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Fix a segment fault issue in cascade classfier

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This commit is contained in:
greensea 2015-04-02 11:20:57 +08:00
parent d948b2a235
commit 7274e2ff1a
1 changed files with 28 additions and 28 deletions
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56
apps/traincascade/boost.cpp
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@ -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++ )
{