Book Image

Qt 5 and OpenCV 4 Computer Vision Projects

By : Zhuo Qingliang
4 (1)
Book Image

Qt 5 and OpenCV 4 Computer Vision Projects

4 (1)
By: Zhuo Qingliang

Overview of this book

OpenCV and Qt have proven to be a winning combination for developing cross-platform computer vision applications. By leveraging their power, you can create robust applications with both an intuitive graphical user interface (GUI) and high-performance capabilities. This book will help you learn through a variety of real-world projects on image processing, face and text recognition, object detection, and high-performance computing. You’ll be able to progressively build on your skills by working on projects of increasing complexity. You’ll begin by creating an image viewer application, building a user interface from scratch by adding menus, performing actions based on key-presses, and applying other functions. As you progress, the book will guide you through using OpenCV image processing and modification functions to edit an image with filters and transformation features. In addition to this, you’ll explore the complex motion analysis and facial landmark detection algorithms, which you can use to build security and face detection applications. Finally, you’ll learn to use pretrained deep learning models in OpenCV and GPUs to filter images quickly. By the end of this book, you will have learned how to effectively develop full-fledged computer vision applications with OpenCV and Qt.
Table of Contents (11 chapters)

The Facetious application

Since the application we are going to create in this chapter will give us a lot of fun by applying funny masks onto detected faces in real time, I name the application Facetious. The first thing that the Facetious application could do is open a webcam and play the video feed from it. That is the work we had done in our Gazer application, which was built by us in the preceding chapter. So here, I will borrow the skeleton of the Gazer application as the basis of our new application. The plan is, first, we make a copy of Gazer, rename it to Facetious, delete the features about motion detecting and change the video recording feature into a new feature of photo taking. By doing so, we will get a simple and clean application onto which we can add our new features of faces and facial landmark detecting.

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