Book Image

Computer Vision with OpenCV 3 and Qt5

By : Amin Ahmadi Tazehkandi
4 (1)
Book Image

Computer Vision with OpenCV 3 and Qt5

4 (1)
By: Amin Ahmadi Tazehkandi

Overview of this book

Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment. This book will teach you to develop applications with the combination of OpenCV 3 and Qt5, and how to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book. Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications.
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Foreword
Contributors
Preface

Foreword

Around 20 years ago, when I was graduating from university, development of large and complex applications that included a graphical user interface was a time-consuming and difficult task. The APIs and tools that existed at that time to create those applications were difficult to use and understand. Creating applications for multiple platforms required writing a large part of it several times.

It was at that time that I discovered Qt, a framework that fixed both of these problems. It came with an easy-to-use, intuitive API and worked across all major desktop operating systems. Suddenly, programming these applications went from being hard work to something I really enjoyed. I wasn't limited to one operating system anymore—I could have my application running on multiple operating systems with a simple recompile. Since then, many things have improved for application developers. Frameworks have put a lot more effort into having easy-to-use APIs. The operating system landscape has changed, and having APIs that are available cross-platform is more important than ever.

OpenCV has, over the last few years, evolved into the leading API for computer vision. It contains a large set of functionalities and algorithms that can be used for things such as face recognition, tracking camera or eye movements, track markers for augmented reality, and much more.

Qt has also, over the same period, turned into one of the leading cross-platform frameworks for application development. Its comprehensive feature set contains most of the functionality you will need to develop a complex graphical application.

Making Qt the best technology to create cross-platform applications has been my mission for the last 17 years. One of the goals has always been to make it easy to combine Qt with other technologies. This book gives you a great example on how this can be done.

Both Qt and OpenCV feature cross-platform C++ APIs, making it straightforward to use them together. By combining them, you will have a powerful set of tools at hand, making it easy to create applications that combine computer vision with a graphical user interface. I hope that this book will help you on your way to becoming an expert in both Qt and OpenCV.

Lars KnollQt Chief Maintainer and CTO at The Qt Company