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 47 CV_AMLTest::CV_AMLTest( const char* _modelName ) : CV_MLBaseTest( _modelName ) 48 { 49 validationFN = "avalidation.xml"; 50 } 51 52 int CV_AMLTest::run_test_case( int testCaseIdx ) 53 { 54 int code = cvtest::TS::OK; 55 code = prepare_test_case( testCaseIdx ); 56 57 if (code == cvtest::TS::OK) 58 { 59 //#define GET_STAT 60 #ifdef GET_STAT 61 const char* data_name = ((CvFileNode*)cvGetSeqElem( dataSetNames, testCaseIdx ))->data.str.ptr; 62 printf("%s, %s ", name, data_name); 63 const int icount = 100; 64 float res[icount]; 65 for (int k = 0; k < icount; k++) 66 { 67 #endif 68 data->shuffleTrainTest(); 69 code = train( testCaseIdx ); 70 #ifdef GET_STAT 71 float case_result = get_error(); 72 73 res[k] = case_result; 74 } 75 float mean = 0, sigma = 0; 76 for (int k = 0; k < icount; k++) 77 { 78 mean += res[k]; 79 } 80 mean = mean /icount; 81 for (int k = 0; k < icount; k++) 82 { 83 sigma += (res[k] - mean)*(res[k] - mean); 84 } 85 sigma = sqrt(sigma/icount); 86 printf("%f, %f\n", mean, sigma); 87 #endif 88 } 89 return code; 90 } 91 92 int CV_AMLTest::validate_test_results( int testCaseIdx ) 93 { 94 int iters; 95 float mean, sigma; 96 // read validation params 97 FileNode resultNode = 98 validationFS.getFirstTopLevelNode()["validation"][modelName][dataSetNames[testCaseIdx]]["result"]; 99 resultNode["iter_count"] >> iters; 100 if ( iters > 0) 101 { 102 resultNode["mean"] >> mean; 103 resultNode["sigma"] >> sigma; 104 model->save(format("/Users/vp/tmp/dtree/testcase_%02d.cur.yml", testCaseIdx)); 105 float curErr = get_test_error( testCaseIdx ); 106 const int coeff = 4; 107 ts->printf( cvtest::TS::LOG, "Test case = %d; test error = %f; mean error = %f (diff=%f), %d*sigma = %f\n", 108 testCaseIdx, curErr, mean, abs( curErr - mean), coeff, coeff*sigma ); 109 if ( abs( curErr - mean) > coeff*sigma ) 110 { 111 ts->printf( cvtest::TS::LOG, "abs(%f - %f) > %f - OUT OF RANGE!\n", curErr, mean, coeff*sigma, coeff ); 112 return cvtest::TS::FAIL_BAD_ACCURACY; 113 } 114 else 115 ts->printf( cvtest::TS::LOG, ".\n" ); 116 117 } 118 else 119 { 120 ts->printf( cvtest::TS::LOG, "validation info is not suitable" ); 121 return cvtest::TS::FAIL_INVALID_TEST_DATA; 122 } 123 return cvtest::TS::OK; 124 } 125 126 TEST(ML_DTree, regression) { CV_AMLTest test( CV_DTREE ); test.safe_run(); } 127 TEST(ML_Boost, regression) { CV_AMLTest test( CV_BOOST ); test.safe_run(); } 128 TEST(ML_RTrees, regression) { CV_AMLTest test( CV_RTREES ); test.safe_run(); } 129 TEST(DISABLED_ML_ERTrees, regression) { CV_AMLTest test( CV_ERTREES ); test.safe_run(); } 130 131 /* End of file. */ 132
