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opencv: Use cv::AutoBuffer<>::data()

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This commit is contained in:
Alexander Alekhin
2018-06-10 22:42:00 +00:00
committed by Alexander Alekhin
parent 135ea264ef
commit b09a4a98d4
90 changed files with 333 additions and 339 deletions
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apps/traincascade/old_ml_boost.cpp
+11 -11
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@@ -168,7 +168,7 @@ CvBoostTree::try_split_node( CvDTreeNode* node )
// store the responses for the corresponding training samples
double* weak_eval = ensemble->get_weak_response()->data.db;
cv::AutoBuffer<int> inn_buf(node->sample_count);
const int* labels = data->get_cv_labels( node, (int*)inn_buf );
const int* labels = data->get_cv_labels(node, inn_buf.data());
int i, count = node->sample_count;
double value = node->value;
@@ -191,7 +191,7 @@ CvBoostTree::calc_node_dir( CvDTreeNode* node )
if( data->get_var_type(vi) >= 0 ) // split on categorical var
{
cv::AutoBuffer<int> inn_buf(n);
const int* cat_labels = data->get_cat_var_data( node, vi, (int*)inn_buf );
const int* cat_labels = data->get_cat_var_data(node, vi, inn_buf.data());
const int* subset = node->split->subset;
double sum = 0, sum_abs = 0;
@@ -210,7 +210,7 @@ CvBoostTree::calc_node_dir( CvDTreeNode* node )
else // split on ordered var
{
cv::AutoBuffer<uchar> inn_buf(2*n*sizeof(int)+n*sizeof(float));
float* values_buf = (float*)(uchar*)inn_buf;
float* values_buf = (float*)inn_buf.data();
int* sorted_indices_buf = (int*)(values_buf + n);
int* sample_indices_buf = sorted_indices_buf + n;
const float* values = 0;
@@ -260,7 +260,7 @@ CvBoostTree::find_split_ord_class( CvDTreeNode* node, int vi, float init_quality
cv::AutoBuffer<uchar> inn_buf;
if( !_ext_buf )
inn_buf.allocate(n*(3*sizeof(int)+sizeof(float)));
uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
float* values_buf = (float*)ext_buf;
int* sorted_indices_buf = (int*)(values_buf + n);
int* sample_indices_buf = sorted_indices_buf + n;
@@ -369,7 +369,7 @@ CvBoostTree::find_split_cat_class( CvDTreeNode* node, int vi, float init_quality
cv::AutoBuffer<uchar> inn_buf((2*mi+3)*sizeof(double) + mi*sizeof(double*));
if( !_ext_buf)
inn_buf.allocate( base_size + 2*n*sizeof(int) );
uchar* base_buf = (uchar*)inn_buf;
uchar* base_buf = inn_buf.data();
uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;
int* cat_labels_buf = (int*)ext_buf;
@@ -490,7 +490,7 @@ CvBoostTree::find_split_ord_reg( CvDTreeNode* node, int vi, float init_quality,
cv::AutoBuffer<uchar> inn_buf;
if( !_ext_buf )
inn_buf.allocate(2*n*(sizeof(int)+sizeof(float)));
uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
float* values_buf = (float*)ext_buf;
int* indices_buf = (int*)(values_buf + n);
@@ -559,7 +559,7 @@ CvBoostTree::find_split_cat_reg( CvDTreeNode* node, int vi, float init_quality,
cv::AutoBuffer<uchar> inn_buf(base_size);
if( !_ext_buf )
inn_buf.allocate(base_size + n*(2*sizeof(int) + sizeof(float)));
uchar* base_buf = (uchar*)inn_buf;
uchar* base_buf = inn_buf.data();
uchar* ext_buf = _ext_buf ? _ext_buf : base_buf + base_size;
int* cat_labels_buf = (int*)ext_buf;
@@ -652,7 +652,7 @@ CvBoostTree::find_surrogate_split_ord( CvDTreeNode* node, int vi, uchar* _ext_bu
cv::AutoBuffer<uchar> inn_buf;
if( !_ext_buf )
inn_buf.allocate(n*(2*sizeof(int)+sizeof(float)));
uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
float* values_buf = (float*)ext_buf;
int* indices_buf = (int*)(values_buf + n);
int* sample_indices_buf = indices_buf + n;
@@ -733,7 +733,7 @@ CvBoostTree::find_surrogate_split_cat( CvDTreeNode* node, int vi, uchar* _ext_bu
cv::AutoBuffer<uchar> inn_buf(base_size);
if( !_ext_buf )
inn_buf.allocate(base_size + n*sizeof(int));
uchar* ext_buf = _ext_buf ? _ext_buf : (uchar*)inn_buf;
uchar* ext_buf = _ext_buf ? _ext_buf : inn_buf.data();
int* cat_labels_buf = (int*)ext_buf;
const int* cat_labels = data->get_cat_var_data(node, vi, cat_labels_buf);
@@ -797,7 +797,7 @@ CvBoostTree::calc_node_value( CvDTreeNode* node )
int i, n = node->sample_count;
const double* weights = ensemble->get_weights()->data.db;
cv::AutoBuffer<uchar> inn_buf(n*(sizeof(int) + ( data->is_classifier ? sizeof(int) : sizeof(int) + sizeof(float))));
int* labels_buf = (int*)(uchar*)inn_buf;
int* labels_buf = (int*)inn_buf.data();
const int* labels = data->get_cv_labels(node, labels_buf);
double* subtree_weights = ensemble->get_subtree_weights()->data.db;
double rcw[2] = {0,0};
@@ -1147,7 +1147,7 @@ CvBoost::update_weights( CvBoostTree* tree )
_buf_size += data->get_length_subbuf()*(sizeof(float)+sizeof(uchar));
}
inn_buf.allocate(_buf_size);
uchar* cur_buf_pos = (uchar*)inn_buf;
uchar* cur_buf_pos = inn_buf.data();
if ( (params.boost_type == LOGIT) || (params.boost_type == GENTLE) )
{