mirror of https://github.com/opencv/opencv.git
Merge pull request #2429 from ilya-lavrenov:master_compatible_tests
commit
ba4513503e
25 changed files with 988 additions and 809 deletions
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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, 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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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@multicorewareinc.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 "perf_precomp.hpp" |
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using namespace perf; |
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using std::tr1::tuple; |
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using std::tr1::get; |
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///////////// norm////////////////////////
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typedef tuple<Size, MatType> normParams; |
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typedef TestBaseWithParam<normParams> normFixture; |
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PERF_TEST_P(normFixture, norm, testing::Combine( |
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OCL_TYPICAL_MAT_SIZES, |
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OCL_PERF_ENUM(CV_8UC1, CV_32FC1))) |
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{ |
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const normParams params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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double value = 0.0; |
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const double eps = CV_MAT_DEPTH(type) == CV_8U ? DBL_EPSILON : 1e-3; |
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Mat src1(srcSize, type), src2(srcSize, type); |
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declare.in(src1, src2, WARMUP_RNG); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc1(src1), oclSrc2(src2); |
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OCL_TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, NORM_INF); |
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SANITY_CHECK(value, eps); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() value = cv::norm(src1, src2, NORM_INF); |
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SANITY_CHECK(value); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
@ -0,0 +1,276 @@ |
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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.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
||||
// For Open Source Computer Vision Library
|
||||
//
|
||||
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
|
||||
// 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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// Fangfang Bai, fangfang@multicorewareinc.com
|
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// Jin Ma, jin@multicorewareinc.com
|
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//
|
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// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// this list of conditions and the following disclaimer in the documentation
|
||||
// and/or other materials provided with the distribution.
|
||||
//
|
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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
|
||||
// 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
|
||||
// (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 "perf_precomp.hpp" |
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using namespace perf; |
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using std::tr1::tuple; |
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using std::tr1::get; |
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///////////// MinMax ////////////////////////
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typedef Size_MatType MinMaxFixture; |
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PERF_TEST_P(MinMaxFixture, MinMax, |
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::testing::Combine(OCL_TYPICAL_MAT_SIZES, |
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OCL_PERF_ENUM(CV_8UC1, CV_32FC1))) |
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{ |
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const Size_MatType_t params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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Mat src(srcSize, type); |
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declare.in(src, WARMUP_RNG); |
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double min_val = std::numeric_limits<double>::max(), |
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max_val = std::numeric_limits<double>::min(); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc(src); |
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OCL_TEST_CYCLE() cv::ocl::minMax(oclSrc, &min_val, &max_val); |
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ASSERT_GE(max_val, min_val); |
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SANITY_CHECK(min_val); |
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SANITY_CHECK(max_val); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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Point min_loc, max_loc; |
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TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc); |
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ASSERT_GE(max_val, min_val); |
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SANITY_CHECK(min_val); |
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SANITY_CHECK(max_val); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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///////////// MinMaxLoc ////////////////////////
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typedef Size_MatType MinMaxLocFixture; |
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OCL_PERF_TEST_P(MinMaxLocFixture, MinMaxLoc, |
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::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1))) |
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{ |
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const Size_MatType_t params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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Mat src(srcSize, type); |
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randu(src, 0, 1); |
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declare.in(src); |
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double min_val = 0.0, max_val = 0.0; |
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Point min_loc, max_loc; |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc(src); |
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OCL_TEST_CYCLE() cv::ocl::minMaxLoc(oclSrc, &min_val, &max_val, &min_loc, &max_loc); |
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ASSERT_GE(max_val, min_val); |
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SANITY_CHECK(min_val); |
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SANITY_CHECK(max_val); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc); |
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ASSERT_GE(max_val, min_val); |
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SANITY_CHECK(min_val); |
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SANITY_CHECK(max_val); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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///////////// Sum ////////////////////////
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typedef Size_MatType SumFixture; |
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OCL_PERF_TEST_P(SumFixture, Sum, |
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::testing::Combine(OCL_TEST_SIZES, |
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OCL_TEST_TYPES)) |
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{ |
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const Size_MatType_t params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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Mat src(srcSize, type); |
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Scalar result; |
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randu(src, 0, 60); |
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declare.in(src); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc(src); |
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OCL_TEST_CYCLE() result = cv::ocl::sum(oclSrc); |
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SANITY_CHECK(result, 1e-6, ERROR_RELATIVE); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() result = cv::sum(src); |
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SANITY_CHECK(result, 1e-6, ERROR_RELATIVE); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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///////////// countNonZero ////////////////////////
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typedef Size_MatType CountNonZeroFixture; |
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OCL_PERF_TEST_P(CountNonZeroFixture, CountNonZero, |
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::testing::Combine(OCL_TEST_SIZES, |
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OCL_PERF_ENUM(CV_8UC1, CV_32FC1))) |
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{ |
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const Size_MatType_t params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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Mat src(srcSize, type); |
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int result = 0; |
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randu(src, 0, 256); |
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declare.in(src); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc(src); |
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OCL_TEST_CYCLE() result = cv::ocl::countNonZero(oclSrc); |
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SANITY_CHECK(result); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() result = cv::countNonZero(src); |
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SANITY_CHECK(result); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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///////////// meanStdDev ////////////////////////
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typedef Size_MatType MeanStdDevFixture; |
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OCL_PERF_TEST_P(MeanStdDevFixture, MeanStdDev, |
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::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES)) |
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{ |
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const Size_MatType_t params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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Mat src(srcSize, type); |
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Scalar mean, stddev; |
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randu(src, 0, 256); |
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declare.in(src); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc(src); |
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OCL_TEST_CYCLE() cv::ocl::meanStdDev(oclSrc, mean, stddev); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() cv::meanStdDev(src, mean, stddev); |
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} |
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else |
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OCL_PERF_ELSE |
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SANITY_CHECK_NOTHING(); |
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// SANITY_CHECK(mean, 1e-6, ERROR_RELATIVE);
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// SANITY_CHECK(stddev, 1e-6, ERROR_RELATIVE);
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} |
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///////////// norm////////////////////////
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CV_ENUM(NormType, NORM_INF, NORM_L1, NORM_L2) |
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typedef std::tr1::tuple<Size, MatType, NormType> NormParams; |
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typedef TestBaseWithParam<NormParams> NormFixture; |
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OCL_PERF_TEST_P(NormFixture, Norm, |
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::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), |
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OCL_TEST_TYPES, NormType::all())) |
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{ |
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const NormParams params = GetParam(); |
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const Size srcSize = get<0>(params); |
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const int type = get<1>(params); |
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const int normType = get<2>(params); |
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perf::ERROR_TYPE errorType = type != NORM_INF ? ERROR_RELATIVE : ERROR_ABSOLUTE; |
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double eps = 1e-5, value; |
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Mat src1(srcSize, type), src2(srcSize, type); |
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declare.in(src1, src2, WARMUP_RNG); |
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if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclSrc1(src1), oclSrc2(src2); |
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OCL_TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, normType); |
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SANITY_CHECK(value, eps, errorType); |
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} |
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else if (RUN_PLAIN_IMPL) |
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{ |
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TEST_CYCLE() value = cv::norm(src1, src2, normType); |
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SANITY_CHECK(value, eps, errorType); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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