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OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. OpenCV contains over 2,500 optimized algorithms for real-time computer vision and is actively used by a large community of programmers, researchers, and industries worldwide.
The library has interfaces for C++, Python, Java, and MATLAB/Octave, and is widely used in various computer vision fields, such as:
- 2D and 3D image processing
- Facial recognition and face detection
- Object detection and recognition
- Machine learning
Here's a simple example using OpenCV in C++ to read and display an image:
Prerequisite: Install OpenCV for C++ on your system (e.g., by following the official installation guide).
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
int main(int argc, char** argv) {
if(argc != 2) {
std::cout << "Usage: display_image ImageToLoadAndDisplay" << std::endl;
return -1;
}
cv::Mat image;
image = cv::imread(argv[1], cv::IMREAD_COLOR);
if(!image.data) {
std::cout << "Could not open or find the image" << std::endl;
return -1;
}
cv::namedWindow("Display window", cv::WINDOW_AUTOSIZE);
cv::imshow("Display window", image);
cv::waitKey(0);
return 0;
}
This example reads an image from the given input path (argv[1]) and displays it in a window. The cv::imread() function is used to read the image, and the cv::imshow() function displays it in the created window.
Remember to compile the code, linking the necessary libraries:
g++ -o display_image display_image.cpp `pkg-config --cflags --libs opencv4`
And run the executable with an image path as an argument:
./display_image path/to/image.jpg
For more advanced examples and detailed documentation on how to use OpenCV, please visit the official OpenCV documentation.