1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // Intel License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2000, Intel Corporation, all rights reserved. 14 // Third party copyrights are property of their respective owners. 15 // 16 // Redistribution and use in source and binary forms, with or without modification, 17 // are permitted provided that the following conditions are met: 18 // 19 // * Redistribution's of source code must retain the above copyright notice, 20 // this list of conditions and the following disclaimer. 21 // 22 // * Redistribution's in binary form must reproduce the above copyright notice, 23 // this list of conditions and the following disclaimer in the documentation 24 // and/or other materials provided with the distribution. 25 // 26 // * The name of Intel Corporation may not be used to endorse or promote products 27 // derived from this software without specific prior written permission. 28 // 29 // This software is provided by the copyright holders and contributors "as is" and 30 // any express or implied warranties, including, but not limited to, the implied 31 // warranties of merchantability and fitness for a particular purpose are disclaimed. 32 // In no event shall the Intel Corporation or contributors be liable for any direct, 33 // indirect, incidental, special, exemplary, or consequential damages 34 // (including, but not limited to, procurement of substitute goods or services; 35 // loss of use, data, or profits; or business interruption) however caused 36 // and on any theory of liability, whether in contract, strict liability, 37 // or tort (including negligence or otherwise) arising in any way out of 38 // the use of this software, even if advised of the possibility of such damage. 39 // 40 //M*/ 41 42 #include "test_precomp.hpp" 43 44 using namespace cv; 45 using namespace std; 46 using cv::ml::SVM; 47 using cv::ml::TrainData; 48 49 //-------------------------------------------------------------------------------------------- 50 class CV_SVMTrainAutoTest : public cvtest::BaseTest { 51 public: 52 CV_SVMTrainAutoTest() {} 53 protected: 54 virtual void run( int start_from ); 55 }; 56 57 void CV_SVMTrainAutoTest::run( int /*start_from*/ ) 58 { 59 int datasize = 100; 60 cv::Mat samples = cv::Mat::zeros( datasize, 2, CV_32FC1 ); 61 cv::Mat responses = cv::Mat::zeros( datasize, 1, CV_32S ); 62 63 RNG rng(0); 64 for (int i = 0; i < datasize; ++i) 65 { 66 int response = rng.uniform(0, 2); // Random from {0, 1}. 67 samples.at<float>( i, 0 ) = rng.uniform(0.f, 0.5f) + response * 0.5f; 68 samples.at<float>( i, 1 ) = rng.uniform(0.f, 0.5f) + response * 0.5f; 69 responses.at<int>( i, 0 ) = response; 70 } 71 72 cv::Ptr<TrainData> data = TrainData::create( samples, cv::ml::ROW_SAMPLE, responses ); 73 cv::Ptr<SVM> svm = SVM::create(); 74 svm->trainAuto( data, 10 ); // 2-fold cross validation. 75 76 float test_data0[2] = {0.25f, 0.25f}; 77 cv::Mat test_point0 = cv::Mat( 1, 2, CV_32FC1, test_data0 ); 78 float result0 = svm->predict( test_point0 ); 79 float test_data1[2] = {0.75f, 0.75f}; 80 cv::Mat test_point1 = cv::Mat( 1, 2, CV_32FC1, test_data1 ); 81 float result1 = svm->predict( test_point1 ); 82 83 if ( fabs( result0 - 0 ) > 0.001 || fabs( result1 - 1 ) > 0.001 ) 84 { 85 ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); 86 } 87 } 88 89 TEST(ML_SVM, trainauto) { CV_SVMTrainAutoTest test; test.safe_run(); } 90
