Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Introducing the OpenCV user interface


OpenCV has its own cross-OS user interface that allows developers to create their own applications without the need to learn complex user interface libraries. The OpenCV user interface is basic, but it gives computer vision developers the basic functions to create and manage their software developments. All of them are native and optimized for real-time use.

OpenCV provides two user interface options:

  • A basic interface based on native user interfaces, cocoa or carbon for Mac OS X, and GTK for Linux or Windows user interfaces, selected by default when compiling OpenCV.
  • A slightly more advanced interface based on Qt library that is a cross-platform interface. You have to enable the Qt option manually in CMake before compiling OpenCV.

In the following screenshot, you can see the basic user interface window on the left, and the Qt user interface on the right: