Added performance for Kalman Filter.
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								modules/ocl/perf/perf_kalman.cpp
									
									
									
									
									
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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: | ||||
| // | ||||
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| // | ||||
| //   * 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 oclMaterials 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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| // | ||||
| //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::ocl::oclMat dsample(sample); | ||||
|  | ||||
|     cv::Mat statePre_; | ||||
|  | ||||
|     if(RUN_PLAIN_IMPL) | ||||
|     { | ||||
|         TEST_CYCLE() | ||||
|         { | ||||
|             cv::KalmanFilter kalman; | ||||
|             kalman.init(dim, dim); | ||||
|             kalman.correct(sample); | ||||
|             kalman.predict(); | ||||
|             statePre_ = kalman.statePre; | ||||
|         } | ||||
|         SANITY_CHECK(statePre_); | ||||
|     }else if(RUN_OCL_IMPL) | ||||
|     { | ||||
|         OCL_TEST_CYCLE() | ||||
|         { | ||||
|             cv::ocl::KalmanFilter kalman_ocl; | ||||
|             kalman_ocl.init(dim, dim);  | ||||
|             kalman_ocl.correct(dsample); | ||||
|             kalman_ocl.predict(); | ||||
|             kalman_ocl.statePre.download(statePre_); | ||||
|         } | ||||
|         SANITY_CHECK(statePre_); | ||||
|     }else | ||||
|         OCL_PERF_ELSE | ||||
| } | ||||
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