|
|
|
@ -374,7 +374,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id |
|
|
|
|
if (is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short* udst_idx = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() + |
|
|
|
|
vi*sample_count + data_root->offset); |
|
|
|
|
(size_t)vi*sample_count + data_root->offset); |
|
|
|
|
for( int i = 0; i < num_valid; i++ ) |
|
|
|
|
{ |
|
|
|
|
idx = src_idx[i]; |
|
|
|
@ -387,7 +387,7 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int* idst_idx = buf->data.i + root->buf_idx*get_length_subbuf() + |
|
|
|
|
vi*sample_count + root->offset; |
|
|
|
|
(size_t)vi*sample_count + root->offset; |
|
|
|
|
for( int i = 0; i < num_valid; i++ ) |
|
|
|
|
{ |
|
|
|
|
idx = src_idx[i]; |
|
|
|
@ -404,14 +404,14 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id |
|
|
|
|
if (is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short* udst = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() + |
|
|
|
|
(workVarCount-1)*sample_count + root->offset); |
|
|
|
|
(size_t)(workVarCount-1)*sample_count + root->offset); |
|
|
|
|
for( int i = 0; i < count; i++ ) |
|
|
|
|
udst[i] = (unsigned short)src_lbls[sidx[i]]; |
|
|
|
|
} |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int* idst = buf->data.i + root->buf_idx*get_length_subbuf() + |
|
|
|
|
(workVarCount-1)*sample_count + root->offset; |
|
|
|
|
(size_t)(workVarCount-1)*sample_count + root->offset; |
|
|
|
|
for( int i = 0; i < count; i++ ) |
|
|
|
|
idst[i] = src_lbls[sidx[i]]; |
|
|
|
|
} |
|
|
|
@ -421,14 +421,14 @@ CvDTreeNode* CvCascadeBoostTrainData::subsample_data( const CvMat* _subsample_id |
|
|
|
|
if (is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short* sample_idx_dst = (unsigned short*)(buf->data.s + root->buf_idx*get_length_subbuf() + |
|
|
|
|
workVarCount*sample_count + root->offset); |
|
|
|
|
(size_t)workVarCount*sample_count + root->offset); |
|
|
|
|
for( int i = 0; i < count; i++ ) |
|
|
|
|
sample_idx_dst[i] = (unsigned short)sample_idx_src[sidx[i]]; |
|
|
|
|
} |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int* sample_idx_dst = buf->data.i + root->buf_idx*get_length_subbuf() + |
|
|
|
|
workVarCount*sample_count + root->offset; |
|
|
|
|
(size_t)workVarCount*sample_count + root->offset; |
|
|
|
|
for( int i = 0; i < count; i++ ) |
|
|
|
|
sample_idx_dst[i] = sample_idx_src[sidx[i]]; |
|
|
|
|
} |
|
|
|
@ -614,9 +614,9 @@ void CvCascadeBoostTrainData::setData( const CvFeatureEvaluator* _featureEvaluat |
|
|
|
|
|
|
|
|
|
// set sample labels
|
|
|
|
|
if (is_buf_16u) |
|
|
|
|
udst = (unsigned short*)(buf->data.s + work_var_count*sample_count); |
|
|
|
|
udst = (unsigned short*)(buf->data.s + (size_t)work_var_count*sample_count); |
|
|
|
|
else |
|
|
|
|
idst = buf->data.i + work_var_count*sample_count; |
|
|
|
|
idst = buf->data.i + (size_t)work_var_count*sample_count; |
|
|
|
|
|
|
|
|
|
for (int si = 0; si < sample_count; si++) |
|
|
|
|
{ |
|
|
|
@ -684,11 +684,11 @@ void CvCascadeBoostTrainData::get_ord_var_data( CvDTreeNode* n, int vi, float* o |
|
|
|
|
if ( vi < numPrecalcIdx ) |
|
|
|
|
{ |
|
|
|
|
if( !is_buf_16u ) |
|
|
|
|
*sortedIndices = buf->data.i + n->buf_idx*get_length_subbuf() + vi*sample_count + n->offset; |
|
|
|
|
*sortedIndices = buf->data.i + n->buf_idx*get_length_subbuf() + (size_t)vi*sample_count + n->offset; |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
const unsigned short* shortIndices = (const unsigned short*)(buf->data.s + n->buf_idx*get_length_subbuf() + |
|
|
|
|
vi*sample_count + n->offset ); |
|
|
|
|
(size_t)vi*sample_count + n->offset ); |
|
|
|
|
for( int i = 0; i < nodeSampleCount; i++ ) |
|
|
|
|
sortedIndicesBuf[i] = shortIndices[i]; |
|
|
|
|
|
|
|
|
@ -799,14 +799,14 @@ struct FeatureIdxOnlyPrecalc : ParallelLoopBody |
|
|
|
|
{ |
|
|
|
|
valCachePtr[si] = (*featureEvaluator)( fi, si ); |
|
|
|
|
if ( is_buf_16u ) |
|
|
|
|
*(udst + fi*sample_count + si) = (unsigned short)si; |
|
|
|
|
*(udst + (size_t)fi*sample_count + si) = (unsigned short)si; |
|
|
|
|
else |
|
|
|
|
*(idst + fi*sample_count + si) = si; |
|
|
|
|
*(idst + (size_t)fi*sample_count + si) = si; |
|
|
|
|
} |
|
|
|
|
if ( is_buf_16u ) |
|
|
|
|
icvSortUShAux( udst + fi*sample_count, sample_count, valCachePtr ); |
|
|
|
|
icvSortUShAux( udst + (size_t)fi*sample_count, sample_count, valCachePtr ); |
|
|
|
|
else |
|
|
|
|
icvSortIntAux( idst + fi*sample_count, sample_count, valCachePtr ); |
|
|
|
|
icvSortIntAux( idst + (size_t)fi*sample_count, sample_count, valCachePtr ); |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
const CvFeatureEvaluator* featureEvaluator; |
|
|
|
@ -835,14 +835,14 @@ struct FeatureValAndIdxPrecalc : ParallelLoopBody |
|
|
|
|
{ |
|
|
|
|
valCache->at<float>(fi,si) = (*featureEvaluator)( fi, si ); |
|
|
|
|
if ( is_buf_16u ) |
|
|
|
|
*(udst + fi*sample_count + si) = (unsigned short)si; |
|
|
|
|
*(udst + (size_t)fi*sample_count + si) = (unsigned short)si; |
|
|
|
|
else |
|
|
|
|
*(idst + fi*sample_count + si) = si; |
|
|
|
|
*(idst + (size_t)fi*sample_count + si) = si; |
|
|
|
|
} |
|
|
|
|
if ( is_buf_16u ) |
|
|
|
|
icvSortUShAux( udst + fi*sample_count, sample_count, valCache->ptr<float>(fi) ); |
|
|
|
|
icvSortUShAux( udst + (size_t)fi*sample_count, sample_count, valCache->ptr<float>(fi) ); |
|
|
|
|
else |
|
|
|
|
icvSortIntAux( idst + fi*sample_count, sample_count, valCache->ptr<float>(fi) ); |
|
|
|
|
icvSortIntAux( idst + (size_t)fi*sample_count, sample_count, valCache->ptr<float>(fi) ); |
|
|
|
|
} |
|
|
|
|
} |
|
|
|
|
const CvFeatureEvaluator* featureEvaluator; |
|
|
|
@ -1165,9 +1165,9 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node ) |
|
|
|
|
if (data->is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short *ldst = (unsigned short *)(buf->data.s + left->buf_idx*length_buf_row + |
|
|
|
|
(workVarCount-1)*scount + left->offset); |
|
|
|
|
(size_t)(workVarCount-1)*scount + left->offset); |
|
|
|
|
unsigned short *rdst = (unsigned short *)(buf->data.s + right->buf_idx*length_buf_row + |
|
|
|
|
(workVarCount-1)*scount + right->offset); |
|
|
|
|
(size_t)(workVarCount-1)*scount + right->offset); |
|
|
|
|
|
|
|
|
|
for( int i = 0; i < n; i++ ) |
|
|
|
|
{ |
|
|
|
@ -1188,9 +1188,9 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node ) |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int *ldst = buf->data.i + left->buf_idx*length_buf_row + |
|
|
|
|
(workVarCount-1)*scount + left->offset; |
|
|
|
|
(size_t)(workVarCount-1)*scount + left->offset; |
|
|
|
|
int *rdst = buf->data.i + right->buf_idx*length_buf_row + |
|
|
|
|
(workVarCount-1)*scount + right->offset; |
|
|
|
|
(size_t)(workVarCount-1)*scount + right->offset; |
|
|
|
|
|
|
|
|
|
for( int i = 0; i < n; i++ ) |
|
|
|
|
{ |
|
|
|
@ -1218,9 +1218,9 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node ) |
|
|
|
|
if (data->is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short* ldst = (unsigned short*)(buf->data.s + left->buf_idx*length_buf_row + |
|
|
|
|
workVarCount*scount + left->offset); |
|
|
|
|
(size_t)workVarCount*scount + left->offset); |
|
|
|
|
unsigned short* rdst = (unsigned short*)(buf->data.s + right->buf_idx*length_buf_row + |
|
|
|
|
workVarCount*scount + right->offset); |
|
|
|
|
(size_t)workVarCount*scount + right->offset); |
|
|
|
|
for (int i = 0; i < n; i++) |
|
|
|
|
{ |
|
|
|
|
unsigned short idx = (unsigned short)tempBuf[i]; |
|
|
|
@ -1239,9 +1239,9 @@ void CvCascadeBoostTree::split_node_data( CvDTreeNode* node ) |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int* ldst = buf->data.i + left->buf_idx*length_buf_row + |
|
|
|
|
workVarCount*scount + left->offset; |
|
|
|
|
(size_t)workVarCount*scount + left->offset; |
|
|
|
|
int* rdst = buf->data.i + right->buf_idx*length_buf_row + |
|
|
|
|
workVarCount*scount + right->offset; |
|
|
|
|
(size_t)workVarCount*scount + right->offset; |
|
|
|
|
for (int i = 0; i < n; i++) |
|
|
|
|
{ |
|
|
|
|
int idx = tempBuf[i]; |
|
|
|
@ -1410,7 +1410,7 @@ void CvCascadeBoost::update_weights( CvBoostTree* tree ) |
|
|
|
|
if (data->is_buf_16u) |
|
|
|
|
{ |
|
|
|
|
unsigned short* labels = (unsigned short*)(buf->data.s + data->data_root->buf_idx*length_buf_row + |
|
|
|
|
data->data_root->offset + (data->work_var_count-1)*data->sample_count); |
|
|
|
|
data->data_root->offset + (size_t)(data->work_var_count-1)*data->sample_count); |
|
|
|
|
for( int i = 0; i < n; i++ ) |
|
|
|
|
{ |
|
|
|
|
// save original categorical responses {0,1}, convert them to {-1,1}
|
|
|
|
@ -1428,7 +1428,7 @@ void CvCascadeBoost::update_weights( CvBoostTree* tree ) |
|
|
|
|
else |
|
|
|
|
{ |
|
|
|
|
int* labels = buf->data.i + data->data_root->buf_idx*length_buf_row + |
|
|
|
|
data->data_root->offset + (data->work_var_count-1)*data->sample_count; |
|
|
|
|
data->data_root->offset + (size_t)(data->work_var_count-1)*data->sample_count; |
|
|
|
|
|
|
|
|
|
for( int i = 0; i < n; i++ ) |
|
|
|
|
{ |
|
|
|
|