There has never been a better time to be a software developer than now. Just look around you and, most probably, you'll see at least a couple of different devices such as computers, smartphones, smart watches, or tablets running some applications on them that help you with various daily tasks or entertain you with music, movies, video games, and so on. Every year, hundreds of new devices are introduced into the market and new versions of operating systems are required to keep up with them in order to provide better interfaces for application developers to create software that makes better use of the underlying resources such as high-resolution displays, various sensors, and so on. As a consequence, software development frameworks have to adapt to and support the ever growing number of platforms. Considering this, Qt is probably one of the most successful cross-platform software development frameworks that offers power, speed, flexibility and ease of use, all at the same time, and it is a top choice when it comes to creating software that needs to look appealing and consistent across a wide range of platforms.
In recent years, and especially with the rise of more powerful processors at lower costs, the role of desktop computers and their handheld counterparts has shifted toward performing the more demanding and complex tasks such as computer vision. Whether it is for intelligent movie or photo editing, securing a sensitive building, counting objects in a production line, or detecting traffic signs, lanes, or pedestrians by an autonomous car, computer vision is being used more and more to solve such real-time problems that once were expected to be solved only by humans. This is where OpenCV Framework enters the scene. In the past few years, OpenCV has grown into a full-fledged cross-platform computer vision framework, with a focus on speed and performance. All around the world, developers and researchers are using OpenCV to realize their computer vision application ideas and algorithms.
This book aims to get you to grips with both Qt and OpenCV frameworks by taking you through their basic concepts and taking you up to the point where you can easily continue on your own to develop and deliver computer vision applications across a wide range of platforms. The only assumption made for being able to easily follow the topics covered in this book is that you are familiar and comfortable with C++ programming concepts such as classes, templates, inheritance, and so on. Even though the tutorials, screenshots, and examples covered throughout the book are based on the Windows operating system, the difference on macOS and Linux operating systems are also mentioned wherever necessary.
This book is the result of months of hard work, and it would have not been possible without the invaluable help of Lawrence Veigas, for his perfect editing; Karl Phillip Buhr, for his honest and insightful reviews and comments; Parth Kothari, without whom this book would have not been a reality; and Zainab Bootwala, Prajakta Naik, Aaron Lazar, Supriya Thabe, Tiksha Sarang, Rekha Nair, Jason Monteiro, Nilesh Mohite, and everyone at Packt Publishing who helped create and deliver this book as it is to you, our readers from all around the world.
