人工智能 计算机视觉 sobel 算子opencv示例

ValidNum:XXX1000XXX ​#include "opencv2/imgproc.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" #include using namespace cv; using namespace std; int main( int argc, char** argv ) { cv::CommandLineParser parser(argc, argv, "{@input |lena.jpg|input image}" "{ksize k|1|ksize (hit 'K' to increase its value at run time)}" "{scale s|1|scale (hit 'S' to increase its value at run time)}" "{delta d|0|delta (hit 'D' to increase its value at run time)}" "{help h|false|show help message}"); cout << "The sample uses Sobel or Scharr OpenCV functions for edge detection\n\n"; parser.printMessage(); cout << "\nPress 'ESC' to exit program.\nPress 'R' to reset values ( ksize will be -1 equal to Scharr function )"; // First we declare the variables we are going to use Mat image,src, src_gray; Mat grad; const String window_name = "Sobel Demo - Simple Edge Detector"; int ksize = parser.get("ksize"); int scale = parser.get("scale"); int delta = parser.get("delta"); int ddepth = CV_16S; String imageName = parser.get("@input"); // As usual we load our source image (src) image = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Load an image // Check if image is loaded fine if( image.empty() ) { printf("Error opening image: %s\n", imageName.c_str()); return EXIT_FAILURE; } for (;;) { // Remove noise by blurring with a Gaussian filter ( kernel size = 3 ) GaussianBlur(image, src, Size(3, 3), 0, 0, BORDER_DEFAULT); // Convert the image to grayscale cvtColor(src, src_gray, COLOR_BGR2GRAY); Mat grad_x, grad_y; Mat abs_grad_x, abs_grad_y; Sobel(src_gray, grad_x, ddepth, 1, 0, ksize, scale, delta, BORDER_DEFAULT); Sobel(src_gray, grad_y, ddepth, 0, 1, ksize, scale, delta, BORDER_DEFAULT); // converting back to CV_8U convertScaleAbs(grad_x, abs_grad_x); convertScaleAbs(grad_y, abs_grad_y); addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad); imshow(window_name, grad); char key = (char)waitKey(0); if(key == 27) { return EXIT_SUCCESS; } if (key == 'k' || key == 'K') { ksize = ksize < 30 ? ksize+2 : -1; } if (key == 's' || key == 'S') { scale++; } if (key == 'd' || key == 'D') { delta++; } if (key == 'r' || key == 'R') { scale = 1; ksize = -1; delta = 0; } } return EXIT_SUCCESS; }

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