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124 lines
4.5 KiB
C++
124 lines
4.5 KiB
C++
///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Jin Ma, jin@multicorewareinc.com
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// Xiaopeng Fu, fuxiaopeng2222@163.com
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// Erping Pang, pang_er_ping@163.com
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other oclMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#ifdef HAVE_OPENCL
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using namespace cv;
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using namespace cv::ocl;
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using namespace cvtest;
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using namespace testing;
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///////K-NEAREST NEIGHBOR//////////////////////////
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static void genTrainData(Mat& trainData, int trainDataRow, int trainDataCol,
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Mat& trainLabel = Mat().setTo(Scalar::all(0)), int nClasses = 0)
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{
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cv::RNG &rng = TS::ptr()->get_rng();
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cv::Size size(trainDataCol, trainDataRow);
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trainData = randomMat(rng, size, CV_32FC1, 1.0, 1000.0, false);
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if(nClasses != 0)
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{
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cv::Size size1(trainDataRow, 1);
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trainLabel = randomMat(rng, size1, CV_8UC1, 0, nClasses - 1, false);
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trainLabel.convertTo(trainLabel, CV_32FC1);
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}
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}
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PARAM_TEST_CASE(KNN, int, Size, int, bool)
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{
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int k;
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int trainDataCol;
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int testDataRow;
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int nClass;
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bool regression;
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virtual void SetUp()
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{
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k = GET_PARAM(0);
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nClass = GET_PARAM(2);
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trainDataCol = GET_PARAM(1).width;
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testDataRow = GET_PARAM(1).height;
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regression = GET_PARAM(3);
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}
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};
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TEST_P(KNN, Accuracy)
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{
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Mat trainData, trainLabels;
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const int trainDataRow = 500;
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genTrainData(trainData, trainDataRow, trainDataCol, trainLabels, nClass);
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Mat testData, testLabels;
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genTrainData(testData, testDataRow, trainDataCol);
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KNearestNeighbour knn_ocl;
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CvKNearest knn_cpu;
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Mat best_label_cpu;
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oclMat best_label_ocl;
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/*ocl k-Nearest_Neighbor start*/
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oclMat trainData_ocl;
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trainData_ocl.upload(trainData);
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Mat simpleIdx;
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knn_ocl.train(trainData, trainLabels, simpleIdx, regression);
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oclMat testdata;
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testdata.upload(testData);
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knn_ocl.find_nearest(testdata, k, best_label_ocl);
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/*ocl k-Nearest_Neighbor end*/
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/*cpu k-Nearest_Neighbor start*/
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knn_cpu.train(trainData, trainLabels, simpleIdx, regression);
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knn_cpu.find_nearest(testData, k, &best_label_cpu);
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/*cpu k-Nearest_Neighbor end*/
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if(regression)
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{
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EXPECT_MAT_SIMILAR(Mat(best_label_ocl), best_label_cpu, 1e-5);
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}
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else
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{
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EXPECT_MAT_NEAR(Mat(best_label_ocl), best_label_cpu, 0.0);
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}
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}
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INSTANTIATE_TEST_CASE_P(OCL_ML, KNN, Combine(Values(6, 5), Values(Size(200, 400), Size(300, 600)),
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Values(4, 3), Values(false, true)));
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#endif // HAVE_OPENCL
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