Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// 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.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// 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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// any express or implied warranties, including, but not limited to, the implied
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// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
///////////// MinMax ////////////////////////
typedef Size_MatType MinMaxFixture;
PERF_TEST_P(MinMaxFixture, MinMax,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
Mat src(srcSize, type);
declare.in(src, WARMUP_RNG);
double min_val = std::numeric_limits<double>::max(),
max_val = std::numeric_limits<double>::min();
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
OCL_TEST_CYCLE() cv::ocl::minMax(oclSrc, &min_val, &max_val);
ASSERT_GE(max_val, min_val);
SANITY_CHECK(min_val);
SANITY_CHECK(max_val);
}
else if (RUN_PLAIN_IMPL)
{
Point min_loc, max_loc;
TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
ASSERT_GE(max_val, min_val);
SANITY_CHECK(min_val);
SANITY_CHECK(max_val);
}
else
OCL_PERF_ELSE
}
///////////// MinMaxLoc ////////////////////////
typedef Size_MatType MinMaxLocFixture;
OCL_PERF_TEST_P(MinMaxLocFixture, MinMaxLoc,
::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
Mat src(srcSize, type);
randu(src, 0, 1);
declare.in(src);
double min_val = 0.0, max_val = 0.0;
Point min_loc, max_loc;
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
OCL_TEST_CYCLE() cv::ocl::minMaxLoc(oclSrc, &min_val, &max_val, &min_loc, &max_loc);
ASSERT_GE(max_val, min_val);
SANITY_CHECK(min_val);
SANITY_CHECK(max_val);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
ASSERT_GE(max_val, min_val);
SANITY_CHECK(min_val);
SANITY_CHECK(max_val);
}
else
OCL_PERF_ELSE
}
///////////// Sum ////////////////////////
typedef Size_MatType SumFixture;
OCL_PERF_TEST_P(SumFixture, Sum,
::testing::Combine(OCL_TEST_SIZES,
OCL_TEST_TYPES))
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
Mat src(srcSize, type);
Scalar result;
randu(src, 0, 60);
declare.in(src);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
OCL_TEST_CYCLE() result = cv::ocl::sum(oclSrc);
SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() result = cv::sum(src);
SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
}
else
OCL_PERF_ELSE
}
///////////// countNonZero ////////////////////////
typedef Size_MatType CountNonZeroFixture;
OCL_PERF_TEST_P(CountNonZeroFixture, CountNonZero,
::testing::Combine(OCL_TEST_SIZES,
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
Mat src(srcSize, type);
int result = 0;
randu(src, 0, 256);
declare.in(src);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
OCL_TEST_CYCLE() result = cv::ocl::countNonZero(oclSrc);
SANITY_CHECK(result);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() result = cv::countNonZero(src);
SANITY_CHECK(result);
}
else
OCL_PERF_ELSE
}
///////////// meanStdDev ////////////////////////
typedef Size_MatType MeanStdDevFixture;
OCL_PERF_TEST_P(MeanStdDevFixture, MeanStdDev,
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
Mat src(srcSize, type);
Scalar mean, stddev;
randu(src, 0, 256);
declare.in(src);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc(src);
OCL_TEST_CYCLE() cv::ocl::meanStdDev(oclSrc, mean, stddev);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::meanStdDev(src, mean, stddev);
}
else
OCL_PERF_ELSE
SANITY_CHECK_NOTHING();
// SANITY_CHECK(mean, 1e-6, ERROR_RELATIVE);
// SANITY_CHECK(stddev, 1e-6, ERROR_RELATIVE);
}
///////////// norm////////////////////////
CV_ENUM(NormType, NORM_INF, NORM_L1, NORM_L2)
typedef std::tr1::tuple<Size, MatType, NormType> NormParams;
typedef TestBaseWithParam<NormParams> NormFixture;
OCL_PERF_TEST_P(NormFixture, Norm,
::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
OCL_TEST_TYPES, NormType::all()))
{
const NormParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const int normType = get<2>(params);
perf::ERROR_TYPE errorType = type != NORM_INF ? ERROR_RELATIVE : ERROR_ABSOLUTE;
double eps = 1e-5, value;
Mat src1(srcSize, type), src2(srcSize, type);
declare.in(src1, src2, WARMUP_RNG);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2);
OCL_TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, normType);
SANITY_CHECK(value, eps, errorType);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() value = cv::norm(src1, src2, normType);
SANITY_CHECK(value, eps, errorType);
}
else
OCL_PERF_ELSE
}