/////////////////////////////////////////////////////////////////////////////////////// // // 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 // 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. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // 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, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" #ifdef HAVE_OPENCL using namespace cv; using namespace cv::ocl; using namespace cvtest; using namespace testing; using namespace std; ////////////////////////////////////////////////////////////////////////// PARAM_TEST_CASE(Kalman, int, int) { int size_; int iteration; virtual void SetUp() { size_ = GET_PARAM(0); iteration = GET_PARAM(1); } }; OCL_TEST_P(Kalman, Accuracy) { const int Dim = size_; const int Steps = iteration; const double max_init = 1; const double max_noise = 0.1; Mat sample_mat(Dim, 1, CV_32F), temp_mat; oclMat Sample(Dim, 1, CV_32F); oclMat Temp(Dim, 1, CV_32F); Mat Temp_cpu(Dim, 1, CV_32F); Size size(Sample.cols, Sample.rows); sample_mat = randomMat(size, Sample.type(), -max_init, max_init, false); Sample.upload(sample_mat); //ocl start cv::ocl::KalmanFilter kalman_filter_ocl; kalman_filter_ocl.init(Dim, Dim); cv::ocl::setIdentity(kalman_filter_ocl.errorCovPre, 1); cv::ocl::setIdentity(kalman_filter_ocl.measurementMatrix, 1); cv::ocl::setIdentity(kalman_filter_ocl.errorCovPost, 1); kalman_filter_ocl.measurementNoiseCov.setTo(Scalar::all(0)); kalman_filter_ocl.statePre.setTo(Scalar::all(0)); kalman_filter_ocl.statePost.setTo(Scalar::all(0)); kalman_filter_ocl.correct(Sample); //ocl end //cpu start cv::KalmanFilter kalman_filter_cpu; kalman_filter_cpu.init(Dim, Dim); cv::setIdentity(kalman_filter_cpu.errorCovPre, 1); cv::setIdentity(kalman_filter_cpu.measurementMatrix, 1); cv::setIdentity(kalman_filter_cpu.errorCovPost, 1); kalman_filter_cpu.measurementNoiseCov.setTo(Scalar::all(0)); kalman_filter_cpu.statePre.setTo(Scalar::all(0)); kalman_filter_cpu.statePost.setTo(Scalar::all(0)); kalman_filter_cpu.correct(sample_mat); //cpu end //test begin for(int i = 0; i<Steps; i++) { kalman_filter_ocl.predict(); kalman_filter_cpu.predict(); cv::gemm(kalman_filter_cpu.transitionMatrix, sample_mat, 1, cv::Mat(), 0, Temp_cpu); Size size1(Temp.cols, Temp.rows); Mat temp = randomMat(size1, Temp.type(), 0, 0xffff, false); cv::multiply(2, temp, temp); cv::subtract(temp, 1, temp); cv::multiply(max_noise, temp, temp); cv::add(temp, Temp_cpu, Temp_cpu); Temp.upload(Temp_cpu); Temp.copyTo(Sample); Temp_cpu.copyTo(sample_mat); kalman_filter_ocl.correct(Temp); kalman_filter_cpu.correct(Temp_cpu); } //test end EXPECT_MAT_NEAR(kalman_filter_cpu.statePost, kalman_filter_ocl.statePost, 0); } INSTANTIATE_TEST_CASE_P(OCL_Video, Kalman, Combine(Values(3, 7), Values(30))); #endif // HAVE_OPENCL