refactored all the tests in ocl/test/test_imgproc.cpp
This commit is contained in:
Ilya Lavrenov
408
modules/ocl/test/test_mean_shift.cpp
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408
modules/ocl/test/test_mean_shift.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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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Multicoreware, 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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// @Authors
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// Niko Li, newlife20080214@gmail.com
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// Jia Haipeng, jiahaipeng95@gmail.com
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// Shengen Yan, yanshengen@gmail.com
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// Jiang Liyuan, lyuan001.good@163.com
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// Rock Li, Rock.Li@amd.com
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// Wu Zailong, bullet@yeah.net
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// Xu Pang, pangxu010@163.com
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// Sen Liu, swjtuls1987@126.com
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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 oclMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#ifdef HAVE_OPENCL
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using namespace testing;
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using namespace std;
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using namespace cv;
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typedef struct
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{
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short x;
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short y;
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} COOR;
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COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, Size size, int sp, int sr, int maxIter, float eps, int *tab)
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{
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int isr2 = sr * sr;
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int c0, c1, c2, c3;
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int iter;
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uchar *ptr = NULL;
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uchar *pstart = NULL;
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int revx = 0, revy = 0;
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c0 = sptr[0];
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c1 = sptr[1];
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c2 = sptr[2];
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c3 = sptr[3];
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// iterate meanshift procedure
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for(iter = 0; iter < maxIter; iter++ )
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{
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int count = 0;
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int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;
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//mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
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int minx = x0 - sp;
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int miny = y0 - sp;
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int maxx = x0 + sp;
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int maxy = y0 + sp;
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//deal with the image boundary
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if(minx < 0) minx = 0;
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if(miny < 0) miny = 0;
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if(maxx >= size.width) maxx = size.width - 1;
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if(maxy >= size.height) maxy = size.height - 1;
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if(iter == 0)
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{
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pstart = sptr;
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}
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else
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{
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pstart = pstart + revy * sstep + (revx << 2); //point to the new position
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}
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ptr = pstart;
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ptr = ptr + (miny - y0) * sstep + ((minx - x0) << 2); //point to the start in the row
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for( int y = miny; y <= maxy; y++, ptr += sstep - ((maxx - minx + 1) << 2))
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{
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int rowCount = 0;
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int x = minx;
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#if CV_ENABLE_UNROLLED
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for( ; x + 4 <= maxx; x += 4, ptr += 16)
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{
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int t0, t1, t2;
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t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
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if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
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{
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s0 += t0;
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s1 += t1;
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s2 += t2;
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sx += x;
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rowCount++;
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}
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t0 = ptr[4], t1 = ptr[5], t2 = ptr[6];
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if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
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{
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s0 += t0;
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s1 += t1;
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s2 += t2;
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sx += x + 1;
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rowCount++;
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}
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t0 = ptr[8], t1 = ptr[9], t2 = ptr[10];
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if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
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{
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s0 += t0;
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s1 += t1;
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s2 += t2;
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sx += x + 2;
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rowCount++;
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}
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t0 = ptr[12], t1 = ptr[13], t2 = ptr[14];
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if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
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{
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s0 += t0;
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s1 += t1;
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s2 += t2;
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sx += x + 3;
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rowCount++;
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}
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}
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#endif
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for(; x <= maxx; x++, ptr += 4)
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{
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int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
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if(tab[t0 - c0 + 255] + tab[t1 - c1 + 255] + tab[t2 - c2 + 255] <= isr2)
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{
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s0 += t0;
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s1 += t1;
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s2 += t2;
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sx += x;
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rowCount++;
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}
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}
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if(rowCount == 0)
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continue;
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count += rowCount;
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sy += y * rowCount;
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}
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if( count == 0 )
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break;
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int x1 = sx / count;
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int y1 = sy / count;
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s0 = s0 / count;
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s1 = s1 / count;
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s2 = s2 / count;
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bool stopFlag = (x0 == x1 && y0 == y1) || (abs(x1 - x0) + abs(y1 - y0) +
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tab[s0 - c0 + 255] + tab[s1 - c1 + 255] + tab[s2 - c2 + 255] <= eps);
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//revise the pointer corresponding to the new (y0,x0)
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revx = x1 - x0;
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revy = y1 - y0;
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x0 = x1;
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y0 = y1;
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c0 = s0;
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c1 = s1;
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c2 = s2;
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if( stopFlag )
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break;
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} //for iter
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dptr[0] = (uchar)c0;
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dptr[1] = (uchar)c1;
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dptr[2] = (uchar)c2;
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dptr[3] = (uchar)c3;
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COOR coor;
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coor.x = (short)x0;
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coor.y = (short)y0;
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return coor;
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}
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void meanShiftFiltering_(const Mat &src_roi, Mat &dst_roi, int sp, int sr, TermCriteria crit)
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{
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if( src_roi.empty() )
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CV_Error( CV_StsBadArg, "The input image is empty" );
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if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
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CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
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CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) );
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CV_Assert( !(dst_roi.step & 0x3) );
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if( !(crit.type & TermCriteria::MAX_ITER) )
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crit.maxCount = 5;
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int maxIter = std::min(std::max(crit.maxCount, 1), 100);
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float eps;
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if( !(crit.type & TermCriteria::EPS) )
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eps = 1.f;
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eps = (float)std::max(crit.epsilon, 0.0);
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int tab[512];
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for(int i = 0; i < 512; i++)
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tab[i] = (i - 255) * (i - 255);
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uchar *sptr = src_roi.data;
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uchar *dptr = dst_roi.data;
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int sstep = (int)src_roi.step;
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int dstep = (int)dst_roi.step;
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Size size = src_roi.size();
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for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
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dptr += dstep - (size.width << 2))
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{
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for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4)
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{
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do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
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}
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}
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}
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void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, TermCriteria crit)
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{
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if( src_roi.empty() )
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CV_Error( CV_StsBadArg, "The input image is empty" );
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if( src_roi.depth() != CV_8U || src_roi.channels() != 4 )
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CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
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CV_Assert( (src_roi.cols == dst_roi.cols) && (src_roi.rows == dst_roi.rows) &&
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(src_roi.cols == dstCoor_roi.cols) && (src_roi.rows == dstCoor_roi.rows));
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CV_Assert( !(dstCoor_roi.step & 0x3) );
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if( !(crit.type & TermCriteria::MAX_ITER) )
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crit.maxCount = 5;
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int maxIter = std::min(std::max(crit.maxCount, 1), 100);
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float eps;
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if( !(crit.type & TermCriteria::EPS) )
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eps = 1.f;
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eps = (float)std::max(crit.epsilon, 0.0);
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int tab[512];
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for(int i = 0; i < 512; i++)
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tab[i] = (i - 255) * (i - 255);
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uchar *sptr = src_roi.data;
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uchar *dptr = dst_roi.data;
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short *dCoorptr = (short *)dstCoor_roi.data;
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int sstep = (int)src_roi.step;
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int dstep = (int)dst_roi.step;
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int dCoorstep = (int)dstCoor_roi.step >> 1;
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Size size = src_roi.size();
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for(int i = 0; i < size.height; i++, sptr += sstep - (size.width << 2),
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dptr += dstep - (size.width << 2), dCoorptr += dCoorstep - (size.width << 1))
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{
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for(int j = 0; j < size.width; j++, sptr += 4, dptr += 4, dCoorptr += 2)
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{
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*((COOR *)dCoorptr) = do_meanShift(j, i, sptr, dptr, sstep, size, sp, sr, maxIter, eps, tab);
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}
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}
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}
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//////////////////////////////// meanShift //////////////////////////////////////////
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PARAM_TEST_CASE(meanShiftTestBase, MatType, MatType, int, int, TermCriteria, bool)
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{
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int type, typeCoor;
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int sp, sr;
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TermCriteria crit;
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bool useRoi;
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// src mat
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Mat src, src_roi;
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Mat dst, dst_roi;
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Mat dstCoor, dstCoor_roi;
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// ocl dst mat
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ocl::oclMat gsrc, gsrc_roi;
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ocl::oclMat gdst, gdst_roi;
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ocl::oclMat gdstCoor, gdstCoor_roi;
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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typeCoor = GET_PARAM(1);
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sp = GET_PARAM(2);
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sr = GET_PARAM(3);
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crit = GET_PARAM(4);
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useRoi = GET_PARAM(5);
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}
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void random_roi()
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{
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Size roiSize = randomSize(1, MAX_VALUE);
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256);
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generateOclMat(gsrc, gsrc_roi, src, roiSize, srcBorder);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 5, 256);
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generateOclMat(gdst, gdst_roi, dst, roiSize, dstBorder);
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randomSubMat(dstCoor, dstCoor_roi, roiSize, dstBorder, typeCoor, 5, 256);
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generateOclMat(gdstCoor, gdstCoor_roi, dstCoor, roiSize, dstBorder);
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}
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void Near(double threshold = 0.0)
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{
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Mat whole, roi;
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gdst.download(whole);
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gdst_roi.download(roi);
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EXPECT_MAT_NEAR(dst, whole, threshold);
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EXPECT_MAT_NEAR(dst_roi, roi, threshold);
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}
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void Near1(double threshold = 0.0)
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{
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Mat whole, roi;
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gdstCoor.download(whole);
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gdstCoor_roi.download(roi);
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EXPECT_MAT_NEAR(dstCoor, whole, threshold);
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EXPECT_MAT_NEAR(dstCoor_roi, roi, threshold);
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}
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};
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/////////////////////////meanShiftFiltering/////////////////////////////
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typedef meanShiftTestBase meanShiftFiltering;
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OCL_TEST_P(meanShiftFiltering, Mat)
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{
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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meanShiftFiltering_(src_roi, dst_roi, sp, sr, crit);
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ocl::meanShiftFiltering(gsrc_roi, gdst_roi, sp, sr, crit);
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Near();
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}
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}
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///////////////////////////meanShiftProc//////////////////////////////////
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typedef meanShiftTestBase meanShiftProc;
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OCL_TEST_P(meanShiftProc, Mat)
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{
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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meanShiftProc_(src_roi, dst_roi, dstCoor_roi, sp, sr, crit);
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ocl::meanShiftProc(gsrc_roi, gdst_roi, gdstCoor_roi, sp, sr, crit);
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Near();
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Near1();
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////
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INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftFiltering, Combine(
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Values((MatType)CV_8UC4),
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Values((MatType)CV_16SC2),
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Values(5),
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Values(6),
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Values(TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 5, 1)),
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Bool()
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));
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INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftProc, Combine(
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Values((MatType)CV_8UC4),
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Values((MatType)CV_16SC2),
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Values(5),
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Values(6),
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Values(TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 5, 1)),
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Bool()
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));
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#endif // HAVE_OPENCL
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