Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
Table of Contents (12 chapters)

Accessing the webcam

To access a computer's webcam or camera device, you can simply call the open() function on a cv::VideoCapture object (OpenCV's method of accessing your camera device), and pass 0 as the default camera ID number. Some computers have multiple cameras attached, or they do not work with a default camera of 0, so it is common practice to allow the user to pass the desired camera number as a command-line argument, in case they want to try camera 1, 2, or -1, for example. We will also try to set the camera resolution to 640 x 480 using cv::VideoCapture::set() to run faster on high-resolution cameras.

Depending on your camera model, driver, or system, OpenCV might not change the properties of your camera. It is not important for this project, so don't worry if it does not work with your webcam.

You can put this code in the main() function of your main.cpp file:

auto cameraNumber = 0; 
if (argc> 1)
cameraNumber = atoi(argv[1]);

// Get access to the camera.
cv::VideoCapture camera;;
if (!camera.isOpened()) {
std::cerr<<"ERROR: Could not access the camera or video!"<< std::endl;

// Try to set the camera resolution.
camera.set(cv::CV_CAP_PROP_FRAME_WIDTH, 640);
camera.set(cv::CV_CAP_PROP_FRAME_HEIGHT, 480);

After the webcam has been initialized, you can grab the current camera image as a cv::Mat object (OpenCV's image container). You can grab each camera frame by using the C++ streaming operator from your cv::VideoCapture object in a cv::Mat object, just like if you were getting input from a console.

OpenCV makes it very easy to capture frames from a video file (such as an AVI or MP4 file) or network stream instead of a webcam. Instead of passing an integer such as, pass a string such as"my_video.avi") and then grab frames just like it was a webcam. The source code provided with this book has an initCamera() function that opens a webcam, video file, or network stream.