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e845184843
* #1538 from StevenPuttemans:bugfix_3283 * #1545 from alalek:ocl_test_fix_rng * #1551 from alalek:cmake_install_win * #1570 from ilya-lavrenov:ipp_warn_fix * #1573 from alalek:perf_simple_strategy * #1574 from alalek:svm_workaround * #1576 from alalek:ocl_fix_cl_double * #1577 from ilya-lavrenov:ocl_setto_opencl12 * #1578 from asmorkalov:android_fd_cp_fix * #1579 from ilya-lavrenov:ocl_norm * #1582 from sperrholz:ocl-arithm-additions * #1586 from ilya-lavrenov:ocl_setto_win_fix * #1589 from ilya-lavrenov:pr1582_fix * #1591 from alalek:ocl_remove_cl_hpp_h * #1592 from alalek:ocl_program_cache_update * #1593 from ilya-lavrenov:ocl_war_on_double * #1594 from ilya-lavrenov:ocl_perf * #1595 from alalek:cl_code_cleanup * #1596 from alalek:test_fix_run_py * #1597 from alalek:ocl_fix_cleanup * #1598 from alalek:ocl_fix_build_mac * #1599 from ilya-lavrenov:ocl_mac_kernel_warnings * #1601 from ilya-lavrenov:ocl_fix_tvl1_and_sparse * #1602 from alalek:ocl_test_dump_info * #1603 from ilya-lavrenov:ocl_disable_svm_noblas * #1605 from alalek:ocl_fixes * #1606 from ilya-lavrenov:ocl_imgproc * #1607 from ilya-lavrenov:ocl_fft_cleanup * #1608 from alalek:fix_warn_upd_haar * #1609 from ilya-lavrenov:ocl_some_optimization * #1610 from alalek:ocl_fix_perf_kalman * #1612 from alalek:ocl_fix_string_info * #1614 from ilya-lavrenov:ocl_svm_misprint * #1616 from ilya-lavrenov:ocl_cvtColor * #1617 from ilya-lavrenov:ocl_info * #1622 from a0byte:2.4 * #1625 from ilya-lavrenov:to_string Conflicts: cmake/OpenCVConfig.cmake cmake/OpenCVDetectPython.cmake cmake/OpenCVGenConfig.cmake modules/core/CMakeLists.txt modules/nonfree/src/surf.ocl.cpp modules/ocl/include/opencv2/ocl/ocl.hpp modules/ocl/include/opencv2/ocl/private/util.hpp modules/ocl/perf/main.cpp modules/ocl/src/arithm.cpp modules/ocl/src/cl_operations.cpp modules/ocl/src/cl_programcache.cpp modules/ocl/src/color.cpp modules/ocl/src/fft.cpp modules/ocl/src/filtering.cpp modules/ocl/src/gemm.cpp modules/ocl/src/haar.cpp modules/ocl/src/imgproc.cpp modules/ocl/src/matrix_operations.cpp modules/ocl/src/pyrlk.cpp modules/ocl/src/split_merge.cpp modules/ocl/src/svm.cpp modules/ocl/test/main.cpp modules/ocl/test/test_fft.cpp modules/ocl/test/test_moments.cpp modules/ocl/test/test_objdetect.cpp modules/ocl/test/test_optflow.cpp modules/ocl/test/utility.hpp modules/python/CMakeLists.txt modules/ts/include/opencv2/ts.hpp modules/ts/src/ts_perf.cpp samples/android/face-detection/jni/DetectionBasedTracker_jni.cpp
162 lines
5.8 KiB
C++
162 lines
5.8 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 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 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( TermCriteria::EPS + TermCriteria::MAX_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( TermCriteria::EPS + TermCriteria::MAX_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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#endif
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