/* * By downloading, copying, installing or using the software you agree to this license. * If you do not agree to this license, do not download, install, * copy or use the software. * * * License Agreement * For Open Source Computer Vision Library * (3 - clause BSD License) * * Redistribution and use in source and binary forms, with or without modification, * are permitted provided that the following conditions are met : * * * Redistributions of source code must retain the above copyright notice, * this list of conditions and the following disclaimer. * * * Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and / or other materials provided with the distribution. * * * Neither the names of the copyright holders nor the names of the contributors * may be used to endorse or promote products derived from this software * without specific prior written permission. * * This software is provided by the copyright holders and contributors "as is" and * any express or implied warranties, including, but not limited to, the implied * warranties of merchantability and fitness for a particular purpose are disclaimed. * In no event shall copyright holders or contributors be liable for any direct, * indirect, incidental, special, exemplary, or consequential damages * (including, but not limited to, procurement of substitute goods or services; * loss of use, data, or profits; or business interruption) however caused * and on any theory of liability, whether in contract, strict liability, * or tort(including negligence or otherwise) arising in any way out of * the use of this software, even if advised of the possibility of such damage. */ #include #include #include #include #include "opencv2/ximgproc/paillou_filter.hpp" using namespace cv; using namespace cv::ximgproc; #include using namespace std; int aa = 100, ww = 10; const char* window_name = "Gradient Modulus"; static void DisplayImage(Mat x,string s) { vector sx; split(x, sx); vector minVal(3), maxVal(3); for (int i = 0; i < static_cast(sx.size()); i++) { minMaxLoc(sx[i], &minVal[i], &maxVal[i]); } maxVal[0] = *max_element(maxVal.begin(), maxVal.end()); minVal[0] = *min_element(minVal.begin(), minVal.end()); Mat uc; x.convertTo(uc, CV_8U,255/(maxVal[0]-minVal[0]),-255*minVal[0]/(maxVal[0]-minVal[0])); imshow(s, uc); } /** * @function paillouFilter * @brief Trackbar callback */ static void PaillouFilter(int, void*pm) { Mat img = *((Mat*)pm); Mat dst; double a=aa/100.0, w=ww/100.0; Mat rx,ry; GradientPaillouX(img, rx, a, w); GradientPaillouY(img, ry, a, w); DisplayImage(rx, "Gx"); DisplayImage(ry, "Gy"); add(rx.mul(rx), ry.mul(ry), dst); sqrt(dst, dst); DisplayImage(dst, window_name ); } int main(int argc, char* argv[]) { if (argc < 2) { cout << "usage: paillou_demo [image]" << endl; return 1; } Mat img = imread(argv[1]); if (img.empty()) { cout << "File not found or empty image\n"; return 1; } imshow("Original",img); namedWindow( window_name, WINDOW_AUTOSIZE ); /// Create a Trackbar for user to enter threshold createTrackbar( "a:",window_name, &aa, 400, PaillouFilter, &img ); createTrackbar( "w:", window_name, &ww, 400, PaillouFilter, &img ); PaillouFilter(0, &img); waitKey(); return 0; }