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

OpenGL support


OpenCV includes OpenGL support. OpenGL is a graphical library integrated in almost all graphical cards as a standard. OpenGL allows us to draw 2D up to complex 3D scenes. OpenCV includes OpenGL support due to the importance of representing 3D spaces in a number of tasks. To allow window support in OpenGL, we have to set up the WINDOW_OPENGLflag when we create the window using the namedWindow call.

The following code creates a window with OpenGL support and draws a rotate plane where we are going to show the web camera frames:

Mat frame; 
GLfloat angle= 0.0; 
GLuint texture;  
VideoCapture camera; 
 
int loadTexture() { 
 
    if (frame.data==NULL) return -1; 

   glBindTexture(GL_TEXTURE_2D, texture);  
   glTexParameteri(GL_TEXTURE_2D,GL_TEXTURE_MAG_FILTER,GL_LINEAR); 
   glTexParameteri(GL_TEXTURE_2D,GL_TEXTURE_MIN_FILTER,GL_LINEAR); 
   glPixelStorei(GL_UNPACK_ALIGNMENT, 1); 
 
   glTexImage2D(GL_TEXTURE_2D, 0, GL_RGB, frame.cols, frame.rows,0, GL_BGR, GL_UNSIGNED_BYTE, frame...