Open Source Computer Vision Library
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862 lines
32 KiB
862 lines
32 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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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, all rights reserved. |
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// Copyright (C) 2014, Itseez, Inc, 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 Intel Corporation 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 "precomp.hpp" |
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#include "opencl_kernels_imgproc.hpp" |
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#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7) |
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static IppStatus sts = ippInit(); |
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#endif |
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/****************************************************************************************\ |
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Sobel & Scharr Derivative Filters |
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\****************************************************************************************/ |
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namespace cv |
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{ |
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static void getScharrKernels( OutputArray _kx, OutputArray _ky, |
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int dx, int dy, bool normalize, int ktype ) |
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{ |
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const int ksize = 3; |
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CV_Assert( ktype == CV_32F || ktype == CV_64F ); |
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_kx.create(ksize, 1, ktype, -1, true); |
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_ky.create(ksize, 1, ktype, -1, true); |
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Mat kx = _kx.getMat(); |
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Mat ky = _ky.getMat(); |
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CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 ); |
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for( int k = 0; k < 2; k++ ) |
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{ |
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Mat* kernel = k == 0 ? &kx : &ky; |
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int order = k == 0 ? dx : dy; |
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int kerI[3]; |
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if( order == 0 ) |
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kerI[0] = 3, kerI[1] = 10, kerI[2] = 3; |
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else if( order == 1 ) |
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kerI[0] = -1, kerI[1] = 0, kerI[2] = 1; |
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Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]); |
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double scale = !normalize || order == 1 ? 1. : 1./32; |
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temp.convertTo(*kernel, ktype, scale); |
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} |
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} |
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static void getSobelKernels( OutputArray _kx, OutputArray _ky, |
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int dx, int dy, int _ksize, bool normalize, int ktype ) |
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{ |
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int i, j, ksizeX = _ksize, ksizeY = _ksize; |
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if( ksizeX == 1 && dx > 0 ) |
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ksizeX = 3; |
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if( ksizeY == 1 && dy > 0 ) |
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ksizeY = 3; |
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CV_Assert( ktype == CV_32F || ktype == CV_64F ); |
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_kx.create(ksizeX, 1, ktype, -1, true); |
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_ky.create(ksizeY, 1, ktype, -1, true); |
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Mat kx = _kx.getMat(); |
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Mat ky = _ky.getMat(); |
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if( _ksize % 2 == 0 || _ksize > 31 ) |
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CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" ); |
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std::vector<int> kerI(std::max(ksizeX, ksizeY) + 1); |
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CV_Assert( dx >= 0 && dy >= 0 && dx+dy > 0 ); |
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for( int k = 0; k < 2; k++ ) |
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{ |
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Mat* kernel = k == 0 ? &kx : &ky; |
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int order = k == 0 ? dx : dy; |
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int ksize = k == 0 ? ksizeX : ksizeY; |
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CV_Assert( ksize > order ); |
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if( ksize == 1 ) |
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kerI[0] = 1; |
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else if( ksize == 3 ) |
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{ |
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if( order == 0 ) |
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kerI[0] = 1, kerI[1] = 2, kerI[2] = 1; |
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else if( order == 1 ) |
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kerI[0] = -1, kerI[1] = 0, kerI[2] = 1; |
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else |
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kerI[0] = 1, kerI[1] = -2, kerI[2] = 1; |
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} |
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else |
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{ |
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int oldval, newval; |
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kerI[0] = 1; |
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for( i = 0; i < ksize; i++ ) |
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kerI[i+1] = 0; |
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for( i = 0; i < ksize - order - 1; i++ ) |
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{ |
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oldval = kerI[0]; |
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for( j = 1; j <= ksize; j++ ) |
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{ |
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newval = kerI[j]+kerI[j-1]; |
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kerI[j-1] = oldval; |
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oldval = newval; |
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} |
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} |
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for( i = 0; i < order; i++ ) |
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{ |
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oldval = -kerI[0]; |
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for( j = 1; j <= ksize; j++ ) |
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{ |
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newval = kerI[j-1] - kerI[j]; |
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kerI[j-1] = oldval; |
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oldval = newval; |
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} |
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} |
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} |
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Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]); |
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double scale = !normalize ? 1. : 1./(1 << (ksize-order-1)); |
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temp.convertTo(*kernel, ktype, scale); |
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} |
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} |
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} |
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void cv::getDerivKernels( OutputArray kx, OutputArray ky, int dx, int dy, |
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int ksize, bool normalize, int ktype ) |
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{ |
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if( ksize <= 0 ) |
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getScharrKernels( kx, ky, dx, dy, normalize, ktype ); |
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else |
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getSobelKernels( kx, ky, dx, dy, ksize, normalize, ktype ); |
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} |
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cv::Ptr<cv::FilterEngine> cv::createDerivFilter(int srcType, int dstType, |
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int dx, int dy, int ksize, int borderType ) |
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{ |
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Mat kx, ky; |
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getDerivKernels( kx, ky, dx, dy, ksize, false, CV_32F ); |
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return createSeparableLinearFilter(srcType, dstType, |
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kx, ky, Point(-1,-1), 0, borderType ); |
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} |
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#ifdef HAVE_IPP |
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namespace cv |
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{ |
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static bool IPPDerivScharr(InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, double scale, double delta, int borderType) |
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{ |
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#if IPP_VERSION_X100 >= 801 |
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if ((0 > dx) || (0 > dy) || (1 != dx + dy)) |
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return false; |
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if (fabs(delta) > FLT_EPSILON) |
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return false; |
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IppiBorderType ippiBorderType = ippiGetBorderType(borderType & (~BORDER_ISOLATED)); |
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if ((int)ippiBorderType < 0) |
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return false; |
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int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); |
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if (ddepth < 0) |
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ddepth = sdepth; |
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int dtype = CV_MAKETYPE(ddepth, cn); |
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Mat src = _src.getMat(); |
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if (0 == (BORDER_ISOLATED & borderType)) |
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{ |
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Size size; Point offset; |
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src.locateROI(size, offset); |
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if (0 < offset.x) |
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ippiBorderType = (IppiBorderType)(ippiBorderType | ippBorderInMemLeft); |
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if (0 < offset.y) |
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ippiBorderType = (IppiBorderType)(ippiBorderType | ippBorderInMemTop); |
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if (offset.x + src.cols < size.width) |
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ippiBorderType = (IppiBorderType)(ippiBorderType | ippBorderInMemRight); |
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if (offset.y + src.rows < size.height) |
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ippiBorderType = (IppiBorderType)(ippiBorderType | ippBorderInMemBottom); |
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} |
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bool horz = (0 == dx) && (1 == dy); |
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IppiSize roiSize = {src.cols, src.rows}; |
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_dst.create( _src.size(), dtype); |
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Mat dst = _dst.getMat(); |
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IppStatus sts = ippStsErr; |
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if ((CV_8U == stype) && (CV_16S == dtype)) |
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{ |
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int bufferSize = 0; Ipp8u *pBuffer; |
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if (horz) |
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{ |
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if (0 > ippiFilterScharrHorizMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp8u, ipp16s, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrHorizMaskBorder_8u16s_C1R(src.ptr(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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else |
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{ |
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if (0 > ippiFilterScharrVertMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp8u, ipp16s, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrVertMaskBorder_8u16s_C1R(src.ptr(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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ippsFree(pBuffer); |
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} |
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else if ((CV_16S == stype) && (CV_16S == dtype)) |
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{ |
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int bufferSize = 0; Ipp8u *pBuffer; |
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if (horz) |
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{ |
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if (0 > ippiFilterScharrHorizMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp16s, ipp16s, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrHorizMaskBorder_16s_C1R(src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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else |
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{ |
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if (0 > ippiFilterScharrVertMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp16s, ipp16s, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrVertMaskBorder_16s_C1R(src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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ippsFree(pBuffer); |
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} |
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else if ((CV_32F == stype) && (CV_32F == dtype)) |
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{ |
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int bufferSize = 0; Ipp8u *pBuffer; |
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if (horz) |
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{ |
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if (0 > ippiFilterScharrHorizMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp32f, ipp32f, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrHorizMaskBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, dst.ptr<Ipp32f>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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else |
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{ |
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if (0 > ippiFilterScharrVertMaskBorderGetBufferSize(roiSize, ippMskSize3x3, ipp32f, ipp32f, 1, &bufferSize)) |
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return false; |
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pBuffer = ippsMalloc_8u(bufferSize); |
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if (NULL == pBuffer) |
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return false; |
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sts = ippiFilterScharrVertMaskBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, dst.ptr<Ipp32f>(), (int)dst.step, roiSize, ippMskSize3x3, ippiBorderType, 0, pBuffer); |
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} |
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ippsFree(pBuffer); |
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if (sts < 0) |
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return false;; |
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if (FLT_EPSILON < fabs(scale - 1.0)) |
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sts = ippiMulC_32f_C1R(dst.ptr<Ipp32f>(), (int)dst.step, (Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, roiSize); |
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} |
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return (0 <= sts); |
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#else |
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CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ddepth); CV_UNUSED(dx); CV_UNUSED(dy); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType); |
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return false; |
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#endif |
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} |
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static bool IPPDerivSobel(InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType) |
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{ |
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if ((borderType != BORDER_REPLICATE) || ((3 != ksize) && (5 != ksize))) |
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return false; |
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if (fabs(delta) > FLT_EPSILON) |
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return false; |
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if (1 != _src.channels()) |
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return false; |
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int bufSize = 0; |
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cv::AutoBuffer<char> buffer; |
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Mat src = _src.getMat(), dst = _dst.getMat(); |
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if ( ddepth < 0 ) |
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ddepth = src.depth(); |
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IppiSize roi = {src.cols, src.rows}; |
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IppiMaskSize kernel = (IppiMaskSize)(ksize*10+ksize); |
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if (src.type() == CV_8U && dst.type() == CV_16S && scale == 1) |
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{ |
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if ((dx == 1) && (dy == 0)) |
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{ |
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if (0 > ippiFilterSobelNegVertGetBufferSize_8u16s_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelNegVertBorder_8u16s_C1R(src.ptr<Ipp8u>(), (int)src.step, |
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dst.ptr<Ipp16s>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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return true; |
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} |
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if ((dx == 0) && (dy == 1)) |
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{ |
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if (0 > ippiFilterSobelHorizGetBufferSize_8u16s_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelHorizBorder_8u16s_C1R(src.ptr<Ipp8u>(), (int)src.step, |
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dst.ptr<Ipp16s>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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return true; |
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} |
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#if !defined(HAVE_IPP_ICV_ONLY) |
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if ((dx == 2) && (dy == 0)) |
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{ |
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if (0 > ippiFilterSobelVertSecondGetBufferSize_8u16s_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelVertSecondBorder_8u16s_C1R(src.ptr<Ipp8u>(), (int)src.step, |
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dst.ptr<Ipp16s>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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return true; |
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} |
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if ((dx == 0) && (dy == 2)) |
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{ |
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if (0 > ippiFilterSobelHorizSecondGetBufferSize_8u16s_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelHorizSecondBorder_8u16s_C1R(src.ptr<Ipp8u>(), (int)src.step, |
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dst.ptr<Ipp16s>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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return true; |
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} |
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#endif |
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} |
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if (src.type() == CV_32F && dst.type() == CV_32F) |
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{ |
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#if 0 |
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if ((dx == 1) && (dy == 0)) |
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{ |
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if (0 > ippiFilterSobelNegVertGetBufferSize_32f_C1R(roi, kernel, &bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelNegVertBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, |
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dst.ptr<Ipp32f>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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if(scale != 1) |
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ippiMulC_32f_C1R(dst.ptr<Ipp32f>(), (int)dst.step, (Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, ippiSize(dst.cols*dst.channels(), dst.rows)); |
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return true; |
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} |
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if ((dx == 0) && (dy == 1)) |
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{ |
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if (0 > ippiFilterSobelHorizGetBufferSize_32f_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelHorizBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, |
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dst.ptr<Ipp32f>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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if(scale != 1) |
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ippiMulC_32f_C1R(dst.ptr<Ipp32f>(), (int)dst.step, (Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, ippiSize(dst.cols*dst.channels(), dst.rows)); |
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return true; |
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} |
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#endif |
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#if !defined(HAVE_IPP_ICV_ONLY) |
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if((dx == 2) && (dy == 0)) |
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{ |
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if (0 > ippiFilterSobelVertSecondGetBufferSize_32f_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelVertSecondBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, |
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dst.ptr<Ipp32f>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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if(scale != 1) |
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ippiMulC_32f_C1R(dst.ptr<Ipp32f>(), (int)dst.step, (Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, ippiSize(dst.cols*dst.channels(), dst.rows)); |
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return true; |
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} |
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if((dx == 0) && (dy == 2)) |
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{ |
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if (0 > ippiFilterSobelHorizSecondGetBufferSize_32f_C1R(roi, kernel,&bufSize)) |
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return false; |
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buffer.allocate(bufSize); |
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if (0 > ippiFilterSobelHorizSecondBorder_32f_C1R(src.ptr<Ipp32f>(), (int)src.step, |
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dst.ptr<Ipp32f>(), (int)dst.step, roi, kernel, |
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ippBorderRepl, 0, (Ipp8u*)(char*)buffer)) |
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return false; |
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if(scale != 1) |
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ippiMulC_32f_C1R(dst.ptr<Ipp32f>(), (int)dst.step, (Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, ippiSize(dst.cols*dst.channels(), dst.rows)); |
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return true; |
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} |
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#endif |
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} |
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return false; |
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} |
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static bool ipp_sobel(InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType) |
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{ |
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if (ksize < 0) |
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{ |
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if (IPPDerivScharr(_src, _dst, ddepth, dx, dy, scale, delta, borderType)) |
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return true; |
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} |
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else if (0 < ksize) |
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{ |
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if (IPPDerivSobel(_src, _dst, ddepth, dx, dy, ksize, scale, delta, borderType)) |
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return true; |
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} |
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return false; |
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} |
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} |
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#endif |
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void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, |
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int ksize, double scale, double delta, int borderType ) |
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{ |
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int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); |
|
if (ddepth < 0) |
|
ddepth = sdepth; |
|
int dtype = CV_MAKE_TYPE(ddepth, cn); |
|
_dst.create( _src.size(), dtype ); |
|
|
|
#ifdef HAVE_TEGRA_OPTIMIZATION |
|
if (tegra::useTegra() && scale == 1.0 && delta == 0) |
|
{ |
|
Mat src = _src.getMat(), dst = _dst.getMat(); |
|
if (ksize == 3 && tegra::sobel3x3(src, dst, dx, dy, borderType)) |
|
return; |
|
if (ksize == -1 && tegra::scharr(src, dst, dx, dy, borderType)) |
|
return; |
|
} |
|
#endif |
|
|
|
CV_IPP_RUN(true, ipp_sobel(_src, _dst, ddepth, dx, dy, ksize, scale, delta, borderType)); |
|
|
|
int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); |
|
|
|
Mat kx, ky; |
|
getDerivKernels( kx, ky, dx, dy, ksize, false, ktype ); |
|
if( scale != 1 ) |
|
{ |
|
// usually the smoothing part is the slowest to compute, |
|
// so try to scale it instead of the faster differenciating part |
|
if( dx == 0 ) |
|
kx *= scale; |
|
else |
|
ky *= scale; |
|
} |
|
sepFilter2D( _src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType ); |
|
} |
|
|
|
|
|
void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, |
|
double scale, double delta, int borderType ) |
|
{ |
|
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); |
|
if (ddepth < 0) |
|
ddepth = sdepth; |
|
int dtype = CV_MAKETYPE(ddepth, cn); |
|
_dst.create( _src.size(), dtype ); |
|
|
|
#ifdef HAVE_TEGRA_OPTIMIZATION |
|
if (tegra::useTegra() && scale == 1.0 && delta == 0) |
|
{ |
|
Mat src = _src.getMat(), dst = _dst.getMat(); |
|
if (tegra::scharr(src, dst, dx, dy, borderType)) |
|
return; |
|
} |
|
#endif |
|
|
|
CV_IPP_RUN(true, IPPDerivScharr(_src, _dst, ddepth, dx, dy, scale, delta, borderType)); |
|
|
|
int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); |
|
|
|
Mat kx, ky; |
|
getScharrKernels( kx, ky, dx, dy, false, ktype ); |
|
if( scale != 1 ) |
|
{ |
|
// usually the smoothing part is the slowest to compute, |
|
// so try to scale it instead of the faster differenciating part |
|
if( dx == 0 ) |
|
kx *= scale; |
|
else |
|
ky *= scale; |
|
} |
|
sepFilter2D( _src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType ); |
|
} |
|
|
|
#ifdef HAVE_OPENCL |
|
|
|
namespace cv { |
|
|
|
#define LAPLACIAN_LOCAL_MEM(tileX, tileY, ksize, elsize) (((tileX) + 2 * (int)((ksize) / 2)) * (3 * (tileY) + 2 * (int)((ksize) / 2)) * elsize) |
|
|
|
static bool ocl_Laplacian5(InputArray _src, OutputArray _dst, |
|
const Mat & kd, const Mat & ks, double scale, double delta, |
|
int borderType, int depth, int ddepth) |
|
{ |
|
const size_t tileSizeX = 16; |
|
const size_t tileSizeYmin = 8; |
|
|
|
const ocl::Device dev = ocl::Device::getDefault(); |
|
|
|
int stype = _src.type(); |
|
int sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype), esz = CV_ELEM_SIZE(stype); |
|
|
|
bool doubleSupport = dev.doubleFPConfig() > 0; |
|
if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) |
|
return false; |
|
|
|
Mat kernelX = kd.reshape(1, 1); |
|
if (kernelX.cols % 2 != 1) |
|
return false; |
|
Mat kernelY = ks.reshape(1, 1); |
|
if (kernelY.cols % 2 != 1) |
|
return false; |
|
CV_Assert(kernelX.cols == kernelY.cols); |
|
|
|
size_t wgs = dev.maxWorkGroupSize(); |
|
size_t lmsz = dev.localMemSize(); |
|
size_t src_step = _src.step(), src_offset = _src.offset(); |
|
const size_t tileSizeYmax = wgs / tileSizeX; |
|
|
|
// workaround for Nvidia: 3 channel vector type takes 4*elem_size in local memory |
|
int loc_mem_cn = dev.vendorID() == ocl::Device::VENDOR_NVIDIA && cn == 3 ? 4 : cn; |
|
|
|
if (((src_offset % src_step) % esz == 0) && |
|
( |
|
(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE) || |
|
((borderType == BORDER_REFLECT || borderType == BORDER_WRAP || borderType == BORDER_REFLECT_101) && |
|
(_src.cols() >= (int) (kernelX.cols + tileSizeX) && _src.rows() >= (int) (kernelY.cols + tileSizeYmax))) |
|
) && |
|
(tileSizeX * tileSizeYmin <= wgs) && |
|
(LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeYmin, kernelX.cols, loc_mem_cn * 4) <= lmsz) |
|
) |
|
{ |
|
Size size = _src.size(), wholeSize; |
|
Point origin; |
|
int dtype = CV_MAKE_TYPE(ddepth, cn); |
|
int wdepth = CV_32F; |
|
|
|
size_t tileSizeY = tileSizeYmax; |
|
while ((tileSizeX * tileSizeY > wgs) || (LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeY, kernelX.cols, loc_mem_cn * 4) > lmsz)) |
|
{ |
|
tileSizeY /= 2; |
|
} |
|
size_t lt2[2] = { tileSizeX, tileSizeY}; |
|
size_t gt2[2] = { lt2[0] * (1 + (size.width - 1) / lt2[0]), lt2[1] }; |
|
|
|
char cvt[2][40]; |
|
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP", |
|
"BORDER_REFLECT_101" }; |
|
|
|
String opts = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUS=%d%s%s" |
|
" -D convertToWT=%s -D convertToDT=%s" |
|
" -D %s -D srcT1=%s -D dstT1=%s -D WT1=%s" |
|
" -D srcT=%s -D dstT=%s -D WT=%s" |
|
" -D CN=%d ", |
|
(int)lt2[0], (int)lt2[1], kernelX.cols / 2, |
|
ocl::kernelToStr(kernelX, wdepth, "KERNEL_MATRIX_X").c_str(), |
|
ocl::kernelToStr(kernelY, wdepth, "KERNEL_MATRIX_Y").c_str(), |
|
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]), |
|
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]), |
|
borderMap[borderType], |
|
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), ocl::typeToStr(wdepth), |
|
ocl::typeToStr(CV_MAKETYPE(sdepth, cn)), |
|
ocl::typeToStr(CV_MAKETYPE(ddepth, cn)), |
|
ocl::typeToStr(CV_MAKETYPE(wdepth, cn)), |
|
cn); |
|
|
|
ocl::Kernel k("laplacian", ocl::imgproc::laplacian5_oclsrc, opts); |
|
if (k.empty()) |
|
return false; |
|
UMat src = _src.getUMat(); |
|
_dst.create(size, dtype); |
|
UMat dst = _dst.getUMat(); |
|
|
|
int src_offset_x = static_cast<int>((src_offset % src_step) / esz); |
|
int src_offset_y = static_cast<int>(src_offset / src_step); |
|
|
|
src.locateROI(wholeSize, origin); |
|
|
|
k.args(ocl::KernelArg::PtrReadOnly(src), (int)src_step, src_offset_x, src_offset_y, |
|
wholeSize.height, wholeSize.width, ocl::KernelArg::WriteOnly(dst), |
|
static_cast<float>(scale), static_cast<float>(delta)); |
|
|
|
return k.run(2, gt2, lt2, false); |
|
} |
|
int iscale = cvRound(scale), idelta = cvRound(delta); |
|
bool floatCoeff = std::fabs(delta - idelta) > DBL_EPSILON || std::fabs(scale - iscale) > DBL_EPSILON; |
|
int wdepth = std::max(depth, floatCoeff ? CV_32F : CV_32S), kercn = 1; |
|
|
|
if (!doubleSupport && wdepth == CV_64F) |
|
return false; |
|
|
|
char cvt[2][40]; |
|
ocl::Kernel k("sumConvert", ocl::imgproc::laplacian5_oclsrc, |
|
format("-D ONLY_SUM_CONVERT " |
|
"-D srcT=%s -D WT=%s -D dstT=%s -D coeffT=%s -D wdepth=%d " |
|
"-D convertToWT=%s -D convertToDT=%s%s", |
|
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), |
|
ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)), |
|
ocl::typeToStr(CV_MAKE_TYPE(ddepth, kercn)), |
|
ocl::typeToStr(wdepth), wdepth, |
|
ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]), |
|
ocl::convertTypeStr(wdepth, ddepth, kercn, cvt[1]), |
|
doubleSupport ? " -D DOUBLE_SUPPORT" : "")); |
|
if (k.empty()) |
|
return false; |
|
|
|
UMat d2x, d2y; |
|
sepFilter2D(_src, d2x, depth, kd, ks, Point(-1, -1), 0, borderType); |
|
sepFilter2D(_src, d2y, depth, ks, kd, Point(-1, -1), 0, borderType); |
|
|
|
UMat dst = _dst.getUMat(); |
|
|
|
ocl::KernelArg d2xarg = ocl::KernelArg::ReadOnlyNoSize(d2x), |
|
d2yarg = ocl::KernelArg::ReadOnlyNoSize(d2y), |
|
dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn); |
|
|
|
if (wdepth >= CV_32F) |
|
k.args(d2xarg, d2yarg, dstarg, (float)scale, (float)delta); |
|
else |
|
k.args(d2xarg, d2yarg, dstarg, iscale, idelta); |
|
|
|
size_t globalsize[] = { dst.cols * cn / kercn, dst.rows }; |
|
return k.run(2, globalsize, NULL, false); |
|
} |
|
|
|
} |
|
|
|
#endif |
|
|
|
#if defined(HAVE_IPP) |
|
namespace cv |
|
{ |
|
static bool ipp_Laplacian(InputArray _src, OutputArray _dst, int ddepth, int ksize, |
|
double scale, double delta, int borderType) |
|
{ |
|
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); |
|
if (ddepth < 0) |
|
ddepth = sdepth; |
|
_dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) ); |
|
|
|
int iscale = saturate_cast<int>(scale), idelta = saturate_cast<int>(delta); |
|
bool floatScale = std::fabs(scale - iscale) > DBL_EPSILON, needScale = iscale != 1; |
|
bool floatDelta = std::fabs(delta - idelta) > DBL_EPSILON, needDelta = delta != 0; |
|
int borderTypeNI = borderType & ~BORDER_ISOLATED; |
|
Mat src = _src.getMat(), dst = _dst.getMat(); |
|
|
|
if (src.data != dst.data) |
|
{ |
|
Ipp32s bufsize; |
|
IppStatus status = (IppStatus)-1; |
|
IppiSize roisize = { src.cols, src.rows }; |
|
IppiMaskSize masksize = ksize == 3 ? ippMskSize3x3 : ippMskSize5x5; |
|
IppiBorderType borderTypeIpp = ippiGetBorderType(borderTypeNI); |
|
|
|
#define IPP_FILTER_LAPLACIAN(ippsrctype, ippdsttype, ippfavor) \ |
|
do \ |
|
{ \ |
|
if (borderTypeIpp >= 0 && ippiFilterLaplacianGetBufferSize_##ippfavor##_C1R(roisize, masksize, &bufsize) >= 0) \ |
|
{ \ |
|
Ipp8u * buffer = ippsMalloc_8u(bufsize); \ |
|
status = ippiFilterLaplacianBorder_##ippfavor##_C1R(src.ptr<ippsrctype>(), (int)src.step, dst.ptr<ippdsttype>(), \ |
|
(int)dst.step, roisize, masksize, borderTypeIpp, 0, buffer); \ |
|
ippsFree(buffer); \ |
|
} \ |
|
} while ((void)0, 0) |
|
|
|
CV_SUPPRESS_DEPRECATED_START |
|
if (sdepth == CV_8U && ddepth == CV_16S && !floatScale && !floatDelta) |
|
{ |
|
IPP_FILTER_LAPLACIAN(Ipp8u, Ipp16s, 8u16s); |
|
|
|
if (needScale && status >= 0) |
|
status = ippiMulC_16s_C1IRSfs((Ipp16s)iscale, dst.ptr<Ipp16s>(), (int)dst.step, roisize, 0); |
|
if (needDelta && status >= 0) |
|
status = ippiAddC_16s_C1IRSfs((Ipp16s)idelta, dst.ptr<Ipp16s>(), (int)dst.step, roisize, 0); |
|
} |
|
else if (sdepth == CV_32F && ddepth == CV_32F) |
|
{ |
|
IPP_FILTER_LAPLACIAN(Ipp32f, Ipp32f, 32f); |
|
|
|
if (needScale && status >= 0) |
|
status = ippiMulC_32f_C1IR((Ipp32f)scale, dst.ptr<Ipp32f>(), (int)dst.step, roisize); |
|
if (needDelta && status >= 0) |
|
status = ippiAddC_32f_C1IR((Ipp32f)delta, dst.ptr<Ipp32f>(), (int)dst.step, roisize); |
|
} |
|
CV_SUPPRESS_DEPRECATED_END |
|
|
|
if (status >= 0) |
|
return true; |
|
} |
|
|
|
#undef IPP_FILTER_LAPLACIAN |
|
return false; |
|
} |
|
} |
|
#endif |
|
|
|
|
|
void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize, |
|
double scale, double delta, int borderType ) |
|
{ |
|
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); |
|
if (ddepth < 0) |
|
ddepth = sdepth; |
|
_dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) ); |
|
|
|
CV_IPP_RUN((ksize == 3 || ksize == 5) && ((borderType & BORDER_ISOLATED) != 0 || !_src.isSubmatrix()) && |
|
((stype == CV_8UC1 && ddepth == CV_16S) || (ddepth == CV_32F && stype == CV_32FC1)) && (!cv::ocl::useOpenCL()), |
|
ipp_Laplacian(_src, _dst, ddepth, ksize, scale, delta, borderType)); |
|
|
|
|
|
#ifdef HAVE_TEGRA_OPTIMIZATION |
|
if (tegra::useTegra() && scale == 1.0 && delta == 0) |
|
{ |
|
Mat src = _src.getMat(), dst = _dst.getMat(); |
|
if (ksize == 1 && tegra::laplace1(src, dst, borderType)) |
|
return; |
|
if (ksize == 3 && tegra::laplace3(src, dst, borderType)) |
|
return; |
|
if (ksize == 5 && tegra::laplace5(src, dst, borderType)) |
|
return; |
|
} |
|
#endif |
|
|
|
if( ksize == 1 || ksize == 3 ) |
|
{ |
|
float K[2][9] = |
|
{ |
|
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 }, |
|
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 } |
|
}; |
|
Mat kernel(3, 3, CV_32F, K[ksize == 3]); |
|
if( scale != 1 ) |
|
kernel *= scale; |
|
filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType ); |
|
} |
|
else |
|
{ |
|
int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); |
|
int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F; |
|
int wtype = CV_MAKETYPE(wdepth, cn); |
|
Mat kd, ks; |
|
getSobelKernels( kd, ks, 2, 0, ksize, false, ktype ); |
|
|
|
CV_OCL_RUN(_dst.isUMat(), |
|
ocl_Laplacian5(_src, _dst, kd, ks, scale, |
|
delta, borderType, wdepth, ddepth)) |
|
|
|
const size_t STRIPE_SIZE = 1 << 14; |
|
Ptr<FilterEngine> fx = createSeparableLinearFilter(stype, |
|
wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() ); |
|
Ptr<FilterEngine> fy = createSeparableLinearFilter(stype, |
|
wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() ); |
|
|
|
Mat src = _src.getMat(), dst = _dst.getMat(); |
|
int y = fx->start(src), dsty = 0, dy = 0; |
|
fy->start(src); |
|
const uchar* sptr = src.ptr(y); |
|
|
|
int dy0 = std::min(std::max((int)(STRIPE_SIZE/(CV_ELEM_SIZE(stype)*src.cols)), 1), src.rows); |
|
Mat d2x( dy0 + kd.rows - 1, src.cols, wtype ); |
|
Mat d2y( dy0 + kd.rows - 1, src.cols, wtype ); |
|
|
|
for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy ) |
|
{ |
|
fx->proceed( sptr, (int)src.step, dy0, d2x.ptr(), (int)d2x.step ); |
|
dy = fy->proceed( sptr, (int)src.step, dy0, d2y.ptr(), (int)d2y.step ); |
|
if( dy > 0 ) |
|
{ |
|
Mat dstripe = dst.rowRange(dsty, dsty + dy); |
|
d2x.rows = d2y.rows = dy; // modify the headers, which should work |
|
d2x += d2y; |
|
d2x.convertTo( dstripe, ddepth, scale, delta ); |
|
} |
|
} |
|
} |
|
} |
|
|
|
///////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_IMPL void |
|
cvSobel( const void* srcarr, void* dstarr, int dx, int dy, int aperture_size ) |
|
{ |
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); |
|
|
|
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() ); |
|
|
|
cv::Sobel( src, dst, dst.depth(), dx, dy, aperture_size, 1, 0, cv::BORDER_REPLICATE ); |
|
if( CV_IS_IMAGE(srcarr) && ((IplImage*)srcarr)->origin && dy % 2 != 0 ) |
|
dst *= -1; |
|
} |
|
|
|
|
|
CV_IMPL void |
|
cvLaplace( const void* srcarr, void* dstarr, int aperture_size ) |
|
{ |
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); |
|
|
|
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() ); |
|
|
|
cv::Laplacian( src, dst, dst.depth(), aperture_size, 1, 0, cv::BORDER_REPLICATE ); |
|
} |
|
|
|
/* End of file. */
|
|
|