@ -45,7 +45,6 @@
# include <stdio.h>
# include "opencv2/core/internal.hpp"
# if CV_SSE2 || CV_SSE3
# if !CV_SSE4_1 && !CV_SSE4_2
# define _mm_blendv_pd(a, b, m) _mm_xor_pd(a, _mm_and_pd(_mm_xor_pd(b, a), m))
@ -53,13 +52,13 @@
# endif
# endif
# if CV_AVX
# define CV_HAAR_USE_AVX 1
# else
# if CV_SSE2 || CV_SSE3
# define CV_HAAR_USE_SSE 1
# endif
# endif
# if CV_AVX
# define CV_HAAR_USE_AVX 1
# else
# if CV_SSE2 || CV_SSE3
# define CV_HAAR_USE_SSE 1
# endif
# endif
/* these settings affect the quality of detection: change with care */
# define CV_ADJUST_FEATURES 1
@ -76,8 +75,7 @@ typedef struct CvHidHaarFeature
float weight ;
}
rect [ CV_HAAR_FEATURE_MAX ] ;
}
CvHidHaarFeature ;
} CvHidHaarFeature ;
typedef struct CvHidHaarTreeNode
@ -86,8 +84,7 @@ typedef struct CvHidHaarTreeNode
float threshold ;
int left ;
int right ;
}
CvHidHaarTreeNode ;
} CvHidHaarTreeNode ;
typedef struct CvHidHaarClassifier
@ -96,8 +93,7 @@ typedef struct CvHidHaarClassifier
//CvHaarFeature* orig_feature;
CvHidHaarTreeNode * node ;
float * alpha ;
}
CvHidHaarClassifier ;
} CvHidHaarClassifier ;
typedef struct CvHidHaarStageClassifier
@ -110,11 +106,10 @@ typedef struct CvHidHaarStageClassifier
struct CvHidHaarStageClassifier * next ;
struct CvHidHaarStageClassifier * child ;
struct CvHidHaarStageClassifier * parent ;
}
CvHidHaarStageClassifier ;
} CvHidHaarStageClassifier ;
struct CvHidHaarClassifierCascade
typedef struct CvHidHaarClassifierCascade
{
int count ;
int isStumpBased ;
@ -127,7 +122,7 @@ struct CvHidHaarClassifierCascade
sumtype * p0 , * p1 , * p2 , * p3 ;
void * * ipp_stages ;
} ;
} CvHidHaarClassifierCascade ;
const int icv_object_win_border = 1 ;
@ -634,21 +629,21 @@ cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* _cascade,
}
//AVX version icvEvalHidHaarClassifier. Process 8 CvHidHaarClassifiers per call. Check AVX support before invocation!!
// AVX version icvEvalHidHaarClassifier. Process 8 CvHidHaarClassifiers per call. Check AVX support before invocation!!
# ifdef CV_HAAR_USE_AVX
CV_INLINE
double icvEvalHidHaarClassifierAVX ( CvHidHaarClassifier * classifier ,
double variance_norm_factor , size_t p_offset )
{
int CV_DECL_ALIGNED ( 32 ) idxV [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
char flags [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
u charflags [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
CvHidHaarTreeNode * nodes [ 8 ] ;
double res = 0 ;
char exitConditionFlag = 0 ;
u charexitConditionFlag = 0 ;
for ( ; ; )
{
float CV_DECL_ALIGNED ( 32 ) tmp [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
nodes [ 0 ] = classifier - > node + idxV [ 0 ] ;
float CV_DECL_ALIGNED ( 32 ) tmp [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
nodes [ 0 ] = ( classifier + 0 ) - > node + idxV [ 0 ] ;
nodes [ 1 ] = ( classifier + 1 ) - > node + idxV [ 1 ] ;
nodes [ 2 ] = ( classifier + 2 ) - > node + idxV [ 2 ] ;
nodes [ 3 ] = ( classifier + 3 ) - > node + idxV [ 3 ] ;
@ -658,46 +653,79 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
nodes [ 7 ] = ( classifier + 7 ) - > node + idxV [ 7 ] ;
__m256 t = _mm256_set1_ps ( variance_norm_factor ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold , nodes [ 6 ] - > threshold , nodes [ 5 ] - > threshold , nodes [ 4 ] - > threshold , nodes [ 3 ] - > threshold , nodes [ 2 ] - > threshold , nodes [ 1 ] - > threshold , nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] ,
p_offset ) , calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight , nodes [ 6 ] - > feature . rect [ 0 ] . weight , nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight , nodes [ 3 ] - > feature . rect [ 0 ] . weight , nodes [ 2 ] - > feature . rect [ 0 ] . weight , nodes [ 1 ] - > feature . rect [ 0 ] . weight , nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold ,
nodes [ 6 ] - > threshold ,
nodes [ 5 ] - > threshold ,
nodes [ 4 ] - > threshold ,
nodes [ 3 ] - > threshold ,
nodes [ 2 ] - > threshold ,
nodes [ 1 ] - > threshold ,
nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight ,
nodes [ 6 ] - > feature . rect [ 0 ] . weight ,
nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight ,
nodes [ 3 ] - > feature . rect [ 0 ] . weight ,
nodes [ 2 ] - > feature . rect [ 0 ] . weight ,
nodes [ 1 ] - > feature . rect [ 0 ] . weight ,
nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight , nodes [ 6 ] - > feature . rect [ 1 ] . weight , nodes [ 5 ] - > feature . rect [ 1 ] . weight , nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight , nodes [ 2 ] - > feature . rect [ 1 ] . weight , nodes [ 1 ] - > feature . rect [ 1 ] . weight , nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight ,
nodes [ 6 ] - > feature . rect [ 1 ] . weight ,
nodes [ 5 ] - > feature . rect [ 1 ] . weight ,
nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight ,
nodes [ 2 ] - > feature . rect [ 1 ] . weight ,
nodes [ 1 ] - > feature . rect [ 1 ] . weight ,
nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
if ( nodes [ 0 ] - > feature . rect [ 2 ] . p0 )
tmp [ 0 ] = calc_sum ( nodes [ 0 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 0 ] - > feature . rect [ 2 ] . weight ;
tmp [ 0 ] = calc_sum ( nodes [ 0 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 0 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 1 ] - > feature . rect [ 2 ] . p0 )
tmp [ 1 ] = calc_sum ( nodes [ 1 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 1 ] - > feature . rect [ 2 ] . weight ;
tmp [ 1 ] = calc_sum ( nodes [ 1 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 1 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 2 ] - > feature . rect [ 2 ] . p0 )
tmp [ 2 ] = calc_sum ( nodes [ 2 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 2 ] - > feature . rect [ 2 ] . weight ;
tmp [ 2 ] = calc_sum ( nodes [ 2 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 2 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 3 ] - > feature . rect [ 2 ] . p0 )
tmp [ 3 ] = calc_sum ( nodes [ 3 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 3 ] - > feature . rect [ 2 ] . weight ;
tmp [ 3 ] = calc_sum ( nodes [ 3 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 3 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 4 ] - > feature . rect [ 2 ] . p0 )
tmp [ 4 ] = calc_sum ( nodes [ 4 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 4 ] - > feature . rect [ 2 ] . weight ;
tmp [ 4 ] = calc_sum ( nodes [ 4 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 4 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 5 ] - > feature . rect [ 2 ] . p0 )
tmp [ 5 ] = calc_sum ( nodes [ 5 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 5 ] - > feature . rect [ 2 ] . weight ;
tmp [ 5 ] = calc_sum ( nodes [ 5 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 5 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 6 ] - > feature . rect [ 2 ] . p0 )
tmp [ 6 ] = calc_sum ( nodes [ 6 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 6 ] - > feature . rect [ 2 ] . weight ;
tmp [ 6 ] = calc_sum ( nodes [ 6 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 6 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 7 ] - > feature . rect [ 2 ] . p0 )
tmp [ 7 ] = calc_sum ( nodes [ 7 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 7 ] - > feature . rect [ 2 ] . weight ;
tmp [ 7 ] = calc_sum ( nodes [ 7 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 7 ] - > feature . rect [ 2 ] . weight ;
sum = _mm256_add_ps ( sum , _mm256_load_ps ( tmp ) ) ;
__m256 left = _mm256_set_ps ( nodes [ 7 ] - > left , nodes [ 6 ] - > left , nodes [ 5 ] - > left , nodes [ 4 ] - > left , nodes [ 3 ] - > left , nodes [ 2 ] - > left , nodes [ 1 ] - > left , nodes [ 0 ] - > left ) ;
__m256 left = _mm256_set_ps ( nodes [ 7 ] - > left , nodes [ 6 ] - > left , nodes [ 5 ] - > left , nodes [ 4 ] - > left , nodes [ 3 ] - > left , nodes [ 2 ] - > left , nodes [ 1 ] - > left , nodes [ 0 ] - > left ) ;
__m256 right = _mm256_set_ps ( nodes [ 7 ] - > right , nodes [ 6 ] - > right , nodes [ 5 ] - > right , nodes [ 4 ] - > right , nodes [ 3 ] - > right , nodes [ 2 ] - > right , nodes [ 1 ] - > right , nodes [ 0 ] - > right ) ;
_mm256_store_si256 ( ( __m256i * ) idxV , _mm256_cvttps_epi32 ( _mm256_blendv_ps ( right , left , _mm256_cmp_ps ( sum , t , _CMP_LT_OQ ) ) ) ) ;
_mm256_store_si256 ( ( __m256i * ) idxV , _mm256_cvttps_epi32 ( _mm256_blendv_ps ( right , left , _mm256_cmp_ps ( sum , t , _CMP_LT_OQ ) ) ) ) ;
for ( int i = 0 ; i < 8 ; i + + )
{
@ -706,17 +734,17 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
if ( ! flags [ i ] )
{
exitConditionFlag + + ;
flags [ i ] = 1 ;
res + = ( ( classifier + i ) - > alpha [ - idxV [ i ] ] ) ;
flags [ i ] = 1 ;
res + = ( classifier + i ) - > alpha [ - idxV [ i ] ] ;
}
idxV [ i ] = 0 ;
}
}
if ( exitConditionFlag = = 8 )
if ( exitConditionFlag = = 8 )
return res ;
}
}
# endif
# endif //CV_HAAR_USE_AVX
CV_INLINE
double icvEvalHidHaarClassifier ( CvHidHaarClassifier * classifier ,
@ -778,18 +806,16 @@ static int
cvRunHaarClassifierCascadeSum ( const CvHaarClassifierCascade * _cascade ,
CvPoint pt , double & stage_sum , int start_stage )
{
# ifdef CV_HAAR_USE_AVX
bool haveAVX = false ;
if ( cv : : checkHardwareSupport ( CV_CPU_AVX ) )
if ( __xgetbv ( ) & 0x6 ) // Check if the OS will save the YMM registers
{
haveAVX = true ;
}
# else
# ifdef CV_HAAR_USE_SSE
bool haveSSE2 = cv : : checkHardwareSupport ( CV_CPU_SSE2 ) ;
# endif
# endif
# ifdef CV_HAAR_USE_AVX
bool haveAVX = false ;
if ( cv : : checkHardwareSupport ( CV_CPU_AVX ) )
if ( __xgetbv ( ) & 0x6 ) // Check if the OS will save the YMM registers
haveAVX = true ;
# else
# ifdef CV_HAAR_USE_SSE
bool haveSSE2 = cv : : checkHardwareSupport ( CV_CPU_SSE2 ) ;
# endif
# endif
int p_offset , pq_offset ;
int i , j ;
@ -828,19 +854,20 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
while ( ptr )
{
stage_sum = 0.0 ;
j = 0 ;
# ifdef CV_HAAR_USE_AVX
# ifdef CV_HAAR_USE_AVX
if ( haveAVX )
{
for ( ; j < cascade - > stage_classifier [ i ] . count - 8 ; j + = 8 )
for ( ; j < = ptr - > count - 8 ; j + = 8 )
{
stage_sum + = icvEvalHidHaarClassifierAVX (
cascade - > stage_ classifier[ i ] . classifier + j ,
ptr - > classifier + j ,
variance_norm_factor , p_offset ) ;
}
}
# endif
for ( j = 0 ; j < ptr - > count ; j + + )
# endif
for ( ; j < ptr - > count ; j + + )
{
stage_sum + = icvEvalHidHaarClassifier ( ptr - > classifier + j , variance_norm_factor , p_offset ) ;
}
@ -860,283 +887,369 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
}
else if ( cascade - > isStumpBased )
{
# ifdef CV_HAAR_USE_AVX
if ( haveAVX )
# ifdef CV_HAAR_USE_AVX
if ( haveAVX )
{
CvHidHaarClassifier * classifiers [ 8 ] ;
CvHidHaarTreeNode * nodes [ 8 ] ;
for ( i = start_stage ; i < cascade - > count ; i + + )
{
CvHidHaarClassifier * classifiers [ 8 ] ;
CvHidHaarTreeNode * nodes [ 8 ] ;
for ( i = start_stage ; i < cascade - > count ; i + + )
stage_sum = 0.0 ;
j = 0 ;
float CV_DECL_ALIGNED ( 32 ) buf [ 8 ] ;
if ( cascade - > stage_classifier [ i ] . two_rects )
{
stage_sum = 0.0 ;
j = 0 ;
float CV_DECL_ALIGNED ( 32 ) buf [ 8 ] ;
if ( cascade - > stage_classifier [ i ] . two_rects )
for ( ; j < = cascade - > stage_classifier [ i ] . count - 8 ; j + = 8 )
{
for ( ; j < = cascade - > stage_classifier [ i ] . count - 8 ; j + = 8 )
{
//__m256 stage_sumPart = _mm256_setzero_ps();
classifiers [ 0 ] = cascade - > stage_classifier [ i ] . classifier + j ;
nodes [ 0 ] = classifiers [ 0 ] - > node ;
classifiers [ 1 ] = cascade - > stage_classifier [ i ] . classifier + j + 1 ;
nodes [ 1 ] = classifiers [ 1 ] - > node ;
classifiers [ 2 ] = cascade - > stage_classifier [ i ] . classifier + j + 2 ;
nodes [ 2 ] = classifiers [ 2 ] - > node ;
classifiers [ 3 ] = cascade - > stage_classifier [ i ] . classifier + j + 3 ;
nodes [ 3 ] = classifiers [ 3 ] - > node ;
classifiers [ 4 ] = cascade - > stage_classifier [ i ] . classifier + j + 4 ;
nodes [ 4 ] = classifiers [ 4 ] - > node ;
classifiers [ 5 ] = cascade - > stage_classifier [ i ] . classifier + j + 5 ;
nodes [ 5 ] = classifiers [ 5 ] - > node ;
classifiers [ 6 ] = cascade - > stage_classifier [ i ] . classifier + j + 6 ;
nodes [ 6 ] = classifiers [ 6 ] - > node ;
classifiers [ 7 ] = cascade - > stage_classifier [ i ] . classifier + j + 7 ;
nodes [ 7 ] = classifiers [ 7 ] - > node ;
__m256 t = _mm256_set1_ps ( variance_norm_factor ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold , nodes [ 6 ] - > threshold , nodes [ 5 ] - > threshold , nodes [ 4 ] - > threshold , nodes [ 3 ] - > threshold , nodes [ 2 ] - > threshold , nodes [ 1 ] - > threshold , nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] ,
p_offset ) , calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight , nodes [ 6 ] - > feature . rect [ 0 ] . weight , nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight , nodes [ 3 ] - > feature . rect [ 0 ] . weight , nodes [ 2 ] - > feature . rect [ 0 ] . weight , nodes [ 1 ] - > feature . rect [ 0 ] . weight , nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight , nodes [ 6 ] - > feature . rect [ 1 ] . weight , nodes [ 5 ] - > feature . rect [ 1 ] . weight , nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight , nodes [ 2 ] - > feature . rect [ 1 ] . weight , nodes [ 1 ] - > feature . rect [ 1 ] . weight , nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
__m256 alpha0 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 0 ] , classifiers [ 6 ] - > alpha [ 0 ] , classifiers [ 5 ] - > alpha [ 0 ] , classifiers [ 4 ] - > alpha [ 0 ] , classifiers [ 3 ] - > alpha [ 0 ] ,
classifiers [ 2 ] - > alpha [ 0 ] , classifiers [ 1 ] - > alpha [ 0 ] , classifiers [ 0 ] - > alpha [ 0 ] ) ;
__m256 alpha1 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 1 ] , classifiers [ 6 ] - > alpha [ 1 ] , classifiers [ 5 ] - > alpha [ 1 ] , classifiers [ 4 ] - > alpha [ 1 ] , classifiers [ 3 ] - > alpha [ 1 ] ,
classifiers [ 2 ] - > alpha [ 1 ] , classifiers [ 1 ] - > alpha [ 1 ] , classifiers [ 0 ] - > alpha [ 1 ] ) ;
_mm256_store_ps ( buf , _mm256_blendv_ps ( alpha0 , alpha1 , _mm256_cmp_ps ( t , sum , _CMP_LE_OQ ) ) ) ;
stage_sum + = ( buf [ 0 ] + buf [ 1 ] + buf [ 2 ] + buf [ 3 ] + buf [ 4 ] + buf [ 5 ] + buf [ 6 ] + buf [ 7 ] ) ;
}
classifiers [ 0 ] = cascade - > stage_classifier [ i ] . classifier + j ;
nodes [ 0 ] = classifiers [ 0 ] - > node ;
classifiers [ 1 ] = cascade - > stage_classifier [ i ] . classifier + j + 1 ;
nodes [ 1 ] = classifiers [ 1 ] - > node ;
classifiers [ 2 ] = cascade - > stage_classifier [ i ] . classifier + j + 2 ;
nodes [ 2 ] = classifiers [ 2 ] - > node ;
classifiers [ 3 ] = cascade - > stage_classifier [ i ] . classifier + j + 3 ;
nodes [ 3 ] = classifiers [ 3 ] - > node ;
classifiers [ 4 ] = cascade - > stage_classifier [ i ] . classifier + j + 4 ;
nodes [ 4 ] = classifiers [ 4 ] - > node ;
classifiers [ 5 ] = cascade - > stage_classifier [ i ] . classifier + j + 5 ;
nodes [ 5 ] = classifiers [ 5 ] - > node ;
classifiers [ 6 ] = cascade - > stage_classifier [ i ] . classifier + j + 6 ;
nodes [ 6 ] = classifiers [ 6 ] - > node ;
classifiers [ 7 ] = cascade - > stage_classifier [ i ] . classifier + j + 7 ;
nodes [ 7 ] = classifiers [ 7 ] - > node ;
__m256 t = _mm256_set1_ps ( variance_norm_factor ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold ,
nodes [ 6 ] - > threshold ,
nodes [ 5 ] - > threshold ,
nodes [ 4 ] - > threshold ,
nodes [ 3 ] - > threshold ,
nodes [ 2 ] - > threshold ,
nodes [ 1 ] - > threshold ,
nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight ,
nodes [ 6 ] - > feature . rect [ 0 ] . weight ,
nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight ,
nodes [ 3 ] - > feature . rect [ 0 ] . weight ,
nodes [ 2 ] - > feature . rect [ 0 ] . weight ,
nodes [ 1 ] - > feature . rect [ 0 ] . weight ,
nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight ,
nodes [ 6 ] - > feature . rect [ 1 ] . weight ,
nodes [ 5 ] - > feature . rect [ 1 ] . weight ,
nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight ,
nodes [ 2 ] - > feature . rect [ 1 ] . weight ,
nodes [ 1 ] - > feature . rect [ 1 ] . weight ,
nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
__m256 alpha0 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 0 ] ,
classifiers [ 6 ] - > alpha [ 0 ] ,
classifiers [ 5 ] - > alpha [ 0 ] ,
classifiers [ 4 ] - > alpha [ 0 ] ,
classifiers [ 3 ] - > alpha [ 0 ] ,
classifiers [ 2 ] - > alpha [ 0 ] ,
classifiers [ 1 ] - > alpha [ 0 ] ,
classifiers [ 0 ] - > alpha [ 0 ] ) ;
__m256 alpha1 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 1 ] ,
classifiers [ 6 ] - > alpha [ 1 ] ,
classifiers [ 5 ] - > alpha [ 1 ] ,
classifiers [ 4 ] - > alpha [ 1 ] ,
classifiers [ 3 ] - > alpha [ 1 ] ,
classifiers [ 2 ] - > alpha [ 1 ] ,
classifiers [ 1 ] - > alpha [ 1 ] ,
classifiers [ 0 ] - > alpha [ 1 ] ) ;
_mm256_store_ps ( buf , _mm256_blendv_ps ( alpha0 , alpha1 , _mm256_cmp_ps ( t , sum , _CMP_LE_OQ ) ) ) ;
stage_sum + = ( buf [ 0 ] + buf [ 1 ] + buf [ 2 ] + buf [ 3 ] + buf [ 4 ] + buf [ 5 ] + buf [ 6 ] + buf [ 7 ] ) ;
}
for ( ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
for ( ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
else
}
else
{
for ( ; j < = ( cascade - > stage_classifier [ i ] . count ) - 8 ; j + = 8 )
{
for ( ; j < = ( cascade - > stage_classifier [ i ] . count ) - 8 ; j + = 8 )
{
float CV_DECL_ALIGNED ( 32 ) tmp [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
classifiers [ 0 ] = cascade - > stage_classifier [ i ] . classifier + j ;
nodes [ 0 ] = classifiers [ 0 ] - > node ;
classifiers [ 1 ] = cascade - > stage_classifier [ i ] . classifier + j + 1 ;
nodes [ 1 ] = classifiers [ 1 ] - > node ;
classifiers [ 2 ] = cascade - > stage_classifier [ i ] . classifier + j + 2 ;
nodes [ 2 ] = classifiers [ 2 ] - > node ;
classifiers [ 3 ] = cascade - > stage_classifier [ i ] . classifier + j + 3 ;
nodes [ 3 ] = classifiers [ 3 ] - > node ;
classifiers [ 4 ] = cascade - > stage_classifier [ i ] . classifier + j + 4 ;
nodes [ 4 ] = classifiers [ 4 ] - > node ;
classifiers [ 5 ] = cascade - > stage_classifier [ i ] . classifier + j + 5 ;
nodes [ 5 ] = classifiers [ 5 ] - > node ;
classifiers [ 6 ] = cascade - > stage_classifier [ i ] . classifier + j + 6 ;
nodes [ 6 ] = classifiers [ 6 ] - > node ;
classifiers [ 7 ] = cascade - > stage_classifier [ i ] . classifier + j + 7 ;
nodes [ 7 ] = classifiers [ 7 ] - > node ;
__m256 t = _mm256_set1_ps ( variance_norm_factor ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold , nodes [ 6 ] - > threshold , nodes [ 5 ] - > threshold , nodes [ 4 ] - > threshold , nodes [ 3 ] - > threshold , nodes [ 2 ] - > threshold , nodes [ 1 ] - > threshold , nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] ,
p_offset ) , calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight , nodes [ 6 ] - > feature . rect [ 0 ] . weight , nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight , nodes [ 3 ] - > feature . rect [ 0 ] . weight , nodes [ 2 ] - > feature . rect [ 0 ] . weight , nodes [ 1 ] - > feature . rect [ 0 ] . weight , nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) , calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight , nodes [ 6 ] - > feature . rect [ 1 ] . weight , nodes [ 5 ] - > feature . rect [ 1 ] . weight , nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight , nodes [ 2 ] - > feature . rect [ 1 ] . weight , nodes [ 1 ] - > feature . rect [ 1 ] . weight , nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
if ( nodes [ 0 ] - > feature . rect [ 2 ] . p0 )
tmp [ 0 ] = calc_sum ( nodes [ 0 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 0 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 1 ] - > feature . rect [ 2 ] . p0 )
tmp [ 1 ] = calc_sum ( nodes [ 1 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 1 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 2 ] - > feature . rect [ 2 ] . p0 )
tmp [ 2 ] = calc_sum ( nodes [ 2 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 2 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 3 ] - > feature . rect [ 2 ] . p0 )
tmp [ 3 ] = calc_sum ( nodes [ 3 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 3 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 4 ] - > feature . rect [ 2 ] . p0 )
tmp [ 4 ] = calc_sum ( nodes [ 4 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 4 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 5 ] - > feature . rect [ 2 ] . p0 )
tmp [ 5 ] = calc_sum ( nodes [ 5 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 5 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 6 ] - > feature . rect [ 2 ] . p0 )
tmp [ 6 ] = calc_sum ( nodes [ 6 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 6 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 7 ] - > feature . rect [ 2 ] . p0 )
tmp [ 7 ] = calc_sum ( nodes [ 7 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 7 ] - > feature . rect [ 2 ] . weight ;
sum = _mm256_add_ps ( sum , _mm256_load_ps ( tmp ) ) ;
__m256 alpha0 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 0 ] , classifiers [ 6 ] - > alpha [ 0 ] , classifiers [ 5 ] - > alpha [ 0 ] , classifiers [ 4 ] - > alpha [ 0 ] , classifiers [ 3 ] - > alpha [ 0 ] ,
classifiers [ 2 ] - > alpha [ 0 ] , classifiers [ 1 ] - > alpha [ 0 ] , classifiers [ 0 ] - > alpha [ 0 ] ) ;
__m256 alpha1 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 1 ] , classifiers [ 6 ] - > alpha [ 1 ] , classifiers [ 5 ] - > alpha [ 1 ] , classifiers [ 4 ] - > alpha [ 1 ] , classifiers [ 3 ] - > alpha [ 1 ] ,
classifiers [ 2 ] - > alpha [ 1 ] , classifiers [ 1 ] - > alpha [ 1 ] , classifiers [ 0 ] - > alpha [ 1 ] ) ;
__m256 outBuf = _mm256_blendv_ps ( alpha0 , alpha1 , _mm256_cmp_ps ( t , sum , _CMP_LE_OQ ) ) ;
outBuf = _mm256_hadd_ps ( outBuf , outBuf ) ;
outBuf = _mm256_hadd_ps ( outBuf , outBuf ) ;
_mm256_store_ps ( buf , outBuf ) ;
stage_sum + = ( buf [ 0 ] + buf [ 4 ] ) ; //(buf[0]+buf[1]+buf[2]+buf[3]+buf[4]+buf[5]+buf[6]+buf[7]);
}
float CV_DECL_ALIGNED ( 32 ) tmp [ 8 ] = { 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 } ;
classifiers [ 0 ] = cascade - > stage_classifier [ i ] . classifier + j ;
nodes [ 0 ] = classifiers [ 0 ] - > node ;
classifiers [ 1 ] = cascade - > stage_classifier [ i ] . classifier + j + 1 ;
nodes [ 1 ] = classifiers [ 1 ] - > node ;
classifiers [ 2 ] = cascade - > stage_classifier [ i ] . classifier + j + 2 ;
nodes [ 2 ] = classifiers [ 2 ] - > node ;
classifiers [ 3 ] = cascade - > stage_classifier [ i ] . classifier + j + 3 ;
nodes [ 3 ] = classifiers [ 3 ] - > node ;
classifiers [ 4 ] = cascade - > stage_classifier [ i ] . classifier + j + 4 ;
nodes [ 4 ] = classifiers [ 4 ] - > node ;
classifiers [ 5 ] = cascade - > stage_classifier [ i ] . classifier + j + 5 ;
nodes [ 5 ] = classifiers [ 5 ] - > node ;
classifiers [ 6 ] = cascade - > stage_classifier [ i ] . classifier + j + 6 ;
nodes [ 6 ] = classifiers [ 6 ] - > node ;
classifiers [ 7 ] = cascade - > stage_classifier [ i ] . classifier + j + 7 ;
nodes [ 7 ] = classifiers [ 7 ] - > node ;
__m256 t = _mm256_set1_ps ( variance_norm_factor ) ;
t = _mm256_mul_ps ( t , _mm256_set_ps ( nodes [ 7 ] - > threshold ,
nodes [ 6 ] - > threshold ,
nodes [ 5 ] - > threshold ,
nodes [ 4 ] - > threshold ,
nodes [ 3 ] - > threshold ,
nodes [ 2 ] - > threshold ,
nodes [ 1 ] - > threshold ,
nodes [ 0 ] - > threshold ) ) ;
__m256 offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 0 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 0 ] , p_offset ) ) ;
__m256 weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 0 ] . weight ,
nodes [ 6 ] - > feature . rect [ 0 ] . weight ,
nodes [ 5 ] - > feature . rect [ 0 ] . weight ,
nodes [ 4 ] - > feature . rect [ 0 ] . weight ,
nodes [ 3 ] - > feature . rect [ 0 ] . weight ,
nodes [ 2 ] - > feature . rect [ 0 ] . weight ,
nodes [ 1 ] - > feature . rect [ 0 ] . weight ,
nodes [ 0 ] - > feature . rect [ 0 ] . weight ) ;
__m256 sum = _mm256_mul_ps ( offset , weight ) ;
offset = _mm256_set_ps ( calc_sum ( nodes [ 7 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 6 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 5 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 4 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 3 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 2 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 1 ] - > feature . rect [ 1 ] , p_offset ) ,
calc_sum ( nodes [ 0 ] - > feature . rect [ 1 ] , p_offset ) ) ;
weight = _mm256_set_ps ( nodes [ 7 ] - > feature . rect [ 1 ] . weight ,
nodes [ 6 ] - > feature . rect [ 1 ] . weight ,
nodes [ 5 ] - > feature . rect [ 1 ] . weight ,
nodes [ 4 ] - > feature . rect [ 1 ] . weight ,
nodes [ 3 ] - > feature . rect [ 1 ] . weight ,
nodes [ 2 ] - > feature . rect [ 1 ] . weight ,
nodes [ 1 ] - > feature . rect [ 1 ] . weight ,
nodes [ 0 ] - > feature . rect [ 1 ] . weight ) ;
sum = _mm256_add_ps ( sum , _mm256_mul_ps ( offset , weight ) ) ;
if ( nodes [ 0 ] - > feature . rect [ 2 ] . p0 )
tmp [ 0 ] = calc_sum ( nodes [ 0 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 0 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 1 ] - > feature . rect [ 2 ] . p0 )
tmp [ 1 ] = calc_sum ( nodes [ 1 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 1 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 2 ] - > feature . rect [ 2 ] . p0 )
tmp [ 2 ] = calc_sum ( nodes [ 2 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 2 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 3 ] - > feature . rect [ 2 ] . p0 )
tmp [ 3 ] = calc_sum ( nodes [ 3 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 3 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 4 ] - > feature . rect [ 2 ] . p0 )
tmp [ 4 ] = calc_sum ( nodes [ 4 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 4 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 5 ] - > feature . rect [ 2 ] . p0 )
tmp [ 5 ] = calc_sum ( nodes [ 5 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 5 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 6 ] - > feature . rect [ 2 ] . p0 )
tmp [ 6 ] = calc_sum ( nodes [ 6 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 6 ] - > feature . rect [ 2 ] . weight ;
if ( nodes [ 7 ] - > feature . rect [ 2 ] . p0 )
tmp [ 7 ] = calc_sum ( nodes [ 7 ] - > feature . rect [ 2 ] , p_offset ) * nodes [ 7 ] - > feature . rect [ 2 ] . weight ;
sum = _mm256_add_ps ( sum , _mm256_load_ps ( tmp ) ) ;
__m256 alpha0 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 0 ] ,
classifiers [ 6 ] - > alpha [ 0 ] ,
classifiers [ 5 ] - > alpha [ 0 ] ,
classifiers [ 4 ] - > alpha [ 0 ] ,
classifiers [ 3 ] - > alpha [ 0 ] ,
classifiers [ 2 ] - > alpha [ 0 ] ,
classifiers [ 1 ] - > alpha [ 0 ] ,
classifiers [ 0 ] - > alpha [ 0 ] ) ;
__m256 alpha1 = _mm256_set_ps ( classifiers [ 7 ] - > alpha [ 1 ] ,
classifiers [ 6 ] - > alpha [ 1 ] ,
classifiers [ 5 ] - > alpha [ 1 ] ,
classifiers [ 4 ] - > alpha [ 1 ] ,
classifiers [ 3 ] - > alpha [ 1 ] ,
classifiers [ 2 ] - > alpha [ 1 ] ,
classifiers [ 1 ] - > alpha [ 1 ] ,
classifiers [ 0 ] - > alpha [ 1 ] ) ;
__m256 outBuf = _mm256_blendv_ps ( alpha0 , alpha1 , _mm256_cmp_ps ( t , sum , _CMP_LE_OQ ) ) ;
outBuf = _mm256_hadd_ps ( outBuf , outBuf ) ;
outBuf = _mm256_hadd_ps ( outBuf , outBuf ) ;
_mm256_store_ps ( buf , outBuf ) ;
stage_sum + = ( buf [ 0 ] + buf [ 4 ] ) ;
}
for ( ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
for ( ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
if ( stage_sum < cascade - > stage_classifier [ i ] . threshold )
return - i ;
}
if ( stage_sum < cascade - > stage_classifier [ i ] . threshold )
return - i ;
}
else
# endif
# if defined CV_HAAR_USE_SSE && CV_HAAR_USE_SSE && (!defined CV_HAAR_USE_AVX || !CV_HAAR_USE_AVX) //old SSE optimization
if ( haveSSE2 )
}
else
# elif defined CV_HAAR_USE_SSE //old SSE optimization
if ( haveSSE2 )
{
for ( i = start_stage ; i < cascade - > count ; i + + )
{
for ( i = start_stage ; i < cascade - > count ; i + + )
__m128d vstage_sum = _mm_setzero_pd ( ) ;
if ( cascade - > stage_classifier [ i ] . two_rects )
{
__m128d vstage_sum = _mm_setzero_pd ( ) ;
if ( cascade - > stage_classifier [ i ] . two_rects )
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
// ayasin - NHM perf optim. Avoid use of costly flaky jcc
__m128d t = _mm_set_sd ( node - > threshold * variance_norm_factor ) ;
__m128d a = _mm_set_sd ( classifier - > alpha [ 0 ] ) ;
__m128d b = _mm_set_sd ( classifier - > alpha [ 1 ] ) ;
__m128d sum = _mm_set_sd ( calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight +
calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ) ;
t = _mm_cmpgt_sd ( t , sum ) ;
vstage_sum = _mm_add_sd ( vstage_sum , _mm_blendv_pd ( b , a , t ) ) ;
}
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
// ayasin - NHM perf optim. Avoid use of costly flaky jcc
__m128d t = _mm_set_sd ( node - > threshold * variance_norm_factor ) ;
__m128d a = _mm_set_sd ( classifier - > alpha [ 0 ] ) ;
__m128d b = _mm_set_sd ( classifier - > alpha [ 1 ] ) ;
__m128d sum = _mm_set_sd ( calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight +
calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ) ;
t = _mm_cmpgt_sd ( t , sum ) ;
vstage_sum = _mm_add_sd ( vstage_sum , _mm_blendv_pd ( b , a , t ) ) ;
}
else
}
else
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
// ayasin - NHM perf optim. Avoid use of costly flaky jcc
__m128d t = _mm_set_sd ( node - > threshold * variance_norm_factor ) ;
__m128d a = _mm_set_sd ( classifier - > alpha [ 0 ] ) ;
__m128d b = _mm_set_sd ( classifier - > alpha [ 1 ] ) ;
double _sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
_sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
_sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
__m128d sum = _mm_set_sd ( _sum ) ;
t = _mm_cmpgt_sd ( t , sum ) ;
vstage_sum = _mm_add_sd ( vstage_sum , _mm_blendv_pd ( b , a , t ) ) ;
}
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
// ayasin - NHM perf optim. Avoid use of costly flaky jcc
__m128d t = _mm_set_sd ( node - > threshold * variance_norm_factor ) ;
__m128d a = _mm_set_sd ( classifier - > alpha [ 0 ] ) ;
__m128d b = _mm_set_sd ( classifier - > alpha [ 1 ] ) ;
double _sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
_sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
_sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
__m128d sum = _mm_set_sd ( _sum ) ;
t = _mm_cmpgt_sd ( t , sum ) ;
vstage_sum = _mm_add_sd ( vstage_sum , _mm_blendv_pd ( b , a , t ) ) ;
}
__m128d i_threshold = _mm_set1_pd ( cascade - > stage_classifier [ i ] . threshold ) ;
if ( _mm_comilt_sd ( vstage_sum , i_threshold ) )
return - i ;
}
__m128d i_threshold = _mm_set1_pd ( cascade - > stage_classifier [ i ] . threshold ) ;
if ( _mm_comilt_sd ( vstage_sum , i_threshold ) )
return - i ;
}
else
# endif
}
else
# endif // AVX or SSE
{
for ( i = start_stage ; i < cascade - > count ; i + + )
{
for ( i = start_stage ; i < cascade - > count ; i + + )
stage_sum = 0.0 ;
if ( cascade - > stage_classifier [ i ] . two_rects )
{
stage_sum = 0.0 ;
if ( cascade - > stage_classifier [ i ] . two_rects )
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
else
}
else
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
for ( j = 0 ; j < cascade - > stage_classifier [ i ] . count ; j + + )
{
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
CvHidHaarClassifier * classifier = cascade - > stage_classifier [ i ] . classifier + j ;
CvHidHaarTreeNode * node = classifier - > node ;
double t = node - > threshold * variance_norm_factor ;
double sum = calc_sum ( node - > feature . rect [ 0 ] , p_offset ) * node - > feature . rect [ 0 ] . weight ;
sum + = calc_sum ( node - > feature . rect [ 1 ] , p_offset ) * node - > feature . rect [ 1 ] . weight ;
if ( node - > feature . rect [ 2 ] . p0 )
sum + = calc_sum ( node - > feature . rect [ 2 ] , p_offset ) * node - > feature . rect [ 2 ] . weight ;
stage_sum + = classifier - > alpha [ sum > = t ] ;
}
if ( stage_sum < cascade - > stage_classifier [ i ] . threshold )
return - i ;
}
if ( stage_sum < cascade - > stage_classifier [ i ] . threshold )
return - i ;
}
}
}
else
{
for ( i = start_stage ; i < cascade - > count ; i + + )
{
stage_sum = 0.0 ;
int k = 0 ;
# ifdef CV_HAAR_USE_AVX
# ifdef CV_HAAR_USE_AVX
if ( haveAVX )
{
for ( ; k < cascade - > stage_classifier [ i ] . count - 8 ; k + = 8 )
for ( ; k < cascade - > stage_classifier [ i ] . count - 8 ; k + = 8 )
{
stage_sum + = icvEvalHidHaarClassifierAVX (
cascade - > stage_classifier [ i ] . classifier + k ,
cascade - > stage_classifier [ i ] . classifier + k ,
variance_norm_factor , p_offset ) ;
}
}
# endif
for ( ; k < cascade - > stage_classifier [ i ] . count ; k + + )
{
# endif
for ( ; k < cascade - > stage_classifier [ i ] . count ; k + + )
{
stage_sum + = icvEvalHidHaarClassifier (
cascade - > stage_classifier [ i ] . classifier + k ,
variance_norm_factor , p_offset ) ;
}
stage_sum + = icvEvalHidHaarClassifier (
cascade - > stage_classifier [ i ] . classifier + k ,
variance_norm_factor , p_offset ) ;
}
if ( stage_sum < cascade - > stage_classifier [ i ] . threshold )
return - i ;
}
}
//_mm256_zeroupper();
return 1 ;
}
@ -1186,7 +1299,7 @@ struct HaarDetectObjects_ScaleImage_Invoker
Size ssz ( sum1 . cols - 1 - winSize0 . width , y2 - y1 ) ;
int x , y , ystep = factor > 2 ? 1 : 2 ;
# ifdef HAVE_IPP
# ifdef HAVE_IPP
if ( cascade - > hid_cascade - > ipp_stages )
{
IppiRect iequRect = { equRect . x , equRect . y , equRect . width , equRect . height } ;
@ -1241,7 +1354,7 @@ struct HaarDetectObjects_ScaleImage_Invoker
}
}
else
# endif
# endif // IPP
for ( y = y1 ; y < y2 ; y + = ystep )
for ( x = 0 ; x < ssz . width ; x + = ystep )
{
@ -1880,18 +1993,18 @@ cvReleaseHaarClassifierCascade( CvHaarClassifierCascade** _cascade )
# define ICV_HAAR_SIZE_NAME "size"
# define ICV_HAAR_STAGES_NAME "stages"
# define ICV_HAAR_TREES_NAME "trees"
# define ICV_HAAR_FEATURE_NAME "feature"
# define ICV_HAAR_RECTS_NAME "rects"
# define ICV_HAAR_TILTED_NAME "tilted"
# define ICV_HAAR_THRESHOLD_NAME "threshold"
# define ICV_HAAR_LEFT_NODE_NAME "left_node"
# define ICV_HAAR_LEFT_VAL_NAME "left_val"
# define ICV_HAAR_RIGHT_NODE_NAME "right_node"
# define ICV_HAAR_RIGHT_VAL_NAME "right_val"
# define ICV_HAAR_STAGE_THRESHOLD_NAME "stage_threshold"
# define ICV_HAAR_PARENT_NAME "parent"
# define ICV_HAAR_NEXT_NAME "next"
# define ICV_HAAR_TREES_NAME "trees"
# define ICV_HAAR_FEATURE_NAME "feature"
# define ICV_HAAR_RECTS_NAME "rects"
# define ICV_HAAR_TILTED_NAME "tilted"
# define ICV_HAAR_THRESHOLD_NAME "threshold"
# define ICV_HAAR_LEFT_NODE_NAME "left_node"
# define ICV_HAAR_LEFT_VAL_NAME "left_val"
# define ICV_HAAR_RIGHT_NODE_NAME "right_node"
# define ICV_HAAR_RIGHT_VAL_NAME "right_val"
# define ICV_HAAR_STAGE_THRESHOLD_NAME "stage_threshold"
# define ICV_HAAR_PARENT_NAME "parent"
# define ICV_HAAR_NEXT_NAME "next"
static int
icvIsHaarClassifier ( const void * struct_ptr )
@ -2418,45 +2531,4 @@ CvType haar_type( CV_TYPE_NAME_HAAR, icvIsHaarClassifier,
icvReadHaarClassifier , icvWriteHaarClassifier ,
icvCloneHaarClassifier ) ;
#if 0
namespace cv
{
HaarClassifierCascade : : HaarClassifierCascade ( ) { }
HaarClassifierCascade : : HaarClassifierCascade ( const String & filename )
{ load ( filename ) ; }
bool HaarClassifierCascade : : load ( const String & filename )
{
cascade = Ptr < CvHaarClassifierCascade > ( ( CvHaarClassifierCascade * ) cvLoad ( filename . c_str ( ) , 0 , 0 , 0 ) ) ;
return ( CvHaarClassifierCascade * ) cascade ! = 0 ;
}
void HaarClassifierCascade : : detectMultiScale ( const Mat & image ,
Vector < Rect > & objects , double scaleFactor ,
int minNeighbors , int flags ,
Size minSize )
{
MemStorage storage ( cvCreateMemStorage ( 0 ) ) ;
CvMat _image = image ;
CvSeq * _objects = cvHaarDetectObjects ( & _image , cascade , storage , scaleFactor ,
minNeighbors , flags , minSize ) ;
Seq < Rect > ( _objects ) . copyTo ( objects ) ;
}
int HaarClassifierCascade : : runAt ( Point pt , int startStage , int ) const
{
return cvRunHaarClassifierCascade ( cascade , pt , startStage ) ;
}
void HaarClassifierCascade : : setImages ( const Mat & sum , const Mat & sqsum ,
const Mat & tilted , double scale )
{
CvMat _sum = sum , _sqsum = sqsum , _tilted = tilted ;
cvSetImagesForHaarClassifierCascade ( cascade , & _sum , & _sqsum , & _tilted , scale ) ;
}
}
# endif
/* End of file. */
Vadim Pisarevsky
13 years ago