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Partially back-port #25075 to 4.x

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This commit is contained in:
Alexander Smorkalov
2024-03-04 15:51:05 +03:00
parent ef611df09b
commit daa8f7dfc6
111 changed files with 1124 additions and 1124 deletions
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apps/traincascade/boost.cpp
+14 -14
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@@ -86,10 +86,10 @@ static CvMat* cvPreprocessIndexArray( const CvMat* idx_arr, int data_arr_size, b
int* dsti;
if( !CV_IS_MAT(idx_arr) )
CV_ERROR( CV_StsBadArg, "Invalid index array" );
CV_ERROR( cv::Error::StsBadArg, "Invalid index array" );
if( idx_arr->rows != 1 && idx_arr->cols != 1 )
CV_ERROR( CV_StsBadSize, "the index array must be 1-dimensional" );
CV_ERROR( cv::Error::StsBadSize, "the index array must be 1-dimensional" );
idx_total = idx_arr->rows + idx_arr->cols - 1;
srcb = idx_arr->data.ptr;
@@ -105,20 +105,20 @@ static CvMat* cvPreprocessIndexArray( const CvMat* idx_arr, int data_arr_size, b
// idx_arr is array of 1's and 0's -
// i.e. it is a mask of the selected components
if( idx_total != data_arr_size )
CV_ERROR( CV_StsUnmatchedSizes,
CV_ERROR( cv::Error::StsUnmatchedSizes,
"Component mask should contain as many elements as the total number of input variables" );
for( i = 0; i < idx_total; i++ )
idx_selected += srcb[i*step] != 0;
if( idx_selected == 0 )
CV_ERROR( CV_StsOutOfRange, "No components/input_variables is selected!" );
CV_ERROR( cv::Error::StsOutOfRange, "No components/input_variables is selected!" );
break;
case CV_32SC1:
// idx_arr is array of integer indices of selected components
if( idx_total > data_arr_size )
CV_ERROR( CV_StsOutOfRange,
CV_ERROR( cv::Error::StsOutOfRange,
"index array may not contain more elements than the total number of input variables" );
idx_selected = idx_total;
// check if sorted already
@@ -134,7 +134,7 @@ static CvMat* cvPreprocessIndexArray( const CvMat* idx_arr, int data_arr_size, b
}
break;
default:
CV_ERROR( CV_StsUnsupportedFormat, "Unsupported index array data type "
CV_ERROR( cv::Error::StsUnsupportedFormat, "Unsupported index array data type "
"(it should be 8uC1, 8sC1 or 32sC1)" );
}
@@ -156,13 +156,13 @@ static CvMat* cvPreprocessIndexArray( const CvMat* idx_arr, int data_arr_size, b
qsort( dsti, idx_total, sizeof(dsti[0]), icvCmpIntegers );
if( dsti[0] < 0 || dsti[idx_total-1] >= data_arr_size )
CV_ERROR( CV_StsOutOfRange, "the index array elements are out of range" );
CV_ERROR( cv::Error::StsOutOfRange, "the index array elements are out of range" );
if( check_for_duplicates )
{
for( i = 1; i < idx_total; i++ )
if( dsti[i] <= dsti[i-1] )
CV_ERROR( CV_StsBadArg, "There are duplicated index array elements" );
CV_ERROR( cv::Error::StsBadArg, "There are duplicated index array elements" );
}
}
@@ -218,7 +218,7 @@ bool CvCascadeBoostParams::read( const FileNode &node )
!boostTypeStr.compare( CC_LOGIT_BOOST ) ? CvBoost::LOGIT :
!boostTypeStr.compare( CC_GENTLE_BOOST ) ? CvBoost::GENTLE : -1;
if (boost_type == -1)
CV_Error( CV_StsBadArg, "unsupported Boost type" );
CV_Error( cv::Error::StsBadArg, "unsupported Boost type" );
node[CC_MINHITRATE] >> minHitRate;
node[CC_MAXFALSEALARM] >> maxFalseAlarm;
node[CC_TRIM_RATE] >> weight_trim_rate ;
@@ -228,7 +228,7 @@ bool CvCascadeBoostParams::read( const FileNode &node )
maxFalseAlarm <= 0 || maxFalseAlarm > 1 ||
weight_trim_rate <= 0 || weight_trim_rate > 1 ||
max_depth <= 0 || weak_count <= 0 )
CV_Error( CV_StsBadArg, "bad parameters range");
CV_Error( cv::Error::StsBadArg, "bad parameters range");
return true;
}
@@ -309,7 +309,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id
bool isMakeRootCopy = true;
if( !data_root )
CV_Error( CV_StsError, "No training data has been set" );
CV_Error( cv::Error::StsError, "No training data has been set" );
if( _subsample_idx )
{
@@ -547,7 +547,7 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat
// TODO: check responses: elements must be 0 or 1
if( _precalcValBufSize < 0 || _precalcIdxBufSize < 0)
CV_Error( CV_StsOutOfRange, "_numPrecalcVal and _numPrecalcIdx must be positive or 0" );
CV_Error( cv::Error::StsOutOfRange, "_numPrecalcVal and _numPrecalcIdx must be positive or 0" );
var_count = var_all = featureEvaluator->getNumFeatures() * featureEvaluator->getFeatureSize();
sample_count = _numSamples;
@@ -602,7 +602,7 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat
if ((uint64)effective_buf_width * (uint64)effective_buf_height != effective_buf_size)
{
CV_Error(CV_StsBadArg, "The memory buffer cannot be allocated since its size exceeds integer fields limit");
CV_Error(cv::Error::StsBadArg, "The memory buffer cannot be allocated since its size exceeds integer fields limit");
}
if ( is_buf_16u )
@@ -914,7 +914,7 @@ CvDTreeNode* CvCascadeBoostTree::predict( int sampleIdx ) const
{
CvDTreeNode* node = root;
if( !node )
CV_Error( CV_StsError, "The tree has not been trained yet" );
CV_Error( cv::Error::StsError, "The tree has not been trained yet" );
if ( ((CvCascadeBoostTrainData*)data)->featureEvaluator->getMaxCatCount() == 0 ) // ordered
{