diff --git a/modules/ml/src/svm.cpp b/modules/ml/src/svm.cpp index 3c970f201a..9752848b9a 100644 --- a/modules/ml/src/svm.cpp +++ b/modules/ml/src/svm.cpp @@ -1551,25 +1551,28 @@ void CvSVM::optimize_linear_svm() return; int var_count = get_var_count(); - int sample_size = (int)(var_count*sizeof(sv[0][0])); + cv::AutoBuffer vbuf(var_count); + double* v = vbuf; float** new_sv = (float**)cvMemStorageAlloc(storage, df_count*sizeof(new_sv[0])); for( i = 0; i < df_count; i++ ) { - new_sv[i] = (float*)cvMemStorageAlloc(storage, sample_size); + new_sv[i] = (float*)cvMemStorageAlloc(storage, var_count*sizeof(new_sv[i][0])); float* dst = new_sv[i]; - memset(dst, 0, sample_size); + memset(v, 0, var_count*sizeof(v[0])); int j, k, sv_count = df[i].sv_count; for( j = 0; j < sv_count; j++ ) { - const float* src = class_count > 1 ? sv[df[i].sv_index[j]] : sv[j]; + const float* src = class_count > 1 && df[i].sv_index ? sv[df[i].sv_index[j]] : sv[j]; double a = df[i].alpha[j]; for( k = 0; k < var_count; k++ ) - dst[k] = (float)(dst[k] + src[k]*a); + v[k] += src[k]*a; } + for( k = 0; k < var_count; k++ ) + dst[k] = (float)v[k]; df[i].sv_count = 1; df[i].alpha[0] = 1.; - if( class_count > 1 ) + if( class_count > 1 && df[i].sv_index ) df[i].sv_index[0] = i; } @@ -2570,7 +2573,8 @@ void CvSVM::read( CvFileStorage* fs, CvFileNode* svm_node ) CV_NEXT_SEQ_ELEM( df_node->data.seq->elem_size, reader ); } - optimize_linear_svm(); + if( cvReadIntByName(fs, svm_node, "optimize_linear", 1) != 0 ) + optimize_linear_svm(); create_kernel(); __END__; diff --git a/modules/ml/test/test_mltests2.cpp b/modules/ml/test/test_mltests2.cpp index 80776b4ced..0e7892c510 100644 --- a/modules/ml/test/test_mltests2.cpp +++ b/modules/ml/test/test_mltests2.cpp @@ -769,7 +769,11 @@ void CV_MLBaseTest::load( const char* filename ) else if( !modelName.compare(CV_KNEAREST) ) knearest->load( filename ); else if( !modelName.compare(CV_SVM) ) + { + delete svm; + svm = new CvSVM; svm->load( filename ); + } else if( !modelName.compare(CV_ANN) ) ann->load( filename ); else if( !modelName.compare(CV_DTREE) ) diff --git a/modules/ml/test/test_save_load.cpp b/modules/ml/test/test_save_load.cpp index 889b98b62b..9fd31b9f24 100644 --- a/modules/ml/test/test_save_load.cpp +++ b/modules/ml/test/test_save_load.cpp @@ -82,32 +82,53 @@ int CV_SLMLTest::validate_test_results( int testCaseIdx ) int code = cvtest::TS::OK; // 1. compare files - ifstream f1( fname1.c_str() ), f2( fname2.c_str() ); - string s1, s2; - int lineIdx = 0; - CV_Assert( f1.is_open() && f2.is_open() ); - for( ; !f1.eof() && !f2.eof(); lineIdx++ ) + FILE *fs1 = fopen(fname1.c_str(), "rb"), *fs2 = fopen(fname2.c_str(), "rb"); + size_t sz1 = 0, sz2 = 0; + if( !fs1 || !fs2 ) + code = cvtest::TS::FAIL_MISSING_TEST_DATA; + if( code >= 0 ) { - getline( f1, s1 ); - getline( f2, s2 ); - if( s1.compare(s2) ) + fseek(fs1, 0, SEEK_END); fseek(fs2, 0, SEEK_END); + sz1 = ftell(fs1); + sz2 = ftell(fs2); + fseek(fs1, 0, SEEK_SET); fseek(fs2, 0, SEEK_SET); + } + + if( sz1 != sz2 ) + code = cvtest::TS::FAIL_INVALID_OUTPUT; + + if( code >= 0 ) + { + const int BUFSZ = 1024; + uchar buf1[BUFSZ], buf2[BUFSZ]; + for( size_t pos = 0; pos < sz1; ) { - ts->printf( cvtest::TS::LOG, "first and second saved files differ in %n-line; first %n line: %s; second %n-line: %s", - lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() ); - code = cvtest::TS::FAIL_INVALID_OUTPUT; + size_t r1 = fread(buf1, 1, BUFSZ, fs1); + size_t r2 = fread(buf2, 1, BUFSZ, fs2); + if( r1 != r2 || memcmp(buf1, buf2, r1) != 0 ) + { + ts->printf( cvtest::TS::LOG, + "in test case %d first (%s) and second (%s) saved files differ in %d-th kb\n", + testCaseIdx, fname1.c_str(), fname2.c_str(), + (int)pos ); + code = cvtest::TS::FAIL_INVALID_OUTPUT; + break; + } + pos += r1; } } - if( !f1.eof() || !f2.eof() ) + + if(fs1) + fclose(fs1); + if(fs2) + fclose(fs2); + + // delete temporary files + if( code >= 0 ) { - ts->printf( cvtest::TS::LOG, "in test case %d first and second saved files differ in %n-line; first %n line: %s; second %n-line: %s", - testCaseIdx, lineIdx, lineIdx, s1.c_str(), lineIdx, s2.c_str() ); - code = cvtest::TS::FAIL_INVALID_OUTPUT; + remove( fname1.c_str() ); + remove( fname2.c_str() ); } - f1.close(); - f2.close(); - // delete temporary files - remove( fname1.c_str() ); - remove( fname2.c_str() ); // 2. compare responses CV_Assert( test_resps1.size() == test_resps2.size() ); @@ -133,4 +154,32 @@ TEST(ML_Boost, save_load) { CV_SLMLTest test( CV_BOOST ); test.safe_run(); } TEST(ML_RTrees, save_load) { CV_SLMLTest test( CV_RTREES ); test.safe_run(); } TEST(ML_ERTrees, save_load) { CV_SLMLTest test( CV_ERTREES ); test.safe_run(); } + +TEST(DISABLED_ML_SVM, linear_save_load) +{ + CvSVM svm1, svm2, svm3; + svm1.load("SVM45_X_38-1.xml"); + svm2.load("SVM45_X_38-2.xml"); + string tname = tempfile("a.xml"); + svm2.save(tname.c_str()); + svm3.load(tname.c_str()); + + ASSERT_EQ(svm1.get_var_count(), svm2.get_var_count()); + ASSERT_EQ(svm1.get_var_count(), svm3.get_var_count()); + + int m = 10000, n = svm1.get_var_count(); + Mat samples(m, n, CV_32F), r1, r2, r3; + randu(samples, 0., 1.); + + svm1.predict(samples, r1); + svm2.predict(samples, r2); + svm3.predict(samples, r3); + + double eps = 1e-4; + EXPECT_LE(norm(r1, r2, NORM_INF), eps); + EXPECT_LE(norm(r1, r3, NORM_INF), eps); + + remove(tname.c_str()); +} + /* End of file. */