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

Creating the graphical user interface


Before we start with the image processing algorithms, we create the main user interface for our application. We are going to use the Qt-based user interface to allow us to create single buttons. The application receives one input parameter to load the image to process, and we are going to create four buttons, as follows:

  • Show histogram
  • Equalize histogram
  • Lomography effect
  • Cartoonize effect

We can see the four results in the following screenshot:

Let's begin developing our project. First of all, we are going to include the OpenCV – required headers, define an image matrix to store the input image, and create a constant string to use the new command-line parser already available from OpenCV 3.0; in this constant, we allow only two input parameters, help and the required image input:

// OpenCV includes 
#include "opencv2/core/utility.hpp" 
#include "opencv2/imgproc.hpp" 
#include "opencv2/highgui.hpp" 
using namespace cv; 
// OpenCV command line parser functions...