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replaced alloca() (a.k.a. cvStackAlloc) with AutoBuffer or vector() everywhere. cvStackAlloc() is still defined, but we do not need alloca() anymore to compile and run OpenCV (fixes #889 and may be some others)

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This commit is contained in:
Vadim Pisarevsky
2011-02-18 10:29:57 +00:00
parent 7b2ec0a1e6
commit 65a7f13af3
21 changed files with 286 additions and 263 deletions
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51
modules/ml/src/boost.cpp
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@@ -1592,32 +1592,22 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
CvMat* weak_responses, CvSlice slice,
bool raw_mode, bool return_sum ) const
{
float* buf = 0;
bool allocated = false;
float value = -FLT_MAX;
CV_FUNCNAME( "CvBoost::predict" );
__BEGIN__;
int i, weak_count, var_count;
CvMat sample, missing;
CvSeqReader reader;
double sum = 0;
int wstep = 0;
const int* vtype;
const int* cmap;
const int* cofs;
const float* sample_data;
if( !weak )
CV_ERROR( CV_StsError, "The boosted tree ensemble has not been trained yet" );
CV_Error( CV_StsError, "The boosted tree ensemble has not been trained yet" );
if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 ||
(_sample->cols != 1 && _sample->rows != 1) ||
(_sample->cols + _sample->rows - 1 != data->var_all && !raw_mode) ||
(active_vars && _sample->cols + _sample->rows - 1 != active_vars->cols && raw_mode) )
CV_ERROR( CV_StsBadArg,
CV_Error( CV_StsBadArg,
"the input sample must be 1d floating-point vector with the same "
"number of elements as the total number of variables or "
"as the number of variables used for training" );
@@ -1626,11 +1616,11 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
{
if( !CV_IS_MAT(_missing) || !CV_IS_MASK_ARR(_missing) ||
!CV_ARE_SIZES_EQ(_missing, _sample) )
CV_ERROR( CV_StsBadArg,
CV_Error( CV_StsBadArg,
"the missing data mask must be 8-bit vector of the same size as input sample" );
}
weak_count = cvSliceLength( slice, weak );
int i, weak_count = cvSliceLength( slice, weak );
if( weak_count >= weak->total )
{
weak_count = weak->total;
@@ -1643,21 +1633,20 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
CV_MAT_TYPE(weak_responses->type) != CV_32FC1 ||
(weak_responses->cols != 1 && weak_responses->rows != 1) ||
weak_responses->cols + weak_responses->rows - 1 != weak_count )
CV_ERROR( CV_StsBadArg,
CV_Error( CV_StsBadArg,
"The output matrix of weak classifier responses must be valid "
"floating-point vector of the same number of components as the length of input slice" );
wstep = CV_IS_MAT_CONT(weak_responses->type) ? 1 : weak_responses->step/sizeof(float);
}
var_count = active_vars->cols;
vtype = data->var_type->data.i;
cmap = data->cat_map->data.i;
cofs = data->cat_ofs->data.i;
int var_count = active_vars->cols;
const int* vtype = data->var_type->data.i;
const int* cmap = data->cat_map->data.i;
const int* cofs = data->cat_ofs->data.i;
// if need, preprocess the input vector
if( !raw_mode )
{
int bufsize;
int step, mstep = 0;
const float* src_sample;
const uchar* src_mask = 0;
@@ -1667,16 +1656,9 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
const int* vidx_abs = active_vars_abs->data.i;
bool have_mask = _missing != 0;
bufsize = var_count*(sizeof(float) + sizeof(uchar));
if( bufsize <= CV_MAX_LOCAL_SIZE )
buf = (float*)cvStackAlloc( bufsize );
else
{
CV_CALL( buf = (float*)cvAlloc( bufsize ));
allocated = true;
}
dst_sample = buf;
dst_mask = (uchar*)(buf + var_count);
cv::AutoBuffer<float> buf(var_count + (var_count+3)/4);
dst_sample = &buf[0];
dst_mask = (uchar*)&buf[var_count];
src_sample = _sample->data.fl;
step = CV_IS_MAT_CONT(_sample->type) ? 1 : _sample->step/sizeof(src_sample[0]);
@@ -1700,7 +1682,7 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
c = a;
int ival = cvRound(val);
if ( (ival != val) && (!m) )
CV_ERROR( CV_StsBadArg,
CV_Error( CV_StsBadArg,
"one of input categorical variable is not an integer" );
while( a < b )
@@ -1741,7 +1723,7 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
else
{
if( !CV_IS_MAT_CONT(_sample->type & (_missing ? _missing->type : -1)) )
CV_ERROR( CV_StsBadArg, "In raw mode the input vectors must be continuous" );
CV_Error( CV_StsBadArg, "In raw mode the input vectors must be continuous" );
}
cvStartReadSeq( weak, &reader );
@@ -1830,11 +1812,6 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
value = (float)cmap[cofs[vtype[data->var_count]] + cls_idx];
}
__END__;
if( allocated )
cvFree( &buf );
return value;
}