/*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 // Jin Ma, jin@multicorewareinc.com // Xiaopeng Fu, fuxiaopeng2222@163.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 "perf_precomp.hpp" using namespace perf; using namespace std; using namespace cv::ocl; using namespace cv; using std::tr1::tuple; using std::tr1::get; ////////////////////////////////// K-NEAREST NEIGHBOR //////////////////////////////////// static void genData(Mat& trainData, Size size, Mat& trainLabel = Mat().setTo(Scalar::all(0)), int nClasses = 0) { trainData.create(size, CV_32FC1); randu(trainData, 1.0, 100.0); if(nClasses != 0) { trainLabel.create(size.height, 1, CV_8UC1); randu(trainLabel, 0, nClasses - 1); trainLabel.convertTo(trainLabel, CV_32FC1); } } typedef tuple KNNParamType; typedef TestBaseWithParam KNNFixture; PERF_TEST_P(KNNFixture, KNN, testing::Values(1000, 2000, 4000)) { KNNParamType params = GetParam(); const int rows = get<0>(params); int columns = 100; int k = rows/250; Mat trainData, trainLabels; Size size(columns, rows); genData(trainData, size, trainLabels, 3); Mat testData; genData(testData, size); Mat best_label; if(RUN_PLAIN_IMPL) { TEST_CYCLE() { CvKNearest knn_cpu; knn_cpu.train(trainData, trainLabels); knn_cpu.find_nearest(testData, k, &best_label); } }else if(RUN_OCL_IMPL) { cv::ocl::oclMat best_label_ocl; cv::ocl::oclMat testdata; testdata.upload(testData); OCL_TEST_CYCLE() { cv::ocl::KNearestNeighbour knn_ocl; knn_ocl.train(trainData, trainLabels); knn_ocl.find_nearest(testdata, k, best_label_ocl); } best_label_ocl.download(best_label); }else OCL_PERF_ELSE SANITY_CHECK(best_label); }