247 lines
8.2 KiB
C++
247 lines
8.2 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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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// Erping Pang, pang_er_ping@163.com
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// Xiaopeng Fu, fuxiaopeng2222@163.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 materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#ifdef HAVE_OPENCL
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using namespace cvtest;
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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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#define OCL_KMEANS_USE_INITIAL_LABELS 1
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#define OCL_KMEANS_PP_CENTERS 2
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PARAM_TEST_CASE(Kmeans, int, int, int)
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{
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int type;
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int K;
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int flags;
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cv::Mat src ;
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ocl::oclMat d_src, d_dists;
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Mat labels, centers;
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ocl::oclMat d_labels, d_centers;
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virtual void SetUp()
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{
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K = GET_PARAM(0);
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type = GET_PARAM(1);
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flags = GET_PARAM(2);
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// MWIDTH=256, MHEIGHT=256. defined in utility.hpp
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cv::Size size = cv::Size(MWIDTH, MHEIGHT);
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src.create(size, type);
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int row_idx = 0;
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const int max_neighbour = MHEIGHT / K - 1;
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CV_Assert(K <= MWIDTH);
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for(int i = 0; i < K; i++ )
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{
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Mat center_row_header = src.row(row_idx);
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center_row_header.setTo(0);
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int nchannel = center_row_header.channels();
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for(int j = 0; j < nchannel; j++)
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center_row_header.at<float>(0, i*nchannel+j) = 50000.0;
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for(int j = 0; (j < max_neighbour) ||
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(i == K-1 && j < max_neighbour + MHEIGHT%K); j ++)
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{
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Mat cur_row_header = src.row(row_idx + 1 + j);
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center_row_header.copyTo(cur_row_header);
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Mat tmpmat = randomMat(cur_row_header.size(), cur_row_header.type(), -200, 200, false);
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cur_row_header += tmpmat;
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}
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row_idx += 1 + max_neighbour;
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}
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}
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};
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OCL_TEST_P(Kmeans, Mat){
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if(flags & KMEANS_USE_INITIAL_LABELS)
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{
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// inital a given labels
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labels.create(src.rows, 1, CV_32S);
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int *label = labels.ptr<int>();
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for(int i = 0; i < src.rows; i++)
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label[i] = rng.uniform(0, K);
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d_labels.upload(labels);
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}
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d_src.upload(src);
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for(int j = 0; j < LOOP_TIMES; j++)
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{
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kmeans(src, K, labels,
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TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 100, 0),
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1, flags, centers);
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ocl::kmeans(d_src, K, d_labels,
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TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 100, 0),
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1, flags, d_centers);
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Mat dd_labels(d_labels);
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Mat dd_centers(d_centers);
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if(flags & KMEANS_USE_INITIAL_LABELS)
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{
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EXPECT_MAT_NEAR(labels, dd_labels, 0);
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EXPECT_MAT_NEAR(centers, dd_centers, 1e-3);
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}
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else
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{
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int row_idx = 0;
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for(int i = 0; i < K; i++)
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{
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// verify lables with ground truth resutls
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int label = labels.at<int>(row_idx);
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int header_label = dd_labels.at<int>(row_idx);
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for(int j = 0; (j < MHEIGHT/K)||(i == K-1 && j < MHEIGHT/K+MHEIGHT%K); j++)
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{
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ASSERT_NEAR(labels.at<int>(row_idx+j), label, 0);
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ASSERT_NEAR(dd_labels.at<int>(row_idx+j), header_label, 0);
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}
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// verify centers
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float *center = centers.ptr<float>(label);
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float *header_center = dd_centers.ptr<float>(header_label);
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for(int t = 0; t < centers.cols; t++)
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ASSERT_NEAR(center[t], header_center[t], 1e-3);
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row_idx += MHEIGHT/K;
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}
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}
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}
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}
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INSTANTIATE_TEST_CASE_P(OCL_ML, Kmeans, Combine(
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Values(3, 5, 8),
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Values(CV_32FC1, CV_32FC2, CV_32FC4),
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Values(OCL_KMEANS_USE_INITIAL_LABELS/*, OCL_KMEANS_PP_CENTERS*/)));
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/////////////////////////////// DistanceToCenters //////////////////////////////////////////
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CV_ENUM(DistType, NORM_L1, NORM_L2SQR);
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PARAM_TEST_CASE(distanceToCenters, DistType, bool)
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{
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cv::Size size;
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int distType;
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bool useRoi;
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cv::Mat src, centers, src_roi, centers_roi;
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cv::ocl::oclMat ocl_src, ocl_centers, ocl_src_roi, ocl_centers_roi;
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virtual void SetUp()
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{
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distType = GET_PARAM(0);
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useRoi = GET_PARAM(1);
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}
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void random_roi()
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{
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Size roiSize_src = randomSize(10,1000);
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Size roiSize_centers = randomSize(10, 1000);
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roiSize_src.width = roiSize_centers.width;
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Border srcBorder = randomBorder(0, useRoi ? 500 : 0);
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randomSubMat(src, src_roi, roiSize_src, srcBorder, CV_32FC1, -SHRT_MAX, SHRT_MAX);
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Border centersBorder = randomBorder(0, useRoi ? 500 : 0);
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randomSubMat(centers, centers_roi, roiSize_centers, centersBorder, CV_32FC1, -SHRT_MAX, SHRT_MAX);
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for(int i = 0; i<centers.rows; i++)
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centers.at<float>(i, randomInt(0,centers.cols-1)) = (float)randomDouble(SHRT_MAX, INT_MAX);
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generateOclMat(ocl_src, ocl_src_roi, src, roiSize_src, srcBorder);
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generateOclMat(ocl_centers, ocl_centers_roi, centers, roiSize_centers, centersBorder);
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}
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};
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OCL_TEST_P(distanceToCenters, Accuracy)
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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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cv::ocl::oclMat ocl_dists;
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cv::ocl::oclMat ocl_labels;
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cv::ocl::distanceToCenters(ocl_dists,ocl_labels,ocl_src_roi, ocl_centers_roi, distType);
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Mat labels, dists;
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ocl_labels.download(labels);
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ocl_dists.download(dists);
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ASSERT_EQ(ocl_dists.cols, ocl_labels.rows);
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Mat batch_dists;
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cv::batchDistance(src_roi, centers_roi, batch_dists, CV_32FC1, noArray(), distType);
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std::vector<double> gold_dists_v;
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for(int i = 0; i<batch_dists.rows; i++)
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{
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Mat r = batch_dists.row(i);
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double mVal;
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Point mLoc;
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minMaxLoc(r, &mVal, NULL, &mLoc, NULL);
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int ocl_label = *(int*)labels.row(i).col(0).data;
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ASSERT_EQ(mLoc.x, ocl_label);
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gold_dists_v.push_back(mVal);
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}
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Mat gold_dists(gold_dists_v);
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dists.convertTo(dists, CV_64FC1);
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double relative_error = cv::norm(gold_dists.t(), dists, NORM_INF|NORM_RELATIVE);
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ASSERT_LE(relative_error, 1e-5);
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}
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}
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INSTANTIATE_TEST_CASE_P (OCL_ML, distanceToCenters, Combine(DistType::all(), Bool()) );
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#endif
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