mirror of
https://github.com/opencv/opencv.git
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904 lines
32 KiB
C++
904 lines
32 KiB
C++
/*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::Error::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 (const ivx::RuntimeError & e)
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{
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VX_DbgThrow(e.what());
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}
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catch (const 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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#if 0 //defined 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))
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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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{
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Mat src = _src.getMat();
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Mat dst = _dst.getMat();
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::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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{
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iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
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useScale = true;
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}
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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;
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}
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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));
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}
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catch (const ::ipp::IwException &)
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{
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return false;
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}
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return true;
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#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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{
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static bool ocl_sepFilter3x3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
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InputArray _kernelX, InputArray _kernelY, double delta, int borderType)
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{
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const ocl::Device & dev = ocl::Device::getDefault();
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int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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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)) )
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return false;
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Mat kernelX = _kernelX.getMat().reshape(1, 1);
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if (kernelX.cols % 2 != 1)
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return false;
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Mat kernelY = _kernelY.getMat().reshape(1, 1);
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if (kernelY.cols % 2 != 1)
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return false;
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if (ddepth < 0)
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ddepth = sdepth;
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Size size = _src.size();
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size_t globalsize[2] = { 0, 0 };
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size_t localsize[2] = { 0, 0 };
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globalsize[0] = size.width / 16;
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globalsize[1] = size.height / 2;
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const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
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char build_opts[1024];
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snprintf(build_opts, sizeof(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());
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ocl::Kernel kernel("sepFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::sepFilter3x3_oclsrc, build_opts);
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if (kernel.empty())
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return false;
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UMat src = _src.getUMat();
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_dst.create(size, CV_MAKETYPE(ddepth, cn));
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if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
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return false;
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UMat dst = _dst.getUMat();
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int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
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idxArg = kernel.set(idxArg, (int)src.step);
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idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
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idxArg = kernel.set(idxArg, (int)dst.step);
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idxArg = kernel.set(idxArg, (int)dst.rows);
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idxArg = kernel.set(idxArg, (int)dst.cols);
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idxArg = kernel.set(idxArg, static_cast<float>(delta));
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return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, 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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CV_INSTRUMENT_REGION();
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CV_Assert(!_src.empty());
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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_MAKE_TYPE(ddepth, cn);
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_dst.create( _src.size(), dtype );
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int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
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Mat kx, ky;
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getDerivKernels( kx, ky, dx, dy, ksize, false, ktype );
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if( scale != 1 )
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{
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// usually the smoothing part is the slowest to compute,
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// so try to scale it instead of the faster differentiating part
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if( dx == 0 )
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kx *= scale;
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else
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ky *= scale;
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}
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CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && ksize == 3 &&
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(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
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ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
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CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
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ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType))
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Mat src = _src.getMat();
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Mat dst = _dst.getMat();
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Point ofs;
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Size wsz(src.cols, src.rows);
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if(!(borderType & BORDER_ISOLATED))
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src.locateROI( wsz, ofs );
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CALL_HAL(sobel, cv_hal_sobel, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
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ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, ksize, scale, delta, borderType&~BORDER_ISOLATED);
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|
|
CV_OVX_RUN(true,
|
|
openvx_sobel(src, dst, dx, dy, ksize, scale, delta, borderType))
|
|
|
|
//CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, ksize, scale, delta, borderType));
|
|
|
|
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 )
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
|
|
CV_Assert(!_src.empty());
|
|
|
|
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 );
|
|
|
|
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 differentiating part
|
|
if( dx == 0 )
|
|
kx *= scale;
|
|
else
|
|
ky *= scale;
|
|
}
|
|
|
|
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
|
|
(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
|
|
ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
|
|
|
|
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
|
|
(size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
|
|
ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType))
|
|
|
|
Mat src = _src.getMat();
|
|
Mat dst = _dst.getMat();
|
|
|
|
Point ofs;
|
|
Size wsz(src.cols, src.rows);
|
|
if(!(borderType & BORDER_ISOLATED))
|
|
src.locateROI( wsz, ofs );
|
|
|
|
CALL_HAL(scharr, cv_hal_scharr, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
|
|
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, scale, delta, borderType&~BORDER_ISOLATED);
|
|
|
|
//CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, 0, scale, delta, borderType));
|
|
|
|
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;
|
|
CV_Assert(src_step != 0 && esz != 0);
|
|
|
|
// 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)
|
|
&& OCL_PERFORMANCE_CHECK(!dev.isAMD()) // TODO FIXIT 2018: Problem with AMDGPU on Linux (2482.3)
|
|
)
|
|
{
|
|
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][50];
|
|
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 CONVERT_TO_WT=%s -D CONVERT_TO_DT=%s"
|
|
" -D %s -D SRC_T1=%s -D DST_T1=%s -D WT1=%s"
|
|
" -D SRC_T=%s -D DST_T=%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], sizeof(cvt[0])),
|
|
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1], sizeof(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][50];
|
|
ocl::Kernel k("sumConvert", ocl::imgproc::laplacian5_oclsrc,
|
|
format("-D ONLY_SUM_CONVERT "
|
|
"-D SRC_T=%s -D WT=%s -D DST_T=%s -D COEFF_T=%s -D WDEPTH=%d "
|
|
"-D CONVERT_TO_WT=%s -D CONVERT_TO_DT=%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], sizeof(cvt[0])),
|
|
ocl::convertTypeStr(wdepth, ddepth, kercn, cvt[1], sizeof(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[] = { (size_t)dst.cols * cn / kercn, (size_t)dst.rows };
|
|
return k.run(2, globalsize, NULL, false);
|
|
}
|
|
|
|
static bool ocl_Laplacian3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
|
|
InputArray _kernel, double delta, int borderType)
|
|
{
|
|
const ocl::Device & dev = ocl::Device::getDefault();
|
|
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
|
|
|
|
if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
|
|
(borderType != BORDER_WRAP) &&
|
|
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
|
|
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
|
|
return false;
|
|
|
|
Mat kernel = _kernel.getMat().reshape(1, 1);
|
|
|
|
if (ddepth < 0)
|
|
ddepth = sdepth;
|
|
|
|
Size size = _src.size();
|
|
size_t globalsize[2] = { 0, 0 };
|
|
size_t localsize[2] = { 0, 0 };
|
|
|
|
globalsize[0] = size.width / 16;
|
|
globalsize[1] = size.height / 2;
|
|
|
|
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
|
|
char build_opts[1024];
|
|
snprintf(build_opts, sizeof(build_opts), "-D %s %s", borderMap[borderType],
|
|
ocl::kernelToStr(kernel, CV_32F, "KERNEL_MATRIX").c_str());
|
|
|
|
ocl::Kernel k("laplacian3_8UC1_cols16_rows2", cv::ocl::imgproc::laplacian3_oclsrc, build_opts);
|
|
if (k.empty())
|
|
return false;
|
|
|
|
UMat src = _src.getUMat();
|
|
_dst.create(size, CV_MAKETYPE(ddepth, cn));
|
|
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
|
|
return false;
|
|
UMat dst = _dst.getUMat();
|
|
|
|
int idxArg = k.set(0, ocl::KernelArg::PtrReadOnly(src));
|
|
idxArg = k.set(idxArg, (int)src.step);
|
|
idxArg = k.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
|
|
idxArg = k.set(idxArg, (int)dst.step);
|
|
idxArg = k.set(idxArg, (int)dst.rows);
|
|
idxArg = k.set(idxArg, (int)dst.cols);
|
|
idxArg = k.set(idxArg, static_cast<float>(delta));
|
|
|
|
return k.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
|
|
}
|
|
|
|
}
|
|
#endif
|
|
|
|
#if defined(HAVE_IPP)
|
|
namespace cv
|
|
{
|
|
|
|
static bool ipp_Laplacian(InputArray _src, OutputArray _dst, int ksize, double scale, double delta, int borderType)
|
|
{
|
|
#ifdef HAVE_IPP_IW
|
|
CV_INSTRUMENT_REGION_IPP();
|
|
|
|
::ipp::IwiSize size(_src.size().width, _src.size().height);
|
|
IppDataType srcType = ippiGetDataType(_src.depth());
|
|
IppDataType dstType = ippiGetDataType(_dst.depth());
|
|
int channels = _src.channels();
|
|
bool useScale = false;
|
|
|
|
if(channels != _dst.channels() || channels > 1)
|
|
return false;
|
|
|
|
if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON)
|
|
useScale = true;
|
|
|
|
IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize);
|
|
if((int)maskSize < 0)
|
|
return false;
|
|
|
|
// Acquire data and begin processing
|
|
try
|
|
{
|
|
Mat src = _src.getMat();
|
|
Mat dst = _dst.getMat();
|
|
::ipp::IwiImage iwSrc = ippiGetImage(src);
|
|
::ipp::IwiImage iwDst = ippiGetImage(dst);
|
|
::ipp::IwiImage iwSrcProc = iwSrc;
|
|
::ipp::IwiImage iwDstProc = iwDst;
|
|
::ipp::IwiBorderSize borderSize(maskSize);
|
|
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
|
|
if(!ippBorder)
|
|
return false;
|
|
|
|
if(srcType == ipp8u && dstType == ipp8u)
|
|
{
|
|
iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
|
|
useScale = true;
|
|
}
|
|
else if(srcType == ipp8u && dstType == ipp32f)
|
|
{
|
|
iwSrc -= borderSize;
|
|
iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels);
|
|
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0);
|
|
iwSrcProc += borderSize;
|
|
}
|
|
|
|
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterLaplacian, iwSrcProc, iwDstProc, maskSize, ::ipp::IwDefault(), ippBorder);
|
|
|
|
if(useScale)
|
|
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta);
|
|
|
|
}
|
|
catch (const ::ipp::IwException &)
|
|
{
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
#else
|
|
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType);
|
|
return false;
|
|
#endif
|
|
}
|
|
}
|
|
#endif
|
|
|
|
|
|
void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
|
|
double scale, double delta, int borderType )
|
|
{
|
|
CV_INSTRUMENT_REGION();
|
|
|
|
CV_Assert(!_src.empty());
|
|
|
|
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) );
|
|
|
|
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;
|
|
|
|
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
|
|
ocl_Laplacian3_8UC1(_src, _dst, ddepth, kernel, delta, borderType));
|
|
}
|
|
|
|
CV_IPP_RUN(!(cv::ocl::isOpenCLActivated() && _dst.isUMat()), ipp_Laplacian(_src, _dst, ksize, scale, delta, borderType));
|
|
|
|
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))
|
|
|
|
Mat src = _src.getMat(), dst = _dst.getMat();
|
|
Point ofs;
|
|
Size wsz(src.cols, src.rows);
|
|
if(!(borderType&BORDER_ISOLATED))
|
|
src.locateROI( wsz, ofs );
|
|
borderType = (borderType&~BORDER_ISOLATED);
|
|
|
|
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() );
|
|
|
|
int y = fx->start(src, wsz, ofs), dsty = 0, dy = 0;
|
|
fy->start(src, wsz, ofs);
|
|
const uchar* sptr = src.ptr() + src.step[0] * 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);
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|
d2x.rows = d2y.rows = dy; // modify the headers, which should work
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|
d2x += d2y;
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|
d2x.convertTo( dstripe, ddepth, scale, delta );
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|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
CV_IMPL void
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|
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 );
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|
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. */
|