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#include "_cv.h"
/****************************************************************************************\
Down-sampling pyramids core functions
\****************************************************************************************/
//////////// Filtering macros /////////////
/* COMMON CASE */
/* 1/16[1 4 6 4 1] */
/* ...| x0 | x1 | x2 | x3 | x4 |... */
#define PD_FILTER( x0, x1, x2, x3, x4 ) ((x2)*6+((x1)+(x3))*4+(x0)+(x4))
/* MACROS FOR BORDERS */
/* | b I a | b | reflection used ("I" denotes the image boundary) */
/* LEFT/TOP */
/* 1/16[1 4 6 4 1] */
/* | x2 | x1 I x0 | x1 | x2 |... */
#define PD_LT(x0,x1,x2) ((x0)*6 + (x1)*8 + (x2)*2)
/* RIGHT/BOTTOM */
/* 1/16[1 4 6 4 1] */
/* ...| x0 | x1 | x2 | x3 I x2 | */
#define PD_RB(x0,x1,x2,x3) ((x0) + ((x1) + (x3))*4 + (x2)*7)
/* SINGULAR CASE ( width == 2 || height == 2 ) */
/* 1/16[1 4 6 4 1] */
/* | x0 | x1 I x0 | x1 I x0 | */
#define PD_SINGULAR(x0,x1) (((x0) + (x1))*8)
#define PD_SCALE_INT(x) (((x) + (1<<7)) >> 8)
#define PD_SCALE_FLT(x) ((x)*0.00390625f)
#define PD_SZ 5
////////// generic macro ////////////
#define ICV_DEF_PYR_DOWN_FUNC( flavor, type, worktype, _pd_scale_ ) \
static CvStatus CV_STDCALL \
icvPyrDownG5x5_##flavor##_CnR( const type* src, int srcstep, type* dst, \
int dststep, CvSize size, void *buf, int Cs ) \
{ \
worktype* buffer = (worktype*)buf; /* pointer to temporary buffer */ \
worktype* rows[PD_SZ]; /* array of rows pointers. dim(rows) is PD_SZ */ \
int y, top_row = 0; \
int Wd = size.width/2, Wdn = Wd*Cs; \
int buffer_step = Wdn; \
int pd_sz = (PD_SZ + 1)*buffer_step; \
int fst = 0, lst = size.height <= PD_SZ/2 ? size.height : PD_SZ/2 + 1; \
\
assert( Cs == 1 || Cs == 3 ); \
srcstep /= sizeof(src[0]); dststep /= sizeof(dst[0]); \
\
/* main loop */ \
for( y = 0; y < size.height; y += 2, dst += dststep ) \
{ \
/* set first and last indices of buffer rows which are need to be filled */ \
int x, y1, k = top_row; \
int x1 = buffer_step; \
worktype *row01, *row23, *row4; \
\
/* assign rows pointers */ \
for( y1 = 0; y1 < PD_SZ; y1++ ) \
{ \
rows[y1] = buffer + k; \
k += buffer_step; \
k &= k < pd_sz ? -1 : 0; \
} \
\
row01 = rows[0]; \
row23 = rows[2]; \
row4 = rows[4]; \
\
/* fill new buffer rows with filtered source (horizontal conv) */ \
if( Cs == 1 ) \
{ \
if( size.width > PD_SZ/2 ) \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
worktype *row = rows[y1]; \
\
/* process left & right bounds */ \
row[0] = PD_LT( src[0], src[1], src[2] ); \
row[Wd-1] = PD_RB( src[Wd*2-4], src[Wd*2-3], \
src[Wd*2-2], src[Wd*2-1]); \
/* other points (even) */ \
for( x = 1; x < Wd - 1; x++ ) \
{ \
row[x] = PD_FILTER( src[2*x-2], src[2*x-1], src[2*x], \
src[2*x+1], src[2*x+2] ); \
} \
} \
else \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
rows[y1][0] = PD_SINGULAR( src[0], src[1] ); \
} \
} \
else /* Cs == 3 */ \
{ \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
worktype *row = rows[y1]; \
\
if( size.width > PD_SZ/2 ) \
{ \
int c; \
for( c = 0; c < 3; c++ ) \
{ \
/* process left & right bounds */ \
row[c] = PD_LT( src[c], src[3+c], src[6+c] ); \
row[Wdn-3+c] = PD_RB( src[Wdn*2-12+c], src[Wdn*2-9+c], \
src[Wdn*2-6+c], src[Wdn*2-3+c] ); \
} \
/* other points (even) */ \
for( x = 3; x < Wdn - 3; x += 3 ) \
{ \
row[x] = PD_FILTER( src[2*x-6], src[2*x-3], src[2*x], \
src[2*x+3], src[2*x+6] ); \
row[x+1] = PD_FILTER( src[2*x-5], src[2*x-2], src[2*x+1], \
src[2*x+4], src[2*x+7] ); \
row[x+2] = PD_FILTER( src[2*x-4], src[2*x-1], src[2*x+2], \
src[2*x+5], src[2*x+8] ); \
} \
} \
else /* size.width <= PD_SZ/2 */ \
{ \
row[0] = PD_SINGULAR( src[0], src[3] ); \
row[1] = PD_SINGULAR( src[1], src[4] ); \
row[2] = PD_SINGULAR( src[2], src[5] ); \
} \
} \
} \
\
/* second pass. Do vertical conv and write results do destination image */ \
if( y > 0 ) \
{ \
if( y < size.height - PD_SZ/2 ) \
{ \
for( x = 0; x < Wdn; x++, x1++ ) \
{ \
dst[x] = (type)_pd_scale_( PD_FILTER( row01[x], row01[x1], \
row23[x], row23[x1], row4[x] )); \
} \
top_row += 2*buffer_step; \
top_row &= top_row < pd_sz ? -1 : 0; \
} \
else /* bottom */ \
for( x = 0; x < Wdn; x++, x1++ ) \
dst[x] = (type)_pd_scale_( PD_RB( row01[x], row01[x1], \
row23[x], row23[x1])); \
} \
else \
{ \
if( size.height > PD_SZ/2 ) /* top */ \
{ \
for( x = 0; x < Wdn; x++, x1++ ) \
dst[x] = (type)_pd_scale_( PD_LT( row01[x], row01[x1], row23[x] )); \
} \
else /* size.height <= PD_SZ/2 */ \
{ \
for( x = 0; x < Wdn; x++, x1++ ) \
dst[x] = (type)_pd_scale_( PD_SINGULAR( row01[x], row01[x1] )); \
} \
fst = PD_SZ - 2; \
} \
\
lst = y + 2 + PD_SZ/2 < size.height ? PD_SZ : size.height - y; \
} \
\
return CV_OK; \
}
ICV_DEF_PYR_DOWN_FUNC( 8u, uchar, int, PD_SCALE_INT )
ICV_DEF_PYR_DOWN_FUNC( 16s, short, int, PD_SCALE_INT )
ICV_DEF_PYR_DOWN_FUNC( 16u, ushort, int, PD_SCALE_INT )
ICV_DEF_PYR_DOWN_FUNC( 32f, float, float, PD_SCALE_FLT )
ICV_DEF_PYR_DOWN_FUNC( 64f, double, double, PD_SCALE_FLT )
/****************************************************************************************\
Up-sampling pyramids core functions
\****************************************************************************************/
/////////// filtering macros //////////////
/* COMMON CASE: NON ZERO */
/* 1/16[1 4 6 4 1] */
/* ...| x0 | 0 | x1 | 0 | x2 |... */
#define PU_FILTER( x0, x1, x2 ) ((x1)*6 + (x0) + (x2))
/* ZERO POINT AT CENTER */
/* 1/16[1 4 6 4 1] */
/* ...| 0 | x0 | 0 | x1 | 0 |... */
#define PU_FILTER_ZI( x0, x1 ) (((x0) + (x1))*4)
/* MACROS FOR BORDERS */
/* | b I a | b | reflection */
/* LEFT/TOP */
/* 1/16[1 4 6 4 1] */
/* | x1 | 0 I x0 | 0 | x1 |... */
#define PU_LT( x0, x1 ) ((x0)*6 + (x1)*2)
/* 1/16[1 4 6 4 1] */
/* | 0 I x0 | 0 | x1 | 0 |... */
#define PU_LT_ZI( x0, x1 ) PU_FILTER_ZI((x0),(x1))
/* RIGHT/BOTTOM: NON ZERO */
/* 1/16[1 4 6 4 1] */
/* ...| x0 | 0 | x1 | 0 I x1 | */
#define PU_RB( x0, x1 ) ((x0) + (x1)*7)
/* RIGHT/BOTTOM: ZERO POINT AT CENTER */
/* 1/16[1 4 6 4 1] */
/* ...| 0 | x0 | 0 I x0 | 0 | */
#define PU_RB_ZI( x0 ) ((x0)*8)
/* SINGULAR CASE */
/* 1/16[1 4 6 4 1] */
/* | x0 | 0 I x0 | 0 I x0 | */
#define PU_SINGULAR( x0 ) PU_RB_ZI((x0)) /* <--| the same formulas */
#define PU_SINGULAR_ZI( x0 ) PU_RB_ZI((x0)) /* <--| */
/* x/64 - scaling in up-sampling functions */
#define PU_SCALE_INT(x) (((x) + (1<<5)) >> 6)
#define PU_SCALE_FLT(x) ((x)*0.015625f)
#define PU_SZ 3
//////////// generic macro /////////////
#define ICV_DEF_PYR_UP_FUNC( flavor, type, worktype, _pu_scale_ ) \
static CvStatus CV_STDCALL \
icvPyrUpG5x5_##flavor##_CnR( const type* src, int srcstep, type* dst, \
int dststep, CvSize size, void *buf, int Cs ) \
{ \
worktype *buffer = (worktype*)buf; \
worktype *rows[PU_SZ]; \
int y, top_row = 0; \
int Wd = size.width * 2, Wdn = Wd * Cs, Wn = size.width * Cs; \
int buffer_step = Wdn; \
int pu_sz = PU_SZ*buffer_step; \
int fst = 0, lst = size.height <= PU_SZ/2 ? size.height : PU_SZ/2 + 1; \
\
assert( Cs == 1 || Cs == 3 ); \
srcstep /= sizeof(src[0]); dststep /= sizeof(dst[0]); \
\
/* main loop */ \
for( y = 0; y < size.height; y++, dst += 2 * dststep ) \
{ \
int x, y1, k = top_row; \
worktype *row0, *row1, *row2; \
type *dst1; \
\
/* assign rows pointers */ \
for( y1 = 0; y1 < PU_SZ; y1++ ) \
{ \
rows[y1] = buffer + k; \
k += buffer_step; \
k &= k < pu_sz ? -1 : 0; \
} \
\
row0 = rows[0]; \
row1 = rows[1]; \
row2 = rows[2]; \
dst1 = dst + dststep; \
\
/* fill new buffer rows with filtered source (horizontal conv) */ \
if( Cs == 1 ) \
if( size.width > PU_SZ / 2 ) \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
worktype *row = rows[y1]; \
\
/* process left & right bounds */ \
row[0] = PU_LT( src[0], src[1] ); \
row[1] = PU_LT_ZI( src[0], src[1] ); \
row[size.width * 2 - 2] = PU_RB( src[size.width - 2], \
src[size.width - 1] ); \
row[size.width * 2 - 1] = PU_RB_ZI( src[size.width - 1] ); \
/* other points */ \
for( x = 1; x < size.width - 1; x++ ) \
{ \
row[2 * x] = PU_FILTER( src[x - 1], src[x], src[x + 1] ); \
row[2 * x + 1] = PU_FILTER_ZI( src[x], src[x + 1] ); \
} \
} \
else /* size.width <= PU_SZ/2 */ \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
worktype *row = rows[y1]; \
worktype val = src[0]; \
\
row[0] = PU_SINGULAR( val ); \
row[1] = PU_SINGULAR_ZI( val ); \
} \
else /* Cs == 3 */ \
for( y1 = fst; y1 < lst; y1++, src += srcstep ) \
{ \
worktype *row = rows[y1]; \
\
if( size.width > PU_SZ / 2 ) \
{ \
int c; \
\
for( c = 0; c < 3; c++ ) \
{ \
/* process left & right bounds */ \
row[c] = PU_LT( src[c], src[3 + c] ); \
row[3 + c] = PU_LT_ZI( src[c], src[3 + c] ); \
row[Wn * 2 - 6 + c] = PU_RB( src[Wn - 6 + c], src[Wn - 3 + c]); \
row[Wn * 2 - 3 + c] = PU_RB_ZI( src[Wn - 3 + c] ); \
} \
/* other points */ \
for( x = 3; x < Wn - 3; x += 3 ) \
{ \
row[2 * x] = PU_FILTER( src[x - 3], src[x], src[x + 3] ); \
row[2 * x + 3] = PU_FILTER_ZI( src[x], src[x + 3] ); \
\
row[2 * x + 1] = PU_FILTER( src[x - 2], src[x + 1], src[x + 4]);\
row[2 * x + 4] = PU_FILTER_ZI( src[x + 1], src[x + 4] ); \
\
row[2 * x + 2] = PU_FILTER( src[x - 1], src[x + 2], src[x + 5]);\
row[2 * x + 5] = PU_FILTER_ZI( src[x + 2], src[x + 5] ); \
} \
} \
else /* size.width <= PU_SZ/2 */ \
{ \
int c; \
\
for( c = 0; c < 3; c++ ) \
{ \
row[c] = PU_SINGULAR( src[c] ); \
row[3 + c] = PU_SINGULAR_ZI( src[c] ); \
} \
} \
} \
\
/* second pass. Do vertical conv and write results do destination image */ \
if( y > 0 ) \
{ \
if( y < size.height - PU_SZ / 2 ) \
{ \
for( x = 0; x < Wdn; x++ ) \
{ \
dst[x] = (type)_pu_scale_( PU_FILTER( row0[x], row1[x], row2[x] )); \
dst1[x] = (type)_pu_scale_( PU_FILTER_ZI( row1[x], row2[x] )); \
} \
top_row += buffer_step; \
top_row &= top_row < pu_sz ? -1 : 0; \
} \
else /* bottom */ \
for( x = 0; x < Wdn; x++ ) \
{ \
dst[x] = (type)_pu_scale_( PU_RB( row0[x], row1[x] )); \
dst1[x] = (type)_pu_scale_( PU_RB_ZI( row1[x] )); \
} \
} \
else \
{ \
if( size.height > PU_SZ / 2 ) /* top */ \
for( x = 0; x < Wdn; x++ ) \
{ \
dst[x] = (type)_pu_scale_( PU_LT( row0[x], row1[x] )); \
dst1[x] = (type)_pu_scale_( PU_LT_ZI( row0[x], row1[x] )); \
} \
else /* size.height <= PU_SZ/2 */ \
for( x = 0; x < Wdn; x++ ) \
{ \
dst[x] = (type)_pu_scale_( PU_SINGULAR( row0[x] )); \
dst1[x] = (type)_pu_scale_( PU_SINGULAR_ZI( row0[x] )); \
} \
fst = PU_SZ - 1; \
} \
\
lst = y < size.height - PU_SZ/2 - 1 ? PU_SZ : size.height + PU_SZ/2 - y - 1; \
} \
\
return CV_OK; \
}
ICV_DEF_PYR_UP_FUNC( 8u, uchar, int, PU_SCALE_INT )
ICV_DEF_PYR_UP_FUNC( 16s, short, int, PU_SCALE_INT )
ICV_DEF_PYR_UP_FUNC( 16u, ushort, int, PU_SCALE_INT )
ICV_DEF_PYR_UP_FUNC( 32f, float, float, PU_SCALE_FLT )
ICV_DEF_PYR_UP_FUNC( 64f, double, double, PU_SCALE_FLT )
static CvStatus CV_STDCALL
icvPyrUpG5x5_GetBufSize( int roiWidth, CvDataType dataType,
int channels, int *bufSize )
{
int bufStep;
if( !bufSize )
return CV_NULLPTR_ERR;
*bufSize = 0;
if( roiWidth < 0 )
return CV_BADSIZE_ERR;
if( channels != 1 && channels != 3 )
return CV_UNSUPPORTED_CHANNELS_ERR;
bufStep = 2*roiWidth*channels;
if( dataType == cv64f )
bufStep *= sizeof(double);
else
bufStep *= sizeof(int);
*bufSize = bufStep * PU_SZ;
return CV_OK;
}
static CvStatus CV_STDCALL
icvPyrDownG5x5_GetBufSize( int roiWidth, CvDataType dataType,
int channels, int *bufSize )
{
int bufStep;
if( !bufSize )
return CV_NULLPTR_ERR;
*bufSize = 0;
if( roiWidth < 0 || (roiWidth & 1) != 0 )
return CV_BADSIZE_ERR;
if( channels != 1 && channels != 3 )
return CV_UNSUPPORTED_CHANNELS_ERR;
bufStep = 2*roiWidth*channels;
if( dataType == cv64f )
bufStep *= sizeof(double);
else
bufStep *= sizeof(int);
*bufSize = bufStep * (PD_SZ + 1);
return CV_OK;
}
/****************************************************************************************\
Downsampled image border completion
\****************************************************************************************/
#define ICV_DEF_PYR_BORDER_FUNC( flavor, arrtype, worktype, _pd_scale_ ) \
static CvStatus CV_STDCALL \
icvPyrDownBorder_##flavor##_CnR( const arrtype *src, int src_step, CvSize src_size, \
arrtype *dst, int dst_step, CvSize dst_size, int channels ) \
{ \
int local_alloc = 0; \
worktype *buf = 0, *buf0 = 0; \
const arrtype* src2; \
arrtype* dst2; \
int buf_size; \
int i, j; \
int W = src_size.width, H = src_size.height; \
int Wd = dst_size.width, Hd = dst_size.height; \
int Wd_, Hd_; \
int Wn = W*channels; \
int bufW; \
int cols, rows; /* columns and rows to modify */ \
\
assert( channels == 1 || channels == 3 ); \
\
buf_size = MAX(src_size.width,src_size.height) * sizeof(buf[0]) * 2 * channels; \
if( buf_size > (1 << 14) ) \
{ \
buf = (worktype*)cvAlloc( buf_size ); \
if( !buf ) \
return CV_OUTOFMEM_ERR; \
} \
else \
{ \
buf = (worktype*)cvAlignPtr(alloca( buf_size+8 ), 8); \
local_alloc = 1; \
} \
\
buf0 = buf; \
\
src_step /= sizeof(src[0]); \
dst_step /= sizeof(dst[0]); \
\
cols = (W & 1) + (Wd*2 > W); \
rows = (H & 1) + (Hd*2 > H); \
\
src2 = src + (H-1)*src_step; \
dst2 = dst + (Hd - rows)*dst_step; \
src += (W - 1)*channels; \
dst += (Wd - cols)*channels; \
\
/* part of row(column) from 1 to Wd_(Hd_) is processed using PD_FILTER macro */ \
Wd_ = Wd - 1 + (cols == 1 && (W & 1) != 0); \
Hd_ = Hd - 1 + (rows == 1 && (H & 1) != 0); \
\
bufW = channels * cols; \
\
/******************* STAGE 1. ******************/ \
\
/* do horizontal convolution of the 1-2 right columns and write results to buffer */\
if( cols > 0 ) \
{ \
if( W <= 2 ) \
{ \
assert( Wd == 1 ); \
for( i = 0; i < H; i++, src += src_step, buf += channels ) \
{ \
if( channels == 1 ) \
buf[0] = PD_SINGULAR( src[1-Wn], src[0] ); \
else \
{ \
buf[0] = PD_SINGULAR( src[3-Wn], src[0] ); \
buf[1] = PD_SINGULAR( src[4-Wn], src[1] ); \
buf[2] = PD_SINGULAR( src[5-Wn], src[2] ); \
} \
} \
} \
else if( (W == 3 && Wd == 1) || (W > 3 && !(Wd & 1)) ) \
{ \
for( i = 0; i < H; i++, src += src_step, buf += channels ) \
{ \
if( channels == 1 ) \
buf[0] = PD_LT( src[-2], src[-1], src[0] ); \
else \
{ \
buf[0] = PD_LT( src[-6], src[-3], src[0] ); \
buf[1] = PD_LT( src[-5], src[-2], src[1] ); \
buf[2] = PD_LT( src[-4], src[-1], src[2] ); \
} \
} \
} \
else if( W == 3 ) \
{ \
for( i = 0; i < H; i++, src += src_step, buf += channels*2 ) \
{ \
if( channels == 1 ) \
{ \
buf[0] = PD_LT( src[-2], src[-1], src[0] ); \
buf[1] = PD_LT( src[0], src[-1], src[-2] ); \
} \
else \
{ \
buf[0] = PD_LT( src[-6], src[-3], src[0] ); \
buf[1] = PD_LT( src[-5], src[-2], src[1] ); \
buf[2] = PD_LT( src[-4], src[-1], src[2] ); \
buf[3] = PD_LT( src[0], src[-3], src[-6] ); \
buf[4] = PD_LT( src[1], src[-2], src[-5] ); \
buf[5] = PD_LT( src[2], src[-1], src[-4] ); \
} \
} \
} \
else if( cols == 1 ) \
{ \
for( i = 0; i < H; i++, src += src_step, buf += channels ) \
{ \
if( channels == 1 ) \
buf[0] = PD_FILTER( src[-4], src[-3], src[-2], src[-1], src[0]); \
else \
{ \
buf[0] = PD_FILTER( src[-12], src[-9], src[-6], src[-3], src[0]); \
buf[1] = PD_FILTER( src[-11], src[-8], src[-5], src[-2], src[1]); \
buf[2] = PD_FILTER( src[-10], src[-7], src[-4], src[-1], src[2]); \
} \
} \
} \
else \
{ \
for( i = 0; i < H; i++, src += src_step, buf += channels*2 ) \
{ \
if( channels == 1 ) \
{ \
buf[0] = PD_FILTER( src[-4], src[-3], src[-2], src[-1], src[0] ); \
buf[1] = PD_LT( src[0], src[-1], src[-2] ); \
} \
else \
{ \
buf[0] = PD_FILTER( src[-12], src[-9], src[-6], src[-3], src[0] ); \
buf[1] = PD_FILTER( src[-11], src[-8], src[-5], src[-2], src[1] ); \
buf[2] = PD_FILTER( src[-10], src[-7], src[-4], src[-1], src[2] ); \
buf[3] = PD_LT( src[0], src[-3], src[-6] ); \
buf[4] = PD_LT( src[1], src[-2], src[-5] ); \
buf[5] = PD_LT( src[2], src[-1], src[-4] ); \
} \
} \
} \
buf = buf0; \
} \
\
src = src2; \
\
/******************* STAGE 2. ******************/ \
\
/* do vertical convolution of the pre-processed right columns, */ \
/* stored in buffer, and write results to the destination */ \
/* do vertical convolution of the 1-2 bottom rows */ \
/* and write results to the buffer */ \
if( H <= 2 ) \
{ \
if( cols > 0 ) \
{ \
assert( Hd == 1 ); \
for( j = 0; j < bufW; j++ ) \
dst[j] = (arrtype)_pd_scale_( PD_SINGULAR( buf[j], buf[j+(H-1)*bufW] ));\
} \
\
if( rows > 0 ) \
{ \
for( j = 0; j < Wn; j++ ) \
buf[j] = PD_SINGULAR( src[j-src_step], src[j] ); \
} \
} \
else if( H == 3 ) \
{ \
if( cols > 0 ) \
{ \
for( j = 0; j < bufW; j++ ) \
{ \
dst[j]= (arrtype)_pd_scale_(PD_LT( buf[j], buf[j+bufW], buf[j+bufW*2]));\
} \
if( Hd == 2 ) \
{ \
dst += dst_step; \
for( j = 0; j < bufW; j++ ) \
dst[j] = (arrtype)_pd_scale_( PD_LT( buf[j+bufW*2], \
buf[j+bufW], buf[j] )); \
} \
} \
\
if( Hd == 1 ) \
{ \
for( j = 0; j < Wn; j++ ) \
buf[j] = PD_LT( src[j-src_step*2], src[j - src_step], src[j] ); \
} \
else \
{ \
for( j = 0; j < Wn; j++ ) \
{ \
buf[j] = PD_LT( src[j-src_step*2], src[j - src_step], src[j] ); \
buf[j+Wn] = PD_LT( src[j],src[j-src_step],src[j-src_step*2] ); \
} \
} \
} \
else \
{ \
if( cols > 0 ) \
{ \
/* top of the right border */ \
for( j = 0; j < bufW; j++ ) \
dst[j]=(arrtype)_pd_scale_( PD_LT( buf[j], buf[j+bufW], buf[j+bufW*2]));\
\
/* middle part of the right border */ \
buf += bufW*2; \
dst += dst_step; \
for( i = 1; i < Hd_; i++, dst += dst_step, buf += bufW*2 ) \
{ \
for( j = 0; j < bufW; j++ ) \
dst[j] = (arrtype)_pd_scale_( PD_FILTER( buf[j-bufW*2], buf[j-bufW],\
buf[j], buf[j+bufW], buf[j+bufW*2] ));\
} \
\
/* bottom of the right border */ \
if( !(H & 1) ) \
{ \
for( j = 0; j < bufW; j++ ) \
dst[j] = (arrtype)_pd_scale_( PD_RB( buf[j-bufW*2], buf[j-bufW], \
buf[j], buf[j+bufW] )); \
} \
else if( rows > 1 ) \
{ \
for( j = 0; j < bufW; j++ ) \
dst[j]=(arrtype)_pd_scale_( PD_LT( buf[j-bufW*2], \
buf[j-bufW], buf[j])); \
} \
\
buf = buf0; \
} \
\
if( rows > 0 ) \
{ \
if( !(H & 1) ) \
{ \
for( j = 0; j < Wn; j++ ) \
buf[j] = PD_LT( src[j], src[j-src_step], src[j-src_step*2] ); \
} \
else if( cols == 1 ) \
{ \
for( j = 0; j < Wn; j++ ) \
buf[j] = PD_FILTER( src[j-src_step*4], src[j-src_step*3], \
src[j-src_step*2], src[j-src_step], src[j] ); \
} \
else \
{ \
for( j = 0; j < Wn; j++ ) \
{ \
buf[j] = PD_FILTER( src[j-src_step*4], src[j-src_step*3], \
src[j-src_step*2], src[j-src_step], src[j] ); \
buf[j+Wn] = PD_LT( src[j], src[j-src_step], src[j-src_step*2] ); \
} \
} \
} \
} \
\
\
/******************* STAGE 3. ******************/ \
\
/* do horizontal convolution of the pre-processed bottom rows,*/ \
/* stored in buffer, and write results to the destination */ \
if( rows > 0 ) \
{ \
dst = dst2; \
\
if( W <= 2 ) \
{ \
assert( Wd == 1 ); \
for( ; rows--; dst += dst_step, buf += Wn ) \
{ \
if( channels == 1 ) \
dst[0] = (arrtype)_pd_scale_( PD_SINGULAR( buf[0], buf[Wn-1] )); \
else \
{ \
dst[0] = (arrtype)_pd_scale_( PD_SINGULAR( buf[0], buf[Wn-3] )); \
dst[1] = (arrtype)_pd_scale_( PD_SINGULAR( buf[1], buf[Wn-2] )); \
dst[2] = (arrtype)_pd_scale_( PD_SINGULAR( buf[2], buf[Wn-1] )); \
} \
} \
} \
else if( W == 3 ) \
{ \
if( Wd == 1 ) \
{ \
for( ; rows--; dst += dst_step, buf += Wn ) \
{ \
if( channels == 1 ) \
dst[0] = (arrtype)_pd_scale_( PD_LT(buf[0], buf[1], buf[2] )); \
else \
{ \
dst[0] = (arrtype)_pd_scale_( PD_LT(buf[0], buf[3], buf[6] )); \
dst[1] = (arrtype)_pd_scale_( PD_LT(buf[1], buf[4], buf[7] )); \
dst[2] = (arrtype)_pd_scale_( PD_LT(buf[2], buf[5], buf[8] )); \
} \
} \
} \
else \
{ \
for( ; rows--; dst += dst_step, buf += Wn ) \
{ \
if( channels == 1 ) \
{ \
dst[0] = (arrtype)_pd_scale_( PD_LT(buf[0], buf[1], buf[2] )); \
dst[1] = (arrtype)_pd_scale_( PD_LT(buf[2], buf[1], buf[0] )); \
} \
else \
{ \
dst[0] = (arrtype)_pd_scale_( PD_LT(buf[0], buf[3], buf[6] )); \
dst[1] = (arrtype)_pd_scale_( PD_LT(buf[1], buf[4], buf[7] )); \
dst[2] = (arrtype)_pd_scale_( PD_LT(buf[2], buf[5], buf[8] )); \
dst[3] = (arrtype)_pd_scale_( PD_LT(buf[6], buf[3], buf[0] )); \
dst[4] = (arrtype)_pd_scale_( PD_LT(buf[7], buf[4], buf[1] )); \
dst[5] = (arrtype)_pd_scale_( PD_LT(buf[8], buf[5], buf[2] )); \
} \
} \
} \
} \
else \
{ \
for( ; rows--; dst += dst_step, buf += Wn ) \
{ \
if( channels == 1 ) \
{ \
/* left part of the bottom row */ \
dst[0] = (arrtype)_pd_scale_( PD_LT( buf[0], buf[1], buf[2] )); \
\
/* middle part of the bottom row */ \
for( i = 1; i < Wd_; i++ ) \
{ \
dst[i] = (arrtype)_pd_scale_( PD_FILTER(buf[i*2-2], buf[i*2-1], \
buf[i*2],buf[i*2+1], buf[i*2+2] )); \
} \
\
/* right part of the bottom row */ \
if( !(W & 1) ) \
dst[i] = (arrtype)_pd_scale_( PD_RB( buf[i*2-2],buf[i*2-1], \
buf[i*2], buf[i*2+1] )); \
else if( cols > 1 ) \
dst[i] = (arrtype)_pd_scale_( PD_LT( buf[i*2-2], \
buf[i*2-1], buf[i*2] )); \
} \
else \
{ \
/* left part of the bottom row */ \
dst[0] = (arrtype)_pd_scale_( PD_LT( buf[0], buf[3], buf[6] )); \
dst[1] = (arrtype)_pd_scale_( PD_LT( buf[1], buf[4], buf[7] )); \
dst[2] = (arrtype)_pd_scale_( PD_LT( buf[2], buf[5], buf[8] )); \
\
/* middle part of the bottom row */ \
for( i = 3; i < Wd_*3; i++ ) \
{ \
dst[i] = (arrtype)_pd_scale_( PD_FILTER(buf[i*2-6], buf[i*2-3], \
buf[i*2],buf[i*2+3], buf[i*2+6]));\
} \
\
/* right part of the bottom row */ \
if( !(W & 1) ) \
{ \
dst[i] = (arrtype)_pd_scale_( PD_RB( buf[i*2-6],buf[i*2-3], \
buf[i*2], buf[i*2+3] )); \
dst[i+1] = (arrtype)_pd_scale_( PD_RB( buf[i*2-5],buf[i*2-2], \
buf[i*2+1], buf[i*2+4] )); \
dst[i+2] = (arrtype)_pd_scale_( PD_RB( buf[i*2-4],buf[i*2-1], \
buf[i*2+2], buf[i*2+5] )); \
} \
else if( cols > 1 ) \
{ \
dst[i] = (arrtype)_pd_scale_( PD_LT( buf[i*2-6], buf[i*2-3], buf[i*2] )); \
dst[i+1] = (arrtype)_pd_scale_( PD_LT( buf[i*2-5], buf[i*2-2], buf[i*2+1]));\
dst[i+2] = (arrtype)_pd_scale_( PD_LT( buf[i*2-4], buf[i*2-1], buf[i*2+2]));\
} \
} \
} \
} \
} \
\
if( !local_alloc ) \
cvFree( &buf0 ); \
\
return CV_OK; \
}
#define ICV_DEF_INIT_PYR_TABLE( FUNCNAME ) \
static void icvInit##FUNCNAME##Table( CvFuncTable* tab ) \
{ \
tab->fn_2d[CV_8U] = (void*)icv##FUNCNAME##_8u_CnR; \
tab->fn_2d[CV_8S] = 0; \
tab->fn_2d[CV_16S] = (void*)icv##FUNCNAME##_16s_CnR; \
tab->fn_2d[CV_16U] = (void*)icv##FUNCNAME##_16u_CnR; \
tab->fn_2d[CV_32F] = (void*)icv##FUNCNAME##_32f_CnR; \
tab->fn_2d[CV_64F] = (void*)icv##FUNCNAME##_64f_CnR; \
}
static void icvInitPyrDownBorderTable( CvFuncTable* tab );
ICV_DEF_INIT_PYR_TABLE( PyrUpG5x5 )
ICV_DEF_INIT_PYR_TABLE( PyrDownG5x5 )
typedef CvStatus (CV_STDCALL * CvPyrDownBorderFunc)( const void* src, int srcstep,
CvSize srcsize, void* dst,
int dststep, CvSize dstsize, int cn );
////////////////////////////// IPP pyramid functions /////////////////////////////////////
icvPyrDown_Gauss5x5_8u_C1R_t icvPyrDown_Gauss5x5_8u_C1R_p = 0;
icvPyrDown_Gauss5x5_8u_C3R_t icvPyrDown_Gauss5x5_8u_C3R_p = 0;
icvPyrDown_Gauss5x5_32f_C1R_t icvPyrDown_Gauss5x5_32f_C1R_p = 0;
icvPyrDown_Gauss5x5_32f_C3R_t icvPyrDown_Gauss5x5_32f_C3R_p = 0;
icvPyrUp_Gauss5x5_8u_C1R_t icvPyrUp_Gauss5x5_8u_C1R_p = 0;
icvPyrUp_Gauss5x5_8u_C3R_t icvPyrUp_Gauss5x5_8u_C3R_p = 0;
icvPyrUp_Gauss5x5_32f_C1R_t icvPyrUp_Gauss5x5_32f_C1R_p = 0;
icvPyrUp_Gauss5x5_32f_C3R_t icvPyrUp_Gauss5x5_32f_C3R_p = 0;
icvPyrUpGetBufSize_Gauss5x5_t icvPyrUpGetBufSize_Gauss5x5_p = 0;
icvPyrDownGetBufSize_Gauss5x5_t icvPyrDownGetBufSize_Gauss5x5_p = 0;
typedef CvStatus (CV_STDCALL * CvPyramidFunc)
( const void* src, int srcstep, void* dst,
int dststep, CvSize size, void* buffer, int cn );
typedef CvStatus (CV_STDCALL * CvPyramidIPPFunc)
( const void* src, int srcstep, void* dst, int dststep, CvSize size, void* buffer );
//////////////////////////////////////////////////////////////////////////////////////////
/****************************************************************************************\
* External functions *
\****************************************************************************************/
CV_IMPL void
cvPyrUp( const void* srcarr, void* dstarr, int _filter )
{
static CvFuncTable pyrup_tab;
static int inittab = 0;
void *buffer = 0;
int local_alloc = 0;
CV_FUNCNAME( "cvPyrUp" );
__BEGIN__;
int coi1 = 0, coi2 = 0;
int buffer_size = 0;
int type, depth, cn;
CvMat srcstub, *src = (CvMat*)srcarr;
CvMat dststub, *dst = (CvMat*)dstarr;
CvFilter filter = (CvFilter) _filter;
CvPyramidFunc func;
CvPyramidIPPFunc ipp_func = 0;
int use_ipp = 0;
CvSize size;
if( !inittab )
{
icvInitPyrUpG5x5Table( &pyrup_tab );
inittab = 1;
}
CV_CALL( src = cvGetMat( src, &srcstub, &coi1 ));
CV_CALL( dst = cvGetMat( dst, &dststub, &coi2 ));
if( coi1 != 0 || coi2 != 0 )
CV_ERROR( CV_BadCOI, "" );
if( filter != CV_GAUSSIAN_5x5 )
CV_ERROR( CV_StsBadArg, "this filter type not supported" );
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedFormats, "" );
if( src->cols*2 != dst->cols || src->rows*2 != dst->rows )
CV_ERROR( CV_StsUnmatchedSizes, "" );
size = cvGetMatSize(src);
type = CV_MAT_TYPE(src->type);
depth = CV_MAT_DEPTH(type);
cn = CV_MAT_CN(type);
if( cn != 1 && cn != 3 )
CV_ERROR( CV_StsUnsupportedFormat, "The images must have 1 or 3 channel" );
func = (CvPyramidFunc)pyrup_tab.fn_2d[depth];
if( !func )
CV_ERROR( CV_StsUnsupportedFormat, "" );
if( icvPyrUpGetBufSize_Gauss5x5_p )
{
ipp_func = type == CV_8UC1 ? icvPyrUp_Gauss5x5_8u_C1R_p :
type == CV_8UC3 ? icvPyrUp_Gauss5x5_8u_C3R_p :
type == CV_32FC1 ? icvPyrUp_Gauss5x5_32f_C1R_p :
type == CV_32FC3 ? icvPyrUp_Gauss5x5_32f_C3R_p : 0;
use_ipp = ipp_func && icvPyrUpGetBufSize_Gauss5x5_p( size.width,
icvDepthToDataType(type), cn, &buffer_size ) >= 0;
}
if( !use_ipp )
icvPyrUpG5x5_GetBufSize( size.width, icvDepthToDataType(type), cn, &buffer_size );
if( buffer_size <= CV_MAX_LOCAL_SIZE )
{
buffer = cvStackAlloc( buffer_size );
local_alloc = 1;
}
else
CV_CALL( buffer = cvAlloc( buffer_size ));
if( !use_ipp )
func( src->data.ptr, src->step, dst->data.ptr, dst->step, size, buffer, cn );
else
IPPI_CALL( ipp_func( src->data.ptr, src->step ? src->step : CV_STUB_STEP,
dst->data.ptr, dst->step ? dst->step : CV_STUB_STEP, size, buffer ));
__END__;
if( buffer && !local_alloc )
cvFree( &buffer );
}
CV_IMPL void
cvPyrDown( const void* srcarr, void* dstarr, int _filter )
{
static CvFuncTable pyrdown_tab;
static CvFuncTable pyrdownborder_tab;
static int inittab = 0;
void *buffer = 0;
int local_alloc = 0;
CV_FUNCNAME( "cvPyrDown" );
__BEGIN__;
int coi1 = 0, coi2 = 0;
int buffer_size = 0;
int type, depth, cn;
CvMat srcstub, *src = (CvMat*)srcarr;
CvMat dststub, *dst = (CvMat*)dstarr;
CvFilter filter = (CvFilter) _filter;
CvPyramidFunc func;
CvPyramidIPPFunc ipp_func = 0;
int use_ipp = 0;
CvSize src_size, src_size2, dst_size;
if( !inittab )
{
icvInitPyrDownG5x5Table( &pyrdown_tab );
icvInitPyrDownBorderTable( &pyrdownborder_tab );
inittab = 1;
}
CV_CALL( src = cvGetMat( src, &srcstub, &coi1 ));
CV_CALL( dst = cvGetMat( dst, &dststub, &coi2 ));
if( coi1 != 0 || coi2 != 0 )
CV_ERROR( CV_BadCOI, "" );
if( filter != CV_GAUSSIAN_5x5 )
CV_ERROR( CV_StsBadArg, "this filter type not supported" );
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedFormats, "" );
src_size = cvGetMatSize(src);
dst_size = cvGetMatSize(dst);
src_size2.width = src_size.width & -2;
src_size2.height = src_size.height & -2;
if( (unsigned)(dst_size.width - src_size.width/2) > 1 ||
(unsigned)(dst_size.height - src_size.height/2) > 1 )
CV_ERROR( CV_StsUnmatchedSizes, "" );
// current restriction of PyrDownBorder*
if( (src_size.width <= 2 && dst_size.width != 1) ||
(src_size.height <= 2 && dst_size.height != 1) )
CV_ERROR( CV_StsUnmatchedSizes, "" );
/*if( src->data.ptr == dst->data.ptr )
CV_ERROR( CV_StsInplaceNotSupported, "" );*/
type = CV_MAT_TYPE(src->type);
depth = CV_MAT_DEPTH(type);
cn = CV_MAT_CN(type);
if( cn != 1 && cn != 3 )
CV_ERROR( CV_StsUnsupportedFormat, "The images must have 1 or 3 channel" );
func = (CvPyramidFunc)pyrdown_tab.fn_2d[depth];
if( !func )
CV_ERROR( CV_StsUnsupportedFormat, "" );
if( icvPyrDownGetBufSize_Gauss5x5_p )
{
ipp_func = type == CV_8UC1 ? icvPyrDown_Gauss5x5_8u_C1R_p :
type == CV_8UC3 ? icvPyrDown_Gauss5x5_8u_C3R_p :
type == CV_32FC1 ? icvPyrDown_Gauss5x5_32f_C1R_p :
type == CV_32FC3 ? icvPyrDown_Gauss5x5_32f_C3R_p : 0;
use_ipp = ipp_func && icvPyrDownGetBufSize_Gauss5x5_p( src_size2.width,
icvDepthToDataType(type), cn, &buffer_size ) >= 0;
}
if( !use_ipp )
icvPyrDownG5x5_GetBufSize( src_size2.width,
icvDepthToDataType(type), cn, &buffer_size );
if( buffer_size <= CV_MAX_LOCAL_SIZE )
{
buffer = cvStackAlloc( buffer_size );
local_alloc = 1;
}
else
CV_CALL( buffer = cvAlloc( buffer_size ));
if( !use_ipp )
func( src->data.ptr, src->step, dst->data.ptr,
dst->step, src_size2, buffer, cn );
else
IPPI_CALL( ipp_func( src->data.ptr, src->step ? src->step : CV_STUB_STEP,
dst->data.ptr, dst->step ? dst->step : CV_STUB_STEP, src_size2, buffer ));
if( src_size.width != dst_size.width*2 || src_size.height != dst_size.height*2 )
{
CvPyrDownBorderFunc border_func = (CvPyrDownBorderFunc)
pyrdownborder_tab.fn_2d[CV_MAT_DEPTH(type)];
if( !border_func )
CV_ERROR( CV_StsUnsupportedFormat, "" );
IPPI_CALL( border_func( src->data.ptr, src->step, src_size,
dst->data.ptr, dst->step, dst_size, CV_MAT_CN(type) ));
}
__END__;
if( buffer && !local_alloc )
cvFree( &buffer );
}
CV_IMPL void
cvReleasePyramid( CvMat*** _pyramid, int extra_layers )
{
CV_FUNCNAME( "cvReleasePyramid" );
__BEGIN__;
CvMat** pyramid;
int i;
if( !_pyramid )
CV_ERROR( CV_StsNullPtr, "" );
pyramid = *_pyramid;
if( pyramid )
{
for( i = 0; i <= extra_layers; i++ )
cvReleaseMat( &pyramid[i] );
}
cvFree( _pyramid );
__END__;
}
CV_IMPL CvMat**
cvCreatePyramid( const CvArr* srcarr, int extra_layers, double rate,
const CvSize* layer_sizes, CvArr* bufarr,
int calc, int filter )
{
CvMat** pyramid = 0;
const float eps = 0.1f;
CV_FUNCNAME( "cvCreatePyramid" );
__BEGIN__;
int i, elem_size, layer_step;
CvMat stub, *src;
CvSize size, layer_size;
uchar* ptr = 0;
CV_CALL( src = cvGetMat( srcarr, &stub ));
if( extra_layers < 0 )
CV_ERROR( CV_StsOutOfRange, "The number of extra layers must be non negative" );
elem_size = CV_ELEM_SIZE(src->type);
size = cvGetMatSize(src);
if( bufarr )
{
CvMat bstub, *buf;
int bufsize = 0;
CV_CALL( buf = cvGetMat( bufarr, &bstub ));
bufsize = buf->rows*buf->cols*CV_ELEM_SIZE(buf->type);
layer_size = size;
for( i = 1; i <= extra_layers; i++ )
{
if( !layer_sizes )
{
layer_size.width = cvRound(layer_size.width*rate+eps);
layer_size.height = cvRound(layer_size.height*rate+eps);
}
else
layer_size = layer_sizes[i-1];
layer_step = layer_size.width*elem_size;
bufsize -= layer_step*layer_size.height;
}
if( bufsize < 0 )
CV_ERROR( CV_StsOutOfRange, "The buffer is too small to fit the pyramid" );
ptr = buf->data.ptr;
}
CV_CALL( pyramid = (CvMat**)cvAlloc( (extra_layers+1)*sizeof(pyramid[0]) ));
memset( pyramid, 0, (extra_layers+1)*sizeof(pyramid[0]) );
pyramid[0] = cvCreateMatHeader( size.height, size.width, src->type );
cvSetData( pyramid[0], src->data.ptr, src->step );
layer_size = size;
for( i = 1; i <= extra_layers; i++ )
{
if( !layer_sizes )
{
layer_size.width = cvRound(layer_size.width*rate + eps);
layer_size.height = cvRound(layer_size.height*rate + eps);
}
else
layer_size = layer_sizes[i];
if( bufarr )
{
pyramid[i] = cvCreateMatHeader( layer_size.height, layer_size.width, src->type );
layer_step = layer_size.width*elem_size;
cvSetData( pyramid[i], ptr, layer_step );
ptr += layer_step*layer_size.height;
}
else
pyramid[i] = cvCreateMat( layer_size.height, layer_size.width, src->type );
if( calc )
cvPyrDown( pyramid[i-1], pyramid[i], filter );
//cvResize( pyramid[i-1], pyramid[i], CV_INTER_LINEAR );
}
__END__;
if( cvGetErrStatus() < 0 )
cvReleasePyramid( &pyramid, extra_layers );
return pyramid;
}
/* MSVC .NET 2003 spends a long time building this, thus, as the code
is not performance-critical, we turn off the optimization here */
#if defined _MSC_VER && _MSC_VER > 1300 && !defined CV_ICC
#pragma optimize("", off)
#endif
ICV_DEF_PYR_BORDER_FUNC( 8u, uchar, int, PD_SCALE_INT )
ICV_DEF_PYR_BORDER_FUNC( 16u, ushort, int, PD_SCALE_INT )
ICV_DEF_PYR_BORDER_FUNC( 16s, short, int, PD_SCALE_INT )
ICV_DEF_PYR_BORDER_FUNC( 32f, float, float, PD_SCALE_FLT )
ICV_DEF_PYR_BORDER_FUNC( 64f, double, double, PD_SCALE_FLT )
#define ICV_DEF_INIT_PYR_BORDER_TABLE( FUNCNAME ) \
static void icvInit##FUNCNAME##Table( CvFuncTable* tab ) \
{ \
tab->fn_2d[CV_8U] = (void*)icv##FUNCNAME##_8u_CnR; \
tab->fn_2d[CV_8S] = 0; \
tab->fn_2d[CV_16U] = (void*)icv##FUNCNAME##_16u_CnR; \
tab->fn_2d[CV_16S] = (void*)icv##FUNCNAME##_16s_CnR; \
tab->fn_2d[CV_32F] = (void*)icv##FUNCNAME##_32f_CnR; \
tab->fn_2d[CV_64F] = (void*)icv##FUNCNAME##_64f_CnR; \
}
ICV_DEF_INIT_PYR_BORDER_TABLE( PyrDownBorder )
/* End of file. */