opencv描边和浮雕基于Sobel

opencv描边和浮雕基于Sobel

代码：

/**
 * @file Sobel_Demo.cpp
 * @brief Sample code uses Sobel or Scharr OpenCV functions for edge detection
 * @author OpenCV team
 */

#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"

#include <iostream>

using namespace cv;
using namespace std;

/**
 * @function main
 */
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 )";

    //![variables]
    // 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<int>("ksize");
    int scale = parser.get<int>("scale");
    int delta = parser.get<int>("delta");
    int ddepth = CV_16S;
    //![variables]

    //![load]
    String imageName = parser.get<String>("@input");
    // As usual we load our source image (src)
    image = imread(samples::findFile("C:/Users/liyihang/Desktop/sc/out.png"), 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;
    }
    //![load]

    cout << "" << "first" << "---" << ksize << "---" << scale << "---" << delta << endl;

    for (;;)
    {
        //![reduce_noise]
        // Remove noise by blurring with a Gaussian filter ( kernel size = 3 )
        GaussianBlur(image, src, Size(3, 3), 0, 0, BORDER_DEFAULT);
        //![reduce_noise]

        //![convert_to_gray]
        // Convert the image to grayscale
        cvtColor(src, src_gray, COLOR_BGR2GRAY);
        //![convert_to_gray]

        //![sobel]
        /// Generate grad_x and grad_y
        Mat grad_x, grad_y;
        Mat abs_grad_x, abs_grad_y;

        /// Gradient X
        Sobel(src_gray, grad_x, ddepth, 1, 0, ksize, scale, delta, BORDER_DEFAULT);

        /// Gradient Y
        Sobel(src_gray, grad_y, ddepth, 0, 1, ksize, scale, delta, BORDER_DEFAULT);
        //![sobel]

        //![convert]
        // converting back to CV_8U
        convertScaleAbs(grad_x, abs_grad_x);
        convertScaleAbs(grad_y, abs_grad_y);
        //![convert]

        //![blend]
        /// Total Gradient (approximate)
        addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
        //![blend]

        //![display]
        imshow(window_name, grad);
        char key = (char)waitKey(0);
        //![display]

        cout << "" << key << "---" << ksize << "---" << scale << "---" << delta << endl;

        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;
}