"Top man... I thought that I'd lived a colourful life until I read about Karl's adventures" - MICKEY THOMAS, WREXHAM AFC & WALES "Certified Twitter legend" - LADBIBLE Karl Phillips is just one of the lads - roofer by day, pilsner drinker by night. But as Bootlegger, he's scored hundreds of thousands of hits on YouTube with his hilarious matchday vlogs and keeps a huge number of followers on social media hooked with his humorous musings on life, work, the Flamethrower and his beloved Wrexham AFC. He even has a beer named after him - Wrexham Lager's iconic Bootlegger 1974 Pilsner, which has made its way onto the shelves of major supermarkets. From tough beginnings with teenage parents to a string of jobs in local factories, whether smearing butter on his headmaster's office window or getting a round of golf in during his shift as a street-cleaner, duckin' around shooting videos in football grounds and pubs across the UK or slightly overdoing it in holiday spots around the world, or in the throes of any of the other hilariously random antics described here, the Captain doesn't take himself too seriously and is mellowing with age, like a fine pilsner!

Blend the power of Qt with OpenCV to build cross-platform computer vision applications Key Features Start creating robust applications with the power of OpenCV and Qt combined Learn from scratch how to develop cross-platform computer vision applications Accentuate your OpenCV applications by developing them with Qt Book Description 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. What you will learn Get an introduction to Qt IDE and SDK Be introduced to OpenCV and see how to communicate between OpenCV and Qt Understand how to create UI using Qt Widgets Learn to develop cross-platform applications using OpenCV 3 and Qt 5 Explore the multithreaded application development features of Qt5 Improve OpenCV 3 application development using Qt5 Build, test, and deploy Qt and OpenCV apps, either dynamically or statically See Computer Vision technologies such as filtering and transformation of images, detecting and matching objects, template matching, object tracking, video and motion analysis, and much more Be introduced to QML and Qt Quick for iOS and Android application development Who this book is for This book is for readers interested in building computer vision applications. Intermediate knowledge of C++ programming is expected. Even though no knowledge of Qt5 and OpenCV 3 is assumed, if you're familiar with these frameworks, you'll benefit.