opencv/modules/ocl/perf/perf_kalman.cpp

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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