opencv/modules/ocl/perf/perf_kalman.cpp
Andrey Pavlenko 2b6fca68bf fixing typo
2013-10-25 18:00:46 +04:00

104 lines
3.5 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// License Agreement
// For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
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#include "perf_precomp.hpp"
#ifdef HAVE_CLAMDBLAS
using namespace perf;
using namespace std;
using namespace cv::ocl;
using namespace cv;
using std::tr1::tuple;
using std::tr1::get;
///////////// Kalman Filter ////////////////////////
typedef tuple<int> KalmanFilterType;
typedef TestBaseWithParam<KalmanFilterType> KalmanFilterFixture;
PERF_TEST_P(KalmanFilterFixture, KalmanFilter,
::testing::Values(1000, 1500))
{
KalmanFilterType params = GetParam();
const int dim = get<0>(params);
cv::Mat sample(dim, 1, CV_32FC1), dresult;
randu(sample, -1, 1);
cv::Mat statePre_;
if (RUN_PLAIN_IMPL)
{
cv::KalmanFilter kalman;
TEST_CYCLE()
{
kalman.init(dim, dim);
kalman.correct(sample);
kalman.predict();
}
statePre_ = kalman.statePre;
}
else if(RUN_OCL_IMPL)
{
cv::ocl::oclMat dsample(sample);
cv::ocl::KalmanFilter kalman_ocl;
OCL_TEST_CYCLE()
{
kalman_ocl.init(dim, dim);
kalman_ocl.correct(dsample);
kalman_ocl.predict();
}
kalman_ocl.statePre.download(statePre_);
}
else
OCL_PERF_ELSE
SANITY_CHECK(statePre_);
}
#endif // HAVE_CLAMDBLAS