From b5f570091163771c7e45d1888a23c64532126d7f Mon Sep 17 00:00:00 2001 From: Marina Kolpakova Date: Sat, 7 Apr 2012 16:06:47 +0000 Subject: [PATCH] fixed build with gcc 4.5+ (#1774) --- modules/legacy/src/em.cpp | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/modules/legacy/src/em.cpp b/modules/legacy/src/em.cpp index d7a71b1a96..4463984979 100644 --- a/modules/legacy/src/em.cpp +++ b/modules/legacy/src/em.cpp @@ -105,7 +105,7 @@ float CvEM::predict( const CvMat* _sample, CvMat* _probs, bool isNormalize ) const { Mat prbs0 = cvarrToMat(_probs), prbs = prbs0, sample = cvarrToMat(_sample); - int cls = emObj.predict(sample, _probs ? _OutputArray(prbs) : _OutputArray::_OutputArray()); + int cls = emObj.predict(sample, _probs ? _OutputArray(prbs) : cv::noArray()); if(_probs) { if(isNormalize) @@ -212,15 +212,15 @@ bool CvEM::train( const Mat& _samples, const Mat& _sample_idx, emObj = EM(_params.nclusters, _params.cov_mat_type, _params.term_crit); bool isOk = false; if( _params.start_step == EM::START_AUTO_STEP ) - isOk = emObj.train(_samples, _labels ? _OutputArray(*_labels) : _OutputArray::_OutputArray(), + isOk = emObj.train(_samples, _labels ? _OutputArray(*_labels) : cv::noArray(), probs, likelihoods); else if( _params.start_step == EM::START_E_STEP ) isOk = emObj.trainE(_samples, means, covsHdrs, weights, - _labels ? _OutputArray(*_labels) : _OutputArray::_OutputArray(), + _labels ? _OutputArray(*_labels) : cv::noArray(), probs, likelihoods); else if( _params.start_step == EM::START_M_STEP ) isOk = emObj.trainM(_samples, prbs, - _labels ? _OutputArray(*_labels) : _OutputArray::_OutputArray(), + _labels ? _OutputArray(*_labels) : cv::noArray(), probs, likelihoods); else CV_Error(CV_StsBadArg, "Bad start type of EM algorithm"); @@ -237,7 +237,7 @@ bool CvEM::train( const Mat& _samples, const Mat& _sample_idx, float CvEM::predict( const Mat& _sample, Mat* _probs, bool isNormalize ) const { - int cls = emObj.predict(_sample, _probs ? _OutputArray(*_probs) : _OutputArray::_OutputArray()); + int cls = emObj.predict(_sample, _probs ? _OutputArray(*_probs) : cv::noArray()); if(_probs && isNormalize) normalize(*_probs, *_probs, 1, 0, NORM_L1); -- GitLab