potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-31 00:03:03 +04:00
Code Packages Releases Wiki Activity

Partially back-port #25075 to 4.x

Browse Source
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
Download Patch File Download Diff File Expand all files Collapse all files
apps/traincascade/old_ml_data.cpp
+36 -36
View File
@@ -284,7 +284,7 @@ const CvMat* CvMLData::get_missing() const
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
__END__;
@@ -331,7 +331,7 @@ void CvMLData::set_delimiter(char ch)
__BEGIN__;
if (ch == miss_ch /*|| ch == flt_separator*/)
CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
CV_ERROR(cv::Error::StsBadArg, "delimited, miss_character and flt_separator must be different");
delimiter = ch;
@@ -349,7 +349,7 @@ void CvMLData::set_miss_ch(char ch)
__BEGIN__;
if (ch == delimiter/* || ch == flt_separator*/)
CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
CV_ERROR(cv::Error::StsBadArg, "delimited, miss_character and flt_separator must be different");
miss_ch = ch;
@@ -367,10 +367,10 @@ void CvMLData::set_response_idx( int idx )
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
if ( idx >= values->cols)
CV_ERROR( CV_StsBadArg, "idx value is not correct" );
CV_ERROR( cv::Error::StsBadArg, "idx value is not correct" );
if ( response_idx >= 0 )
chahge_var_idx( response_idx, true );
@@ -387,7 +387,7 @@ int CvMLData::get_response_idx() const
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
__END__;
return response_idx;
}
@@ -400,19 +400,19 @@ void CvMLData::change_var_type( int var_idx, int type )
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
var_count = values->cols;
if ( var_idx < 0 || var_idx >= var_count)
CV_ERROR( CV_StsBadArg, "var_idx is not correct" );
CV_ERROR( cv::Error::StsBadArg, "var_idx is not correct" );
if ( type != CV_VAR_ORDERED && type != CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "type is not correct" );
CV_ERROR( cv::Error::StsBadArg, "type is not correct" );
assert( var_types );
if ( var_types->data.ptr[var_idx] == CV_VAR_CATEGORICAL && type == CV_VAR_ORDERED)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
CV_ERROR( cv::Error::StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[var_idx] = (uchar)type;
__END__;
@@ -428,7 +428,7 @@ void CvMLData::set_var_types( const char* str )
const char* ord = 0, *cat = 0;
int var_count = 0, set_var_type_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
var_count = values->cols;
@@ -437,7 +437,7 @@ void CvMLData::set_var_types( const char* str )
ord = strstr( str, "ord" );
cat = strstr( str, "cat" );
if ( !ord && !cat )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
if ( !ord && strlen(cat) == 3 ) // str == "cat"
{
@@ -455,19 +455,19 @@ void CvMLData::set_var_types( const char* str )
{
char* stopstring = NULL;
if ( ord[3] != '[')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
ord += 4; // pass "ord["
do
{
int b1 = (int)strtod( ord, &stopstring );
if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
ord = stopstring + 1;
if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
{
if ( var_types->data.ptr[b1] == CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
CV_ERROR( cv::Error::StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[b1] = CV_VAR_ORDERED;
set_var_type_count++;
}
@@ -477,39 +477,39 @@ void CvMLData::set_var_types( const char* str )
{
int b2 = (int)strtod( ord, &stopstring);
if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
ord = stopstring + 1;
for (int i = b1; i <= b2; i++)
{
if ( var_types->data.ptr[i] == CV_VAR_CATEGORICAL)
CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
CV_ERROR( cv::Error::StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
var_types->data.ptr[i] = CV_VAR_ORDERED;
}
set_var_type_count += b2 - b1 + 1;
}
else
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
}
}
while (*stopstring != ']');
if ( stopstring[1] != '\0' && stopstring[1] != ',')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
}
if ( cat ) // parse cat str
{
char* stopstring = NULL;
if ( cat[3] != '[')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
cat += 4; // pass "cat["
do
{
int b1 = (int)strtod( cat, &stopstring );
if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
cat = stopstring + 1;
if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
{
@@ -522,25 +522,25 @@ void CvMLData::set_var_types( const char* str )
{
int b2 = (int)strtod( cat, &stopstring);
if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
cat = stopstring + 1;
for (int i = b1; i <= b2; i++)
var_types->data.ptr[i] = CV_VAR_CATEGORICAL;
set_var_type_count += b2 - b1 + 1;
}
else
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
}
}
while (*stopstring != ']');
if ( stopstring[1] != '\0' && stopstring[1] != ',')
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
}
if (set_var_type_count != var_count)
CV_ERROR( CV_StsBadArg, "types string is not correct" );
CV_ERROR( cv::Error::StsBadArg, "types string is not correct" );
__END__;
}
@@ -553,7 +553,7 @@ const CvMat* CvMLData::get_var_types()
uchar *var_types_out_ptr = 0;
int avcount, vt_size;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
assert( var_idx_mask );
@@ -597,7 +597,7 @@ const CvMat* CvMLData::get_responses()
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
var_count = values->cols;
if ( response_idx < 0 || response_idx >= var_count )
@@ -621,7 +621,7 @@ void CvMLData::set_train_test_split( const CvTrainTestSplit * spl)
int sample_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
sample_count = values->rows;
@@ -631,14 +631,14 @@ void CvMLData::set_train_test_split( const CvTrainTestSplit * spl)
{
train_sample_count = spl->train_sample_part.count;
if (train_sample_count > sample_count)
CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
CV_ERROR( cv::Error::StsBadArg, "train samples count is not correct" );
train_sample_count = train_sample_count<=0 ? sample_count : train_sample_count;
}
else // dtype.train_sample_part_mode == CV_PORTION
{
train_sample_portion = spl->train_sample_part.portion;
if ( train_sample_portion > 1)
CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
CV_ERROR( cv::Error::StsBadArg, "train samples count is not correct" );
train_sample_portion = train_sample_portion <= FLT_EPSILON ||
1 - train_sample_portion <= FLT_EPSILON ? 1 : train_sample_portion;
train_sample_count = std::max(1, cvFloor( train_sample_portion * sample_count ));
@@ -680,7 +680,7 @@ const CvMat* CvMLData::get_train_sample_idx() const
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
__END__;
return train_sample_idx;
@@ -692,7 +692,7 @@ const CvMat* CvMLData::get_test_sample_idx() const
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
__END__;
return test_sample_idx;
@@ -704,7 +704,7 @@ void CvMLData::mix_train_and_test_idx()
__BEGIN__;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
__END__;
if ( !sample_idx)
@@ -731,7 +731,7 @@ const CvMat* CvMLData::get_var_idx()
int avcount = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
assert( var_idx_mask );
@@ -776,12 +776,12 @@ void CvMLData::change_var_idx( int vi, bool state )
int var_count = 0;
if ( !values )
CV_ERROR( CV_StsInternal, "data is empty" );
CV_ERROR( cv::Error::StsInternal, "data is empty" );
var_count = values->cols;
if ( vi < 0 || vi >= var_count)
CV_ERROR( CV_StsBadArg, "variable index is not correct" );
CV_ERROR( cv::Error::StsBadArg, "variable index is not correct" );
assert( var_idx_mask );
var_idx_mask->data.ptr[vi] = state;