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Tetragramm
GitHub Repository: Tetragramm/opencv
Path: blob/master/modules/imgproc/src/deriv.cpp
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/*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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#include "opencv2/core/openvx/ovx_defs.hpp"
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#include "filter.hpp"
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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_OPENVX
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namespace cv
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{
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namespace ovx {
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template <> inline bool skipSmallImages<VX_KERNEL_SOBEL_3x3>(int w, int h) { return w*h < 320 * 240; }
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}
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static bool openvx_sobel(InputArray _src, OutputArray _dst,
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int dx, int dy, int ksize,
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double scale, double delta, int borderType)
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{
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if (_src.type() != CV_8UC1 || _dst.type() != CV_16SC1 ||
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ksize != 3 || scale != 1.0 || delta != 0.0 ||
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(dx | dy) != 1 || (dx + dy) != 1 ||
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_src.cols() < ksize || _src.rows() < ksize ||
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ovx::skipSmallImages<VX_KERNEL_SOBEL_3x3>(_src.cols(), _src.rows())
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)
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return false;
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Mat src = _src.getMat();
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Mat dst = _dst.getMat();
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if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
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return false; //Process isolated borders only
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vx_enum border;
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switch (borderType & ~BORDER_ISOLATED)
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{
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case BORDER_CONSTANT:
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border = VX_BORDER_CONSTANT;
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break;
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case BORDER_REPLICATE:
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// border = VX_BORDER_REPLICATE;
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// break;
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default:
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return false;
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}
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try
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{
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ivx::Context ctx = ovx::getOpenVXContext();
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//if ((vx_size)ksize > ctx.convolutionMaxDimension())
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// return false;
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Mat a;
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if (dst.data != src.data)
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a = src;
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else
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src.copyTo(a);
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ivx::Image
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ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
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ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
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ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_S16,
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ivx::Image::createAddressing(dst.cols, dst.rows, 2, (vx_int32)(dst.step)), dst.data);
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//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
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//since OpenVX standard says nothing about thread-safety for now
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ivx::border_t prevBorder = ctx.immediateBorder();
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ctx.setImmediateBorder(border, (vx_uint8)(0));
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if(dx)
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ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, ib, NULL));
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else
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ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, NULL, ib));
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ctx.setImmediateBorder(prevBorder);
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}
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catch (ivx::RuntimeError & e)
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{
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VX_DbgThrow(e.what());
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}
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catch (ivx::WrapperError & e)
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{
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VX_DbgThrow(e.what());
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}
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return true;
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}
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}
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#endif
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#ifdef HAVE_IPP
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namespace cv
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{
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static bool ipp_Deriv(InputArray _src, OutputArray _dst, int dx, int dy, int ksize, double scale, double delta, int borderType)
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{
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#ifdef HAVE_IPP_IW
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CV_INSTRUMENT_REGION_IPP();
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::ipp::IwiSize size(_src.size().width, _src.size().height);
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IppDataType srcType = ippiGetDataType(_src.depth());
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IppDataType dstType = ippiGetDataType(_dst.depth());
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int channels = _src.channels();
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bool useScale = false;
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bool useScharr = false;
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if(channels != _dst.channels() || channels > 1)
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return false;
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if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON)
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useScale = true;
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if(ksize <= 0)
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{
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ksize = 3;
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useScharr = true;
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}
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IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize);
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if((int)maskSize < 0)
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return false;
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#if IPP_VERSION_X100 <= 201703
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// Bug with mirror wrap
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if(borderType == BORDER_REFLECT_101 && (ksize/2+1 > size.width || ksize/2+1 > size.height))
298
return false;
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#endif
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IwiDerivativeType derivType = ippiGetDerivType(dx, dy, (useScharr)?false:true);
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if((int)derivType < 0)
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return false;
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// Acquire data and begin processing
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try
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{
308
Mat src = _src.getMat();
309
Mat dst = _dst.getMat();
310
::ipp::IwiImage iwSrc = ippiGetImage(src);
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::ipp::IwiImage iwDst = ippiGetImage(dst);
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::ipp::IwiImage iwSrcProc = iwSrc;
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::ipp::IwiImage iwDstProc = iwDst;
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::ipp::IwiBorderSize borderSize(maskSize);
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::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
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if(!ippBorder)
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return false;
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if(srcType == ipp8u && dstType == ipp8u)
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{
321
iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
322
useScale = true;
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}
324
else if(srcType == ipp8u && dstType == ipp32f)
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{
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iwSrc -= borderSize;
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iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels);
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CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0, ::ipp::IwiScaleParams(ippAlgHintFast));
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iwSrcProc += borderSize;
330
}
331
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if(useScharr)
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CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterScharr, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder);
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else
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CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterSobel, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder);
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if(useScale)
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CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta, ::ipp::IwiScaleParams(ippAlgHintFast));
339
}
340
catch (const ::ipp::IwException &)
341
{
342
return false;
343
}
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return true;
346
#else
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CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(dx); CV_UNUSED(dy); CV_UNUSED(ksize); 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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}
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#endif
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#ifdef HAVE_OPENCL
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namespace cv
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{
357
static bool ocl_sepFilter3x3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
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InputArray _kernelX, InputArray _kernelY, double delta, int borderType)
359
{
360
const ocl::Device & dev = ocl::Device::getDefault();
361
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
362
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if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
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(_src.offset() == 0) && (_src.step() % 4 == 0) &&
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(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
366
return false;
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368
Mat kernelX = _kernelX.getMat().reshape(1, 1);
369
if (kernelX.cols % 2 != 1)
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return false;
371
Mat kernelY = _kernelY.getMat().reshape(1, 1);
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if (kernelY.cols % 2 != 1)
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return false;
374
375
if (ddepth < 0)
376
ddepth = sdepth;
377
378
Size size = _src.size();
379
size_t globalsize[2] = { 0, 0 };
380
size_t localsize[2] = { 0, 0 };
381
382
globalsize[0] = size.width / 16;
383
globalsize[1] = size.height / 2;
384
385
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
386
char build_opts[1024];
387
sprintf(build_opts, "-D %s %s%s", borderMap[borderType],
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ocl::kernelToStr(kernelX, CV_32F, "KERNEL_MATRIX_X").c_str(),
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ocl::kernelToStr(kernelY, CV_32F, "KERNEL_MATRIX_Y").c_str());
390
391
ocl::Kernel kernel("sepFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::sepFilter3x3_oclsrc, build_opts);
392
if (kernel.empty())
393
return false;
394
395
UMat src = _src.getUMat();
396
_dst.create(size, CV_MAKETYPE(ddepth, cn));
397
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
398
return false;
399
UMat dst = _dst.getUMat();
400
401
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
402
idxArg = kernel.set(idxArg, (int)src.step);
403
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
404
idxArg = kernel.set(idxArg, (int)dst.step);
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idxArg = kernel.set(idxArg, (int)dst.rows);
406
idxArg = kernel.set(idxArg, (int)dst.cols);
407
idxArg = kernel.set(idxArg, static_cast<float>(delta));
408
409
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
410
}
411
}
412
#endif
413
414
void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
415
int ksize, double scale, double delta, int borderType )
416
{
417
CV_INSTRUMENT_REGION();
418
419
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
420
if (ddepth < 0)
421
ddepth = sdepth;
422
int dtype = CV_MAKE_TYPE(ddepth, cn);
423
_dst.create( _src.size(), dtype );
424
425
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
426
427
Mat kx, ky;
428
getDerivKernels( kx, ky, dx, dy, ksize, false, ktype );
429
if( scale != 1 )
430
{
431
// usually the smoothing part is the slowest to compute,
432
// so try to scale it instead of the faster differentiating part
433
if( dx == 0 )
434
kx *= scale;
435
else
436
ky *= scale;
437
}
438
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CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && ksize == 3 &&
440
(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
441
ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
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443
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
444
ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), 0, borderType))
445
446
Mat src = _src.getMat();
447
Mat dst = _dst.getMat();
448
449
Point ofs;
450
Size wsz(src.cols, src.rows);
451
if(!(borderType & BORDER_ISOLATED))
452
src.locateROI( wsz, ofs );
453
454
CALL_HAL(sobel, cv_hal_sobel, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
455
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, ksize, scale, delta, borderType&~BORDER_ISOLATED);
456
457
CV_OVX_RUN(true,
458
openvx_sobel(src, dst, dx, dy, ksize, scale, delta, borderType))
459
460
CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, ksize, scale, delta, borderType));
461
462
sepFilter2D(src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType );
463
}
464
465
466
void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
467
double scale, double delta, int borderType )
468
{
469
CV_INSTRUMENT_REGION();
470
471
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
472
if (ddepth < 0)
473
ddepth = sdepth;
474
int dtype = CV_MAKETYPE(ddepth, cn);
475
_dst.create( _src.size(), dtype );
476
477
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
478
479
Mat kx, ky;
480
getScharrKernels( kx, ky, dx, dy, false, ktype );
481
if( scale != 1 )
482
{
483
// usually the smoothing part is the slowest to compute,
484
// so try to scale it instead of the faster differentiating part
485
if( dx == 0 )
486
kx *= scale;
487
else
488
ky *= scale;
489
}
490
491
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
492
(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
493
ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
494
495
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
496
(size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
497
ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), 0, borderType))
498
499
Mat src = _src.getMat();
500
Mat dst = _dst.getMat();
501
502
Point ofs;
503
Size wsz(src.cols, src.rows);
504
if(!(borderType & BORDER_ISOLATED))
505
src.locateROI( wsz, ofs );
506
507
CALL_HAL(scharr, cv_hal_scharr, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
508
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, scale, delta, borderType&~BORDER_ISOLATED);
509
510
CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, 0, scale, delta, borderType));
511
512
sepFilter2D( src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType );
513
}
514
515
#ifdef HAVE_OPENCL
516
517
namespace cv {
518
519
#define LAPLACIAN_LOCAL_MEM(tileX, tileY, ksize, elsize) (((tileX) + 2 * (int)((ksize) / 2)) * (3 * (tileY) + 2 * (int)((ksize) / 2)) * elsize)
520
521
static bool ocl_Laplacian5(InputArray _src, OutputArray _dst,
522
const Mat & kd, const Mat & ks, double scale, double delta,
523
int borderType, int depth, int ddepth)
524
{
525
const size_t tileSizeX = 16;
526
const size_t tileSizeYmin = 8;
527
528
const ocl::Device dev = ocl::Device::getDefault();
529
530
int stype = _src.type();
531
int sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype), esz = CV_ELEM_SIZE(stype);
532
533
bool doubleSupport = dev.doubleFPConfig() > 0;
534
if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
535
return false;
536
537
Mat kernelX = kd.reshape(1, 1);
538
if (kernelX.cols % 2 != 1)
539
return false;
540
Mat kernelY = ks.reshape(1, 1);
541
if (kernelY.cols % 2 != 1)
542
return false;
543
CV_Assert(kernelX.cols == kernelY.cols);
544
545
size_t wgs = dev.maxWorkGroupSize();
546
size_t lmsz = dev.localMemSize();
547
size_t src_step = _src.step(), src_offset = _src.offset();
548
const size_t tileSizeYmax = wgs / tileSizeX;
549
CV_Assert(src_step != 0 && esz != 0);
550
551
// workaround for NVIDIA: 3 channel vector type takes 4*elem_size in local memory
552
int loc_mem_cn = dev.vendorID() == ocl::Device::VENDOR_NVIDIA && cn == 3 ? 4 : cn;
553
if (((src_offset % src_step) % esz == 0) &&
554
(
555
(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE) ||
556
((borderType == BORDER_REFLECT || borderType == BORDER_WRAP || borderType == BORDER_REFLECT_101) &&
557
(_src.cols() >= (int) (kernelX.cols + tileSizeX) && _src.rows() >= (int) (kernelY.cols + tileSizeYmax)))
558
) &&
559
(tileSizeX * tileSizeYmin <= wgs) &&
560
(LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeYmin, kernelX.cols, loc_mem_cn * 4) <= lmsz)
561
&& OCL_PERFORMANCE_CHECK(!dev.isAMD()) // TODO FIXIT 2018: Problem with AMDGPU on Linux (2482.3)
562
)
563
{
564
Size size = _src.size(), wholeSize;
565
Point origin;
566
int dtype = CV_MAKE_TYPE(ddepth, cn);
567
int wdepth = CV_32F;
568
569
size_t tileSizeY = tileSizeYmax;
570
while ((tileSizeX * tileSizeY > wgs) || (LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeY, kernelX.cols, loc_mem_cn * 4) > lmsz))
571
{
572
tileSizeY /= 2;
573
}
574
size_t lt2[2] = { tileSizeX, tileSizeY};
575
size_t gt2[2] = { lt2[0] * (1 + (size.width - 1) / lt2[0]), lt2[1] };
576
577
char cvt[2][40];
578
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP",
579
"BORDER_REFLECT_101" };
580
581
String opts = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUS=%d%s%s"
582
" -D convertToWT=%s -D convertToDT=%s"
583
" -D %s -D srcT1=%s -D dstT1=%s -D WT1=%s"
584
" -D srcT=%s -D dstT=%s -D WT=%s"
585
" -D CN=%d ",
586
(int)lt2[0], (int)lt2[1], kernelX.cols / 2,
587
ocl::kernelToStr(kernelX, wdepth, "KERNEL_MATRIX_X").c_str(),
588
ocl::kernelToStr(kernelY, wdepth, "KERNEL_MATRIX_Y").c_str(),
589
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]),
590
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]),
591
borderMap[borderType],
592
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), ocl::typeToStr(wdepth),
593
ocl::typeToStr(CV_MAKETYPE(sdepth, cn)),
594
ocl::typeToStr(CV_MAKETYPE(ddepth, cn)),
595
ocl::typeToStr(CV_MAKETYPE(wdepth, cn)),
596
cn);
597
598
ocl::Kernel k("laplacian", ocl::imgproc::laplacian5_oclsrc, opts);
599
if (k.empty())
600
return false;
601
UMat src = _src.getUMat();
602
_dst.create(size, dtype);
603
UMat dst = _dst.getUMat();
604
605
int src_offset_x = static_cast<int>((src_offset % src_step) / esz);
606
int src_offset_y = static_cast<int>(src_offset / src_step);
607
608
src.locateROI(wholeSize, origin);
609
610
k.args(ocl::KernelArg::PtrReadOnly(src), (int)src_step, src_offset_x, src_offset_y,
611
wholeSize.height, wholeSize.width, ocl::KernelArg::WriteOnly(dst),
612
static_cast<float>(scale), static_cast<float>(delta));
613
614
return k.run(2, gt2, lt2, false);
615
}
616
int iscale = cvRound(scale), idelta = cvRound(delta);
617
bool floatCoeff = std::fabs(delta - idelta) > DBL_EPSILON || std::fabs(scale - iscale) > DBL_EPSILON;
618
int wdepth = std::max(depth, floatCoeff ? CV_32F : CV_32S), kercn = 1;
619
620
if (!doubleSupport && wdepth == CV_64F)
621
return false;
622
623
char cvt[2][40];
624
ocl::Kernel k("sumConvert", ocl::imgproc::laplacian5_oclsrc,
625
format("-D ONLY_SUM_CONVERT "
626
"-D srcT=%s -D WT=%s -D dstT=%s -D coeffT=%s -D wdepth=%d "
627
"-D convertToWT=%s -D convertToDT=%s%s",
628
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
629
ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)),
630
ocl::typeToStr(CV_MAKE_TYPE(ddepth, kercn)),
631
ocl::typeToStr(wdepth), wdepth,
632
ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]),
633
ocl::convertTypeStr(wdepth, ddepth, kercn, cvt[1]),
634
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
635
if (k.empty())
636
return false;
637
638
UMat d2x, d2y;
639
sepFilter2D(_src, d2x, depth, kd, ks, Point(-1, -1), 0, borderType);
640
sepFilter2D(_src, d2y, depth, ks, kd, Point(-1, -1), 0, borderType);
641
642
UMat dst = _dst.getUMat();
643
644
ocl::KernelArg d2xarg = ocl::KernelArg::ReadOnlyNoSize(d2x),
645
d2yarg = ocl::KernelArg::ReadOnlyNoSize(d2y),
646
dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn);
647
648
if (wdepth >= CV_32F)
649
k.args(d2xarg, d2yarg, dstarg, (float)scale, (float)delta);
650
else
651
k.args(d2xarg, d2yarg, dstarg, iscale, idelta);
652
653
size_t globalsize[] = { (size_t)dst.cols * cn / kercn, (size_t)dst.rows };
654
return k.run(2, globalsize, NULL, false);
655
}
656
657
static bool ocl_Laplacian3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
658
InputArray _kernel, double delta, int borderType)
659
{
660
const ocl::Device & dev = ocl::Device::getDefault();
661
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
662
663
if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
664
(borderType != BORDER_WRAP) &&
665
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
666
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
667
return false;
668
669
Mat kernel = _kernel.getMat().reshape(1, 1);
670
671
if (ddepth < 0)
672
ddepth = sdepth;
673
674
Size size = _src.size();
675
size_t globalsize[2] = { 0, 0 };
676
size_t localsize[2] = { 0, 0 };
677
678
globalsize[0] = size.width / 16;
679
globalsize[1] = size.height / 2;
680
681
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
682
char build_opts[1024];
683
sprintf(build_opts, "-D %s %s", borderMap[borderType],
684
ocl::kernelToStr(kernel, CV_32F, "KERNEL_MATRIX").c_str());
685
686
ocl::Kernel k("laplacian3_8UC1_cols16_rows2", cv::ocl::imgproc::laplacian3_oclsrc, build_opts);
687
if (k.empty())
688
return false;
689
690
UMat src = _src.getUMat();
691
_dst.create(size, CV_MAKETYPE(ddepth, cn));
692
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
693
return false;
694
UMat dst = _dst.getUMat();
695
696
int idxArg = k.set(0, ocl::KernelArg::PtrReadOnly(src));
697
idxArg = k.set(idxArg, (int)src.step);
698
idxArg = k.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
699
idxArg = k.set(idxArg, (int)dst.step);
700
idxArg = k.set(idxArg, (int)dst.rows);
701
idxArg = k.set(idxArg, (int)dst.cols);
702
idxArg = k.set(idxArg, static_cast<float>(delta));
703
704
return k.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
705
}
706
707
}
708
#endif
709
710
#if defined(HAVE_IPP)
711
namespace cv
712
{
713
714
static bool ipp_Laplacian(InputArray _src, OutputArray _dst, int ksize, double scale, double delta, int borderType)
715
{
716
#ifdef HAVE_IPP_IW
717
CV_INSTRUMENT_REGION_IPP();
718
719
::ipp::IwiSize size(_src.size().width, _src.size().height);
720
IppDataType srcType = ippiGetDataType(_src.depth());
721
IppDataType dstType = ippiGetDataType(_dst.depth());
722
int channels = _src.channels();
723
bool useScale = false;
724
725
if(channels != _dst.channels() || channels > 1)
726
return false;
727
728
if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON)
729
useScale = true;
730
731
IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize);
732
if((int)maskSize < 0)
733
return false;
734
735
// Acquire data and begin processing
736
try
737
{
738
Mat src = _src.getMat();
739
Mat dst = _dst.getMat();
740
::ipp::IwiImage iwSrc = ippiGetImage(src);
741
::ipp::IwiImage iwDst = ippiGetImage(dst);
742
::ipp::IwiImage iwSrcProc = iwSrc;
743
::ipp::IwiImage iwDstProc = iwDst;
744
::ipp::IwiBorderSize borderSize(maskSize);
745
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
746
if(!ippBorder)
747
return false;
748
749
if(srcType == ipp8u && dstType == ipp8u)
750
{
751
iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
752
useScale = true;
753
}
754
else if(srcType == ipp8u && dstType == ipp32f)
755
{
756
iwSrc -= borderSize;
757
iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels);
758
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0);
759
iwSrcProc += borderSize;
760
}
761
762
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterLaplacian, iwSrcProc, iwDstProc, maskSize, ::ipp::IwDefault(), ippBorder);
763
764
if(useScale)
765
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta);
766
767
}
768
catch (const ::ipp::IwException &)
769
{
770
return false;
771
}
772
773
return true;
774
#else
775
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType);
776
return false;
777
#endif
778
}
779
}
780
#endif
781
782
783
void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
784
double scale, double delta, int borderType )
785
{
786
CV_INSTRUMENT_REGION();
787
788
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
789
if (ddepth < 0)
790
ddepth = sdepth;
791
_dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) );
792
793
if( ksize == 1 || ksize == 3 )
794
{
795
float K[2][9] =
796
{
797
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 },
798
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 }
799
};
800
801
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
802
if( scale != 1 )
803
kernel *= scale;
804
805
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
806
ocl_Laplacian3_8UC1(_src, _dst, ddepth, kernel, delta, borderType));
807
}
808
809
CV_IPP_RUN(!(cv::ocl::isOpenCLActivated() && _dst.isUMat()), ipp_Laplacian(_src, _dst, ksize, scale, delta, borderType));
810
811
if( ksize == 1 || ksize == 3 )
812
{
813
float K[2][9] =
814
{
815
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 },
816
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 }
817
};
818
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
819
if( scale != 1 )
820
kernel *= scale;
821
822
filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType );
823
}
824
else
825
{
826
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
827
int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F;
828
int wtype = CV_MAKETYPE(wdepth, cn);
829
Mat kd, ks;
830
getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );
831
832
CV_OCL_RUN(_dst.isUMat(),
833
ocl_Laplacian5(_src, _dst, kd, ks, scale,
834
delta, borderType, wdepth, ddepth))
835
836
Mat src = _src.getMat(), dst = _dst.getMat();
837
Point ofs;
838
Size wsz(src.cols, src.rows);
839
if(!(borderType&BORDER_ISOLATED))
840
src.locateROI( wsz, ofs );
841
borderType = (borderType&~BORDER_ISOLATED);
842
843
const size_t STRIPE_SIZE = 1 << 14;
844
Ptr<FilterEngine> fx = createSeparableLinearFilter(stype,
845
wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
846
Ptr<FilterEngine> fy = createSeparableLinearFilter(stype,
847
wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );
848
849
int y = fx->start(src, wsz, ofs), dsty = 0, dy = 0;
850
fy->start(src, wsz, ofs);
851
const uchar* sptr = src.ptr() + src.step[0] * y;
852
853
int dy0 = std::min(std::max((int)(STRIPE_SIZE/(CV_ELEM_SIZE(stype)*src.cols)), 1), src.rows);
854
Mat d2x( dy0 + kd.rows - 1, src.cols, wtype );
855
Mat d2y( dy0 + kd.rows - 1, src.cols, wtype );
856
857
for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy )
858
{
859
fx->proceed( sptr, (int)src.step, dy0, d2x.ptr(), (int)d2x.step );
860
dy = fy->proceed( sptr, (int)src.step, dy0, d2y.ptr(), (int)d2y.step );
861
if( dy > 0 )
862
{
863
Mat dstripe = dst.rowRange(dsty, dsty + dy);
864
d2x.rows = d2y.rows = dy; // modify the headers, which should work
865
d2x += d2y;
866
d2x.convertTo( dstripe, ddepth, scale, delta );
867
}
868
}
869
}
870
}
871
872
/////////////////////////////////////////////////////////////////////////////////////////
873
874
CV_IMPL void
875
cvSobel( const void* srcarr, void* dstarr, int dx, int dy, int aperture_size )
876
{
877
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
878
879
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() );
880
881
cv::Sobel( src, dst, dst.depth(), dx, dy, aperture_size, 1, 0, cv::BORDER_REPLICATE );
882
if( CV_IS_IMAGE(srcarr) && ((IplImage*)srcarr)->origin && dy % 2 != 0 )
883
dst *= -1;
884
}
885
886
887
CV_IMPL void
888
cvLaplace( const void* srcarr, void* dstarr, int aperture_size )
889
{
890
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
891
892
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() );
893
894
cv::Laplacian( src, dst, dst.depth(), aperture_size, 1, 0, cv::BORDER_REPLICATE );
895
}
896
897
/* End of file. */
898
899