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453 lines
14 KiB
453 lines
14 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "seamless_cloning.hpp" |
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using namespace cv; |
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using namespace std; |
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void Cloning::computeGradientX( const Mat &img, Mat &gx) |
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{ |
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Mat kernel = Mat::zeros(1, 3, CV_8S); |
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kernel.at<char>(0,2) = 1; |
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kernel.at<char>(0,1) = -1; |
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if(img.channels() == 3) |
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{ |
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filter2D(img, gx, CV_32F, kernel); |
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} |
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else if (img.channels() == 1) |
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{ |
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filter2D(img, gx, CV_32F, kernel); |
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cvtColor(gx, gx, COLOR_GRAY2BGR); |
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} |
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} |
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void Cloning::computeGradientY( const Mat &img, Mat &gy) |
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{ |
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Mat kernel = Mat::zeros(3, 1, CV_8S); |
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kernel.at<char>(2,0) = 1; |
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kernel.at<char>(1,0) = -1; |
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if(img.channels() == 3) |
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{ |
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filter2D(img, gy, CV_32F, kernel); |
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} |
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else if (img.channels() == 1) |
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{ |
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filter2D(img, gy, CV_32F, kernel); |
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cvtColor(gy, gy, COLOR_GRAY2BGR); |
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} |
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} |
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void Cloning::computeLaplacianX( const Mat &img, Mat &laplacianX) |
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{ |
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Mat kernel = Mat::zeros(1, 3, CV_8S); |
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kernel.at<char>(0,0) = -1; |
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kernel.at<char>(0,1) = 1; |
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filter2D(img, laplacianX, CV_32F, kernel); |
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} |
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void Cloning::computeLaplacianY( const Mat &img, Mat &laplacianY) |
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{ |
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Mat kernel = Mat::zeros(3, 1, CV_8S); |
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kernel.at<char>(0,0) = -1; |
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kernel.at<char>(1,0) = 1; |
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filter2D(img, laplacianY, CV_32F, kernel); |
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} |
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void Cloning::dst(const Mat& src, Mat& dest, bool invert) |
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{ |
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Mat temp = Mat::zeros(src.rows, 2 * src.cols + 2, CV_32F); |
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int flag = invert ? DFT_ROWS + DFT_SCALE + DFT_INVERSE: DFT_ROWS; |
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src.copyTo(temp(Rect(1,0, src.cols, src.rows))); |
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for(int j = 0 ; j < src.rows ; ++j) |
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{ |
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float * tempLinePtr = temp.ptr<float>(j); |
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const float * srcLinePtr = src.ptr<float>(j); |
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for(int i = 0 ; i < src.cols ; ++i) |
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{ |
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tempLinePtr[src.cols + 2 + i] = - srcLinePtr[src.cols - 1 - i]; |
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} |
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} |
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Mat planes[] = {temp, Mat::zeros(temp.size(), CV_32F)}; |
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Mat complex; |
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merge(planes, 2, complex); |
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dft(complex, complex, flag); |
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split(complex, planes); |
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temp = Mat::zeros(src.cols, 2 * src.rows + 2, CV_32F); |
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for(int j = 0 ; j < src.cols ; ++j) |
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{ |
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float * tempLinePtr = temp.ptr<float>(j); |
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for(int i = 0 ; i < src.rows ; ++i) |
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{ |
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float val = planes[1].ptr<float>(i)[j + 1]; |
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tempLinePtr[i + 1] = val; |
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tempLinePtr[temp.cols - 1 - i] = - val; |
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} |
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} |
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Mat planes2[] = {temp, Mat::zeros(temp.size(), CV_32F)}; |
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merge(planes2, 2, complex); |
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dft(complex, complex, flag); |
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split(complex, planes2); |
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temp = planes2[1].t(); |
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temp(Rect( 0, 1, src.cols, src.rows)).copyTo(dest); |
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} |
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void Cloning::solve(const Mat &img, Mat& mod_diff, Mat &result) |
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{ |
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const int w = img.cols; |
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const int h = img.rows; |
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Mat res; |
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dst(mod_diff, res); |
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for(int j = 0 ; j < h-2; j++) |
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{ |
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float * resLinePtr = res.ptr<float>(j); |
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for(int i = 0 ; i < w-2; i++) |
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{ |
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resLinePtr[i] /= (filter_X[i] + filter_Y[j] - 4); |
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} |
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} |
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dst(res, mod_diff, true); |
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unsigned char * resLinePtr = result.ptr<unsigned char>(0); |
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const unsigned char * imgLinePtr = img.ptr<unsigned char>(0); |
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const float * interpLinePtr = NULL; |
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//first col |
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for(int i = 0 ; i < w ; ++i) |
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result.ptr<unsigned char>(0)[i] = img.ptr<unsigned char>(0)[i]; |
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for(int j = 1 ; j < h-1 ; ++j) |
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{ |
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resLinePtr = result.ptr<unsigned char>(j); |
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imgLinePtr = img.ptr<unsigned char>(j); |
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interpLinePtr = mod_diff.ptr<float>(j-1); |
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//first row |
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resLinePtr[0] = imgLinePtr[0]; |
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for(int i = 1 ; i < w-1 ; ++i) |
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{ |
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//saturate cast is not used here, because it behaves differently from the previous implementation |
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//most notable, saturate_cast rounds before truncating, here it's the opposite. |
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float value = interpLinePtr[i-1]; |
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if(value < 0.) |
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resLinePtr[i] = 0; |
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else if (value > 255.0) |
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resLinePtr[i] = 255; |
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else |
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resLinePtr[i] = static_cast<unsigned char>(value); |
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} |
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//last row |
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resLinePtr[w-1] = imgLinePtr[w-1]; |
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} |
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//last col |
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resLinePtr = result.ptr<unsigned char>(h-1); |
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imgLinePtr = img.ptr<unsigned char>(h-1); |
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for(int i = 0 ; i < w ; ++i) |
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resLinePtr[i] = imgLinePtr[i]; |
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} |
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void Cloning::poissonSolver(const Mat &img, Mat &laplacianX , Mat &laplacianY, Mat &result) |
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{ |
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const int w = img.cols; |
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const int h = img.rows; |
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Mat lap = laplacianX + laplacianY; |
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Mat bound = img.clone(); |
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rectangle(bound, Point(1, 1), Point(img.cols-2, img.rows-2), Scalar::all(0), -1); |
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Mat boundary_points; |
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Laplacian(bound, boundary_points, CV_32F); |
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boundary_points = lap - boundary_points; |
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Mat mod_diff = boundary_points(Rect(1, 1, w-2, h-2)); |
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solve(img,mod_diff,result); |
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} |
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void Cloning::initVariables(const Mat &destination, const Mat &binaryMask) |
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{ |
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destinationGradientX = Mat(destination.size(),CV_32FC3); |
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destinationGradientY = Mat(destination.size(),CV_32FC3); |
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patchGradientX = Mat(destination.size(),CV_32FC3); |
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patchGradientY = Mat(destination.size(),CV_32FC3); |
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binaryMaskFloat = Mat(binaryMask.size(),CV_32FC1); |
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binaryMaskFloatInverted = Mat(binaryMask.size(),CV_32FC1); |
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//init of the filters used in the dst |
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const int w = destination.cols; |
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filter_X.resize(w - 2); |
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double scale = CV_PI / (w - 1); |
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for(int i = 0 ; i < w-2 ; ++i) |
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filter_X[i] = 2.0f * (float)std::cos(scale * (i + 1)); |
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const int h = destination.rows; |
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filter_Y.resize(h - 2); |
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scale = CV_PI / (h - 1); |
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for(int j = 0 ; j < h - 2 ; ++j) |
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filter_Y[j] = 2.0f * (float)std::cos(scale * (j + 1)); |
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} |
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void Cloning::computeDerivatives(const Mat& destination, const Mat &patch, const Mat &binaryMask) |
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{ |
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initVariables(destination, binaryMask); |
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computeGradientX(destination, destinationGradientX); |
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computeGradientY(destination, destinationGradientY); |
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computeGradientX(patch, patchGradientX); |
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computeGradientY(patch, patchGradientY); |
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Mat Kernel(Size(3, 3), CV_8UC1); |
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Kernel.setTo(Scalar(1)); |
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erode(binaryMask, binaryMask, Kernel, Point(-1,-1), 3); |
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binaryMask.convertTo(binaryMaskFloat, CV_32FC1, 1.0/255.0); |
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} |
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void Cloning::scalarProduct(Mat mat, float r, float g, float b) |
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{ |
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vector <Mat> channels; |
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split(mat,channels); |
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multiply(channels[2],r,channels[2]); |
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multiply(channels[1],g,channels[1]); |
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multiply(channels[0],b,channels[0]); |
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merge(channels,mat); |
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} |
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void Cloning::arrayProduct(const cv::Mat& lhs, const cv::Mat& rhs, cv::Mat& result) const |
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{ |
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vector <Mat> lhs_channels; |
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vector <Mat> result_channels; |
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split(lhs,lhs_channels); |
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split(result,result_channels); |
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for(int chan = 0 ; chan < 3 ; ++chan) |
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multiply(lhs_channels[chan],rhs,result_channels[chan]); |
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merge(result_channels,result); |
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} |
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void Cloning::poisson(const Mat &destination) |
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{ |
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Mat laplacianX = destinationGradientX + patchGradientX; |
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Mat laplacianY = destinationGradientY + patchGradientY; |
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computeLaplacianX(laplacianX,laplacianX); |
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computeLaplacianY(laplacianY,laplacianY); |
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split(laplacianX,rgbx_channel); |
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split(laplacianY,rgby_channel); |
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split(destination,output); |
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for(int chan = 0 ; chan < 3 ; ++chan) |
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{ |
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poissonSolver(output[chan], rgbx_channel[chan], rgby_channel[chan], output[chan]); |
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} |
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} |
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void Cloning::evaluate(const Mat &I, const Mat &wmask, const Mat &cloned) |
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{ |
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bitwise_not(wmask,wmask); |
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wmask.convertTo(binaryMaskFloatInverted,CV_32FC1,1.0/255.0); |
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arrayProduct(destinationGradientX, binaryMaskFloatInverted, destinationGradientX); |
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arrayProduct(destinationGradientY, binaryMaskFloatInverted, destinationGradientY); |
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poisson(I); |
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merge(output,cloned); |
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} |
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void Cloning::normalClone(const Mat &destination, const Mat &patch, const Mat &binaryMask, Mat &cloned, int flag) |
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{ |
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const int w = destination.cols; |
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const int h = destination.rows; |
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const int channel = destination.channels(); |
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const int n_elem_in_line = w * channel; |
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computeDerivatives(destination,patch,binaryMask); |
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switch(flag) |
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{ |
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case NORMAL_CLONE: |
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arrayProduct(patchGradientX, binaryMaskFloat, patchGradientX); |
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arrayProduct(patchGradientY, binaryMaskFloat, patchGradientY); |
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break; |
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case MIXED_CLONE: |
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{ |
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AutoBuffer<int> maskIndices(n_elem_in_line); |
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for (int i = 0; i < n_elem_in_line; ++i) |
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maskIndices[i] = i / channel; |
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for(int i=0;i < h; i++) |
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{ |
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float * patchXLinePtr = patchGradientX.ptr<float>(i); |
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float * patchYLinePtr = patchGradientY.ptr<float>(i); |
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const float * destinationXLinePtr = destinationGradientX.ptr<float>(i); |
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const float * destinationYLinePtr = destinationGradientY.ptr<float>(i); |
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const float * binaryMaskLinePtr = binaryMaskFloat.ptr<float>(i); |
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for(int j=0; j < n_elem_in_line; j++) |
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{ |
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int maskIndex = maskIndices[j]; |
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if(abs(patchXLinePtr[j] - patchYLinePtr[j]) > |
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abs(destinationXLinePtr[j] - destinationYLinePtr[j])) |
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{ |
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patchXLinePtr[j] *= binaryMaskLinePtr[maskIndex]; |
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patchYLinePtr[j] *= binaryMaskLinePtr[maskIndex]; |
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} |
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else |
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{ |
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patchXLinePtr[j] = destinationXLinePtr[j] |
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* binaryMaskLinePtr[maskIndex]; |
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patchYLinePtr[j] = destinationYLinePtr[j] |
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* binaryMaskLinePtr[maskIndex]; |
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} |
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} |
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} |
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} |
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break; |
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case MONOCHROME_TRANSFER: |
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Mat gray; |
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cvtColor(patch, gray, COLOR_BGR2GRAY ); |
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computeGradientX(gray,patchGradientX); |
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computeGradientY(gray,patchGradientY); |
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arrayProduct(patchGradientX, binaryMaskFloat, patchGradientX); |
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arrayProduct(patchGradientY, binaryMaskFloat, patchGradientY); |
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break; |
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} |
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evaluate(destination,binaryMask,cloned); |
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} |
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void Cloning::localColorChange(Mat &I, Mat &mask, Mat &wmask, Mat &cloned, float red_mul=1.0, |
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float green_mul=1.0, float blue_mul=1.0) |
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{ |
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computeDerivatives(I,mask,wmask); |
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arrayProduct(patchGradientX,binaryMaskFloat, patchGradientX); |
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arrayProduct(patchGradientY,binaryMaskFloat, patchGradientY); |
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scalarProduct(patchGradientX,red_mul,green_mul,blue_mul); |
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scalarProduct(patchGradientY,red_mul,green_mul,blue_mul); |
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evaluate(I,wmask,cloned); |
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} |
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void Cloning::illuminationChange(Mat &I, Mat &mask, Mat &wmask, Mat &cloned, float alpha, float beta) |
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{ |
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CV_INSTRUMENT_REGION(); |
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computeDerivatives(I,mask,wmask); |
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arrayProduct(patchGradientX,binaryMaskFloat, patchGradientX); |
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arrayProduct(patchGradientY,binaryMaskFloat, patchGradientY); |
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Mat mag; |
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magnitude(patchGradientX,patchGradientY,mag); |
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Mat multX, multY, multx_temp, multy_temp; |
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multiply(patchGradientX,pow(alpha,beta),multX); |
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pow(mag,-1*beta, multx_temp); |
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multiply(multX,multx_temp, patchGradientX); |
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patchNaNs(patchGradientX); |
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multiply(patchGradientY,pow(alpha,beta),multY); |
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pow(mag,-1*beta, multy_temp); |
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multiply(multY,multy_temp,patchGradientY); |
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patchNaNs(patchGradientY); |
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Mat zeroMask = (patchGradientX != 0); |
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patchGradientX.copyTo(patchGradientX, zeroMask); |
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patchGradientY.copyTo(patchGradientY, zeroMask); |
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evaluate(I,wmask,cloned); |
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} |
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void Cloning::textureFlatten(Mat &I, Mat &mask, Mat &wmask, float low_threshold, |
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float high_threshold, int kernel_size, Mat &cloned) |
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{ |
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computeDerivatives(I,mask,wmask); |
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Mat out; |
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Canny(mask,out,low_threshold,high_threshold,kernel_size); |
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Mat zeros = Mat::zeros(patchGradientX.size(), CV_32FC3); |
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Mat zerosMask = (out != 255); |
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zeros.copyTo(patchGradientX, zerosMask); |
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zeros.copyTo(patchGradientY, zerosMask); |
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arrayProduct(patchGradientX,binaryMaskFloat, patchGradientX); |
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arrayProduct(patchGradientY,binaryMaskFloat, patchGradientY); |
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evaluate(I,wmask,cloned); |
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}
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