opencv/modules/ocl/perf/perf_kalman.cpp

93 lines
3.4 KiB
C++

/*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:
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// * Redistribution's of source code must retain the above copyright notice,
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//M*/
#include "perf_precomp.hpp"
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_);
}