my rating.

Amazon Customer Mar 25, 2016

Excellent book to build practical OpenCV projects! I'm still relatively new to OpenCV, but all examples are well laid out and easy to follow. The author does a good job explaining the concepts in detail and shows how they apply in real life. As a professional programmer, I especially love that you can just fork the code from GitHub and follow along. Strongly recommend to readers with basic knowledge of computer vision, machines learning, and Python!

JrB May 11, 2018

There a lot of information in this book. It is to the point. I think it is great for a beginner to semi-advanced users. Plenty of examples to help you really understand what is going on.

OpenCV with Python Blueprints: Design and develop advanced computer vision projects using OpenCV with Python

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