+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "_cxcore.h"
-
-/****************************************************************************************\
-* Find sum of pixels in the ROI *
-\****************************************************************************************/
-
-#define ICV_SUM_COI_CASE( __op__, len, cn ) \
- for( ; x <= (len) - 4*(cn); x += 4*(cn) ) \
- s0 += __op__(src[x]) + __op__(src[x+(cn)]) + \
- __op__(src[x+(cn)*2]) + __op__(src[x+(cn)*3]);\
- \
- for( ; x < (len); x += (cn) ) \
- s0 += __op__(src[x]);
-
-
-#define ICV_SUM_CASE_C1( __op__, len ) \
- ICV_SUM_COI_CASE( __op__, len, 1 )
-
-
-#define ICV_SUM_CASE_C2( __op__, len ) \
- for( ; x <= (len) - 8; x += 8 ) \
- { \
- s0 += __op__(src[x]) + __op__(src[x+2]) + \
- __op__(src[x+4]) + __op__(src[x+6]); \
- s1 += __op__(src[x+1]) + __op__(src[x+3]) + \
- __op__(src[x+5]) + __op__(src[x+7]); \
- } \
- \
- for( ; x < (len); x += 2 ) \
- { \
- s0 += __op__(src[x]); \
- s1 += __op__(src[x+1]); \
- }
-
-
-
-#define ICV_SUM_CASE_C3( __op__, len ) \
- for( ; x <= (len) - 12; x += 12 ) \
- { \
- s0 += __op__(src[x]) + __op__(src[x+3]) + \
- __op__(src[x+6]) + __op__(src[x+9]); \
- s1 += __op__(src[x+1]) + __op__(src[x+4]) + \
- __op__(src[x+7]) + __op__(src[x+10]); \
- s2 += __op__(src[x+2]) + __op__(src[x+5]) + \
- __op__(src[x+8]) + __op__(src[x+11]); \
- } \
- \
- for( ; x < (len); x += 3 ) \
- { \
- s0 += __op__(src[x]); \
- s1 += __op__(src[x+1]); \
- s2 += __op__(src[x+2]); \
- }
-
-
-#define ICV_SUM_CASE_C4( __op__, len ) \
- for( ; x <= (len) - 16; x += 16 ) \
- { \
- s0 += __op__(src[x]) + __op__(src[x+4]) + \
- __op__(src[x+8]) + __op__(src[x+12]); \
- s1 += __op__(src[x+1]) + __op__(src[x+5]) + \
- __op__(src[x+9]) + __op__(src[x+13]); \
- s2 += __op__(src[x+2]) + __op__(src[x+6]) + \
- __op__(src[x+10]) + __op__(src[x+14]); \
- s3 += __op__(src[x+3]) + __op__(src[x+7]) + \
- __op__(src[x+11]) + __op__(src[x+15]); \
- } \
- \
- for( ; x < (len); x += 4 ) \
- { \
- s0 += __op__(src[x]); \
- s1 += __op__(src[x+1]); \
- s2 += __op__(src[x+2]); \
- s3 += __op__(src[x+3]); \
- }
-
-
-////////////////////////////////////// entry macros //////////////////////////////////////
-
-#define ICV_SUM_ENTRY_COMMON() \
- step /= sizeof(src[0])
-
-#define ICV_SUM_ENTRY_C1( sumtype ) \
- sumtype s0 = 0; \
- ICV_SUM_ENTRY_COMMON()
-
-#define ICV_SUM_ENTRY_C2( sumtype ) \
- sumtype s0 = 0, s1 = 0; \
- ICV_SUM_ENTRY_COMMON()
-
-#define ICV_SUM_ENTRY_C3( sumtype ) \
- sumtype s0 = 0, s1 = 0, s2 = 0; \
- ICV_SUM_ENTRY_COMMON()
-
-#define ICV_SUM_ENTRY_C4( sumtype ) \
- sumtype s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
- ICV_SUM_ENTRY_COMMON()
-
-
-#define ICV_SUM_ENTRY_BLOCK_COMMON( block_size ) \
- int remaining = block_size; \
- ICV_SUM_ENTRY_COMMON()
-
-#define ICV_SUM_ENTRY_BLOCK_C1( sumtype, worktype, block_size ) \
- sumtype sum0 = 0; \
- worktype s0 = 0; \
- ICV_SUM_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_SUM_ENTRY_BLOCK_C2( sumtype, worktype, block_size ) \
- sumtype sum0 = 0, sum1 = 0; \
- worktype s0 = 0, s1 = 0; \
- ICV_SUM_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_SUM_ENTRY_BLOCK_C3( sumtype, worktype, block_size ) \
- sumtype sum0 = 0, sum1 = 0, sum2 = 0; \
- worktype s0 = 0, s1 = 0, s2 = 0; \
- ICV_SUM_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_SUM_ENTRY_BLOCK_C4( sumtype, worktype, block_size ) \
- sumtype sum0 = 0, sum1 = 0, sum2 = 0, sum3 = 0; \
- worktype s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
- ICV_SUM_ENTRY_BLOCK_COMMON( block_size )
-
-
-/////////////////////////////////////// exit macros //////////////////////////////////////
-
-#define ICV_SUM_EXIT_C1( tmp, sumtype ) \
- sum[0] = (sumtype)tmp##0
-
-#define ICV_SUM_EXIT_C2( tmp, sumtype ) \
- sum[0] = (sumtype)tmp##0; \
- sum[1] = (sumtype)tmp##1;
-
-#define ICV_SUM_EXIT_C3( tmp, sumtype ) \
- sum[0] = (sumtype)tmp##0; \
- sum[1] = (sumtype)tmp##1; \
- sum[2] = (sumtype)tmp##2;
-
-#define ICV_SUM_EXIT_C4( tmp, sumtype ) \
- sum[0] = (sumtype)tmp##0; \
- sum[1] = (sumtype)tmp##1; \
- sum[2] = (sumtype)tmp##2; \
- sum[3] = (sumtype)tmp##3;
-
-#define ICV_SUM_EXIT_BLOCK_C1( sumtype ) \
- sum0 += s0; \
- ICV_SUM_EXIT_C1( sum, sumtype )
-
-#define ICV_SUM_EXIT_BLOCK_C2( sumtype ) \
- sum0 += s0; sum1 += s1; \
- ICV_SUM_EXIT_C2( sum, sumtype )
-
-#define ICV_SUM_EXIT_BLOCK_C3( sumtype ) \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; \
- ICV_SUM_EXIT_C3( sum, sumtype )
-
-#define ICV_SUM_EXIT_BLOCK_C4( sumtype ) \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; sum3 += s3; \
- ICV_SUM_EXIT_C4( sum, sumtype )
-
-////////////////////////////////////// update macros /////////////////////////////////////
-
-#define ICV_SUM_UPDATE_COMMON( block_size ) \
- remaining = block_size
-
-#define ICV_SUM_UPDATE_C1( block_size ) \
- ICV_SUM_UPDATE_COMMON( block_size ); \
- sum0 += s0; \
- s0 = 0
-
-#define ICV_SUM_UPDATE_C2( block_size ) \
- ICV_SUM_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; \
- s0 = s1 = 0
-
-#define ICV_SUM_UPDATE_C3( block_size ) \
- ICV_SUM_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; sum2 += s2; \
- s0 = s1 = s2 = 0
-
-#define ICV_SUM_UPDATE_C4( block_size ) \
- ICV_SUM_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; sum3 += s3; \
- s0 = s1 = s2 = s3 = 0
-
-
-#define ICV_DEF_SUM_NOHINT_BLOCK_FUNC_2D( name, flavor, cn, \
- __op__, arrtype, sumtype_final, sumtype, worktype, block_size )\
-IPCVAPI_IMPL(CvStatus, icv##name##_##flavor##_C##cn##R,( \
- const arrtype* src, int step, CvSize size, \
- sumtype_final* sum ), (src, step, size, sum) ) \
-{ \
- ICV_SUM_ENTRY_BLOCK_C##cn(sumtype,worktype,(block_size)*(cn)); \
- size.width *= cn; \
- \
- for( ; size.height--; src += step ) \
- { \
- int x = 0; \
- while( x < size.width ) \
- { \
- int limit = MIN( remaining, size.width - x ); \
- remaining -= limit; \
- limit += x; \
- ICV_SUM_CASE_C##cn( __op__, limit ); \
- if( remaining == 0 ) \
- { \
- ICV_SUM_UPDATE_C##cn( (block_size)*(cn) ); \
- } \
- } \
- } \
- \
- ICV_SUM_EXIT_BLOCK_C##cn( sumtype_final ); \
- return CV_OK; \
-}
-
-
-#define ICV_DEF_SUM_NOHINT_FUNC_2D( name, flavor, cn, \
- __op__, arrtype, sumtype_final, sumtype, worktype, block_size )\
-IPCVAPI_IMPL(CvStatus, icv##name##_##flavor##_C##cn##R,( \
- const arrtype* src, int step, CvSize size, \
- sumtype_final* sum ), (src, step, size, sum) ) \
-{ \
- ICV_SUM_ENTRY_C##cn( sumtype ); \
- size.width *= cn; \
- \
- for( ; size.height--; src += step ) \
- { \
- int x = 0; \
- ICV_SUM_CASE_C##cn( __op__, size.width ); \
- } \
- \
- ICV_SUM_EXIT_C##cn( s, sumtype_final ); \
- return CV_OK; \
-}
-
-
-#define ICV_DEF_SUM_HINT_FUNC_2D( name, flavor, cn, \
- __op__, arrtype, sumtype_final, sumtype, worktype, block_size )\
-IPCVAPI_IMPL(CvStatus, icv##name##_##flavor##_C##cn##R,( \
- const arrtype* src, int step, CvSize size, \
- sumtype_final* sum, CvHintAlgorithm /*hint*/ ), \
- (src, step, size, sum, cvAlgHintAccurate) ) \
-{ \
- ICV_SUM_ENTRY_C##cn( sumtype ); \
- size.width *= cn; \
- \
- for( ; size.height--; src += step ) \
- { \
- int x = 0; \
- ICV_SUM_CASE_C##cn( __op__, size.width ); \
- } \
- \
- ICV_SUM_EXIT_C##cn( s, sumtype_final ); \
- return CV_OK; \
-}
-
-
-#define ICV_DEF_SUM_NOHINT_BLOCK_FUNC_2D_COI( name, flavor, \
- __op__, arrtype, sumtype_final, sumtype, worktype, block_size )\
-static CvStatus CV_STDCALL icv##name##_##flavor##_CnCR( \
- const arrtype* src, int step, CvSize size, int cn, \
- int coi, sumtype_final* sum ) \
-{ \
- ICV_SUM_ENTRY_BLOCK_C1(sumtype,worktype,(block_size)*(cn)); \
- size.width *= cn; \
- src += coi - 1; \
- \
- for( ; size.height--; src += step ) \
- { \
- int x = 0; \
- while( x < size.width ) \
- { \
- int limit = MIN( remaining, size.width - x ); \
- remaining -= limit; \
- limit += x; \
- ICV_SUM_COI_CASE( __op__, limit, cn ); \
- if( remaining == 0 ) \
- { \
- ICV_SUM_UPDATE_C1( (block_size)*(cn) ); \
- } \
- } \
- } \
- \
- ICV_SUM_EXIT_BLOCK_C1( sumtype_final ); \
- return CV_OK; \
-}
-
-
-#define ICV_DEF_SUM_NOHINT_FUNC_2D_COI( name, flavor, \
- __op__, arrtype, sumtype_final, sumtype, worktype, block_size )\
-static CvStatus CV_STDCALL icv##name##_##flavor##_CnCR( \
- const arrtype* src, int step, CvSize size, int cn, \
- int coi, sumtype_final* sum ) \
-{ \
- ICV_SUM_ENTRY_C1( sumtype ); \
- size.width *= cn; \
- src += coi - 1; \
- \
- for( ; size.height--; src += step ) \
- { \
- int x = 0; \
- ICV_SUM_COI_CASE( __op__, size.width, cn ); \
- } \
- \
- ICV_SUM_EXIT_C1( s, sumtype_final ); \
- return CV_OK; \
-}
-
-
-#define ICV_DEF_SUM_ALL( name, flavor, __op__, arrtype, sumtype_final, sumtype, \
- worktype, hintp_type, nohint_type, block_size ) \
- ICV_DEF_SUM_##hintp_type##_FUNC_2D( name, flavor, 1, __op__, arrtype, \
- sumtype_final, sumtype, worktype, block_size ) \
- ICV_DEF_SUM_##hintp_type##_FUNC_2D( name, flavor, 2, __op__, arrtype, \
- sumtype_final, sumtype, worktype, block_size ) \
- ICV_DEF_SUM_##hintp_type##_FUNC_2D( name, flavor, 3, __op__, arrtype, \
- sumtype_final, sumtype, worktype, block_size ) \
- ICV_DEF_SUM_##hintp_type##_FUNC_2D( name, flavor, 4, __op__, arrtype, \
- sumtype_final, sumtype, worktype, block_size ) \
- ICV_DEF_SUM_##nohint_type##_FUNC_2D_COI( name, flavor, __op__, arrtype, \
- sumtype_final, sumtype, worktype, block_size )
-
-ICV_DEF_SUM_ALL( Sum, 8u, CV_NOP, uchar, double, int64, unsigned,
- NOHINT_BLOCK, NOHINT_BLOCK, 1 << 24 )
-ICV_DEF_SUM_ALL( Sum, 16u, CV_NOP, ushort, double, int64, unsigned,
- NOHINT_BLOCK, NOHINT_BLOCK, 1 << 16 )
-ICV_DEF_SUM_ALL( Sum, 16s, CV_NOP, short, double, int64, int,
- NOHINT_BLOCK, NOHINT_BLOCK, 1 << 16 )
-ICV_DEF_SUM_ALL( Sum, 32s, CV_NOP, int, double, double, double, NOHINT, NOHINT, 0 )
-ICV_DEF_SUM_ALL( Sum, 32f, CV_NOP, float, double, double, double, HINT, NOHINT, 0 )
-ICV_DEF_SUM_ALL( Sum, 64f, CV_NOP, double, double, double, double, NOHINT, NOHINT, 0 )
-
-#define icvSum_8s_C1R 0
-#define icvSum_8s_C2R 0
-#define icvSum_8s_C3R 0
-#define icvSum_8s_C4R 0
-#define icvSum_8s_CnCR 0
-
-CV_DEF_INIT_BIG_FUNC_TAB_2D( Sum, R )
-CV_DEF_INIT_FUNC_TAB_2D( Sum, CnCR )
-
-CV_IMPL CvScalar
-cvSum( const CvArr* arr )
-{
- static CvBigFuncTable sum_tab;
- static CvFuncTable sumcoi_tab;
- static int inittab = 0;
-
- CvScalar sum = {{0,0,0,0}};
-
- CV_FUNCNAME("cvSum");
-
- __BEGIN__;
-
- int type, coi = 0;
- int mat_step;
- CvSize size;
- CvMat stub, *mat = (CvMat*)arr;
-
- if( !inittab )
- {
- icvInitSumRTable( &sum_tab );
- icvInitSumCnCRTable( &sumcoi_tab );
- inittab = 1;
- }
-
- if( !CV_IS_MAT(mat) )
- {
- if( CV_IS_MATND(mat) )
- {
- void* matnd = (void*)mat;
- CvMatND nstub;
- CvNArrayIterator iterator;
- int pass_hint;
-
- CV_CALL( cvInitNArrayIterator( 1, &matnd, 0, &nstub, &iterator ));
-
- type = CV_MAT_TYPE(iterator.hdr[0]->type);
- if( CV_MAT_CN(type) > 4 )
- CV_ERROR( CV_StsOutOfRange, "The input array must have at most 4 channels" );
-
- pass_hint = CV_MAT_DEPTH(type) == CV_32F;
-
- if( !pass_hint )
- {
- CvFunc2D_1A1P func = (CvFunc2D_1A1P)(sum_tab.fn_2d[type]);
- if( !func )
- CV_ERROR( CV_StsUnsupportedFormat, "" );
-
- do
- {
- CvScalar temp = {{0,0,0,0}};
- IPPI_CALL( func( iterator.ptr[0], CV_STUB_STEP,
- iterator.size, temp.val ));
- sum.val[0] += temp.val[0];
- sum.val[1] += temp.val[1];
- sum.val[2] += temp.val[2];
- sum.val[3] += temp.val[3];
- }
- while( cvNextNArraySlice( &iterator ));
- }
- else
- {
- CvFunc2D_1A1P1I func = (CvFunc2D_1A1P1I)(sum_tab.fn_2d[type]);
- if( !func )
- CV_ERROR( CV_StsUnsupportedFormat, "" );
-
- do
- {
- CvScalar temp = {{0,0,0,0}};
- IPPI_CALL( func( iterator.ptr[0], CV_STUB_STEP,
- iterator.size, temp.val, cvAlgHintAccurate ));
- sum.val[0] += temp.val[0];
- sum.val[1] += temp.val[1];
- sum.val[2] += temp.val[2];
- sum.val[3] += temp.val[3];
- }
- while( cvNextNArraySlice( &iterator ));
- }
- EXIT;
- }
- else
- CV_CALL( mat = cvGetMat( mat, &stub, &coi ));
- }
-
- type = CV_MAT_TYPE(mat->type);
- size = cvGetMatSize( mat );
-
- mat_step = mat->step;
-
- if( CV_IS_MAT_CONT( mat->type ))
- {
- size.width *= size.height;
-
- if( size.width <= CV_MAX_INLINE_MAT_OP_SIZE )
- {
- if( type == CV_32FC1 )
- {
- float* data = mat->data.fl;
-
- do
- {
- sum.val[0] += data[size.width - 1];
- }
- while( --size.width );
-
- EXIT;
- }
-
- if( type == CV_64FC1 )
- {
- double* data = mat->data.db;
-
- do
- {
- sum.val[0] += data[size.width - 1];
- }
- while( --size.width );
-
- EXIT;
- }
- }
- size.height = 1;
- mat_step = CV_STUB_STEP;
- }
-
- if( CV_MAT_CN(type) == 1 || coi == 0 )
- {
- int pass_hint = CV_MAT_DEPTH(type) == CV_32F;
-
- if( CV_MAT_CN(type) > 4 )
- CV_ERROR( CV_StsOutOfRange, "The input array must have at most 4 channels" );
-
- if( !pass_hint )
- {
- CvFunc2D_1A1P func = (CvFunc2D_1A1P)(sum_tab.fn_2d[type]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, size, sum.val ));
- }
- else
- {
- CvFunc2D_1A1P1I func = (CvFunc2D_1A1P1I)(sum_tab.fn_2d[type]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, size, sum.val, cvAlgHintAccurate ));
- }
- }
- else
- {
- CvFunc2DnC_1A1P func = (CvFunc2DnC_1A1P)(sumcoi_tab.fn_2d[CV_MAT_DEPTH(type)]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, size,
- CV_MAT_CN(type), coi, sum.val ));
- }
-
- __END__;
-
- return sum;
-}
-
-
-#define ICV_DEF_NONZERO_ALL( flavor, __op__, arrtype ) \
- ICV_DEF_SUM_NOHINT_FUNC_2D( CountNonZero, flavor, 1, __op__, \
- arrtype, int, int, int, 0 ) \
- ICV_DEF_SUM_NOHINT_FUNC_2D_COI( CountNonZero, flavor, __op__, \
- arrtype, int, int, int, 0 )
-
-#undef CV_NONZERO_DBL
-#define CV_NONZERO_DBL(x) (((x) & CV_BIG_INT(0x7fffffffffffffff)) != 0)
-
-ICV_DEF_NONZERO_ALL( 8u, CV_NONZERO, uchar )
-ICV_DEF_NONZERO_ALL( 16s, CV_NONZERO, ushort )
-ICV_DEF_NONZERO_ALL( 32s, CV_NONZERO, int )
-ICV_DEF_NONZERO_ALL( 32f, CV_NONZERO_FLT, int )
-ICV_DEF_NONZERO_ALL( 64f, CV_NONZERO_DBL, int64 )
-
-#define icvCountNonZero_8s_C1R icvCountNonZero_8u_C1R
-#define icvCountNonZero_8s_CnCR icvCountNonZero_8u_CnCR
-#define icvCountNonZero_16u_C1R icvCountNonZero_16s_C1R
-#define icvCountNonZero_16u_CnCR icvCountNonZero_16s_CnCR
-
-CV_DEF_INIT_FUNC_TAB_2D( CountNonZero, C1R )
-CV_DEF_INIT_FUNC_TAB_2D( CountNonZero, CnCR )
-
-CV_IMPL int
-cvCountNonZero( const CvArr* arr )
-{
- static CvFuncTable nz_tab;
- static CvFuncTable nzcoi_tab;
- static int inittab = 0;
-
- int count = 0;
-
- CV_FUNCNAME("cvCountNonZero");
-
- __BEGIN__;
-
- int type, coi = 0;
- int mat_step;
- CvSize size;
- CvMat stub, *mat = (CvMat*)arr;
-
- if( !inittab )
- {
- icvInitCountNonZeroC1RTable( &nz_tab );
- icvInitCountNonZeroCnCRTable( &nzcoi_tab );
- inittab = 1;
- }
-
- if( !CV_IS_MAT(mat) )
- {
- if( CV_IS_MATND(mat) )
- {
- void* matnd = (void*)arr;
- CvMatND nstub;
- CvNArrayIterator iterator;
- CvFunc2D_1A1P func;
-
- CV_CALL( cvInitNArrayIterator( 1, &matnd, 0, &nstub, &iterator ));
-
- type = CV_MAT_TYPE(iterator.hdr[0]->type);
-
- if( CV_MAT_CN(type) != 1 )
- CV_ERROR( CV_BadNumChannels,
- "Only single-channel array are supported here" );
-
- func = (CvFunc2D_1A1P)(nz_tab.fn_2d[CV_MAT_DEPTH(type)]);
- if( !func )
- CV_ERROR( CV_StsUnsupportedFormat, "" );
-
- do
- {
- int temp;
- IPPI_CALL( func( iterator.ptr[0], CV_STUB_STEP,
- iterator.size, &temp ));
- count += temp;
- }
- while( cvNextNArraySlice( &iterator ));
- EXIT;
- }
- else
- CV_CALL( mat = cvGetMat( mat, &stub, &coi ));
- }
-
- type = CV_MAT_TYPE(mat->type);
- size = cvGetMatSize( mat );
-
- mat_step = mat->step;
-
- if( CV_IS_MAT_CONT( mat->type ))
- {
- size.width *= size.height;
- size.height = 1;
- mat_step = CV_STUB_STEP;
- }
-
- if( CV_MAT_CN(type) == 1 || coi == 0 )
- {
- CvFunc2D_1A1P func = (CvFunc2D_1A1P)(nz_tab.fn_2d[CV_MAT_DEPTH(type)]);
-
- if( CV_MAT_CN(type) != 1 )
- CV_ERROR( CV_BadNumChannels,
- "The function can handle only a single channel at a time (use COI)");
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, size, &count ));
- }
- else
- {
- CvFunc2DnC_1A1P func = (CvFunc2DnC_1A1P)(nzcoi_tab.fn_2d[CV_MAT_DEPTH(type)]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, size, CV_MAT_CN(type), coi, &count ));
- }
-
- __END__;
-
- return count;
-}
-
-
-/****************************************************************************************\
-* Reduce Matrix to Vector *
-\****************************************************************************************/
-
-#define ICV_ACC_ROWS_FUNC( name, flavor, arrtype, acctype, \
- __op__, load_macro ) \
-static CvStatus CV_STDCALL \
-icv##name##Rows_##flavor##_C1R( const arrtype* src, int srcstep,\
- acctype* dst, CvSize size ) \
-{ \
- int i, width = size.width; \
- srcstep /= sizeof(src[0]); \
- \
- for( i = 0; i < width; i++ ) \
- dst[i] = load_macro(src[i]); \
- \
- for( ; --size.height; ) \
- { \
- src += srcstep; \
- for( i = 0; i <= width - 4; i += 4 ) \
- { \
- acctype s0 = load_macro(src[i]); \
- acctype s1 = load_macro(src[i+1]); \
- acctype a0 = dst[i], a1 = dst[i+1]; \
- a0 = (acctype)__op__(a0,s0); a1 = (acctype)__op__(a1,s1); \
- dst[i] = a0; dst[i+1] = a1; \
- \
- s0 = load_macro(src[i+2]); \
- s1 = load_macro(src[i+3]); \
- a0 = dst[i+2]; a1 = dst[i+3]; \
- a0 = (acctype)__op__(a0,s0); a1 = (acctype)__op__(a1,s1); \
- dst[i+2] = a0; dst[i+3] = a1; \
- } \
- \
- for( ; i < width; i++ ) \
- { \
- acctype s0 = load_macro(src[i]), a0 = dst[i]; \
- a0 = (acctype)__op__(a0,s0); \
- dst[i] = a0; \
- } \
- } \
- \
- return CV_OK; \
-}
-
-
-#define ICV_ACC_COLS_FUNC_C1( name, flavor, arrtype, worktype, acctype, __op__ )\
-static CvStatus CV_STDCALL \
-icv##name##Cols_##flavor##_C1R( const arrtype* src, int srcstep, \
- acctype* dst, int dststep, CvSize size )\
-{ \
- int i, width = size.width; \
- srcstep /= sizeof(src[0]); \
- dststep /= sizeof(dst[0]); \
- \
- for( ; size.height--; src += srcstep, dst += dststep ) \
- { \
- if( width == 1 ) \
- dst[0] = (acctype)src[0]; \
- else \
- { \
- worktype a0 = src[0], a1 = src[1]; \
- for( i = 2; i <= width - 4; i += 4 ) \
- { \
- worktype s0 = src[i], s1 = src[i+1]; \
- a0 = __op__(a0, s0); \
- a1 = __op__(a1, s1); \
- s0 = src[i+2]; s1 = src[i+3]; \
- a0 = __op__(a0, s0); \
- a1 = __op__(a1, s1); \
- } \
- \
- for( ; i < width; i++ ) \
- { \
- worktype s0 = src[i]; \
- a0 = __op__(a0, s0); \
- } \
- a0 = __op__(a0, a1); \
- dst[0] = (acctype)a0; \
- } \
- } \
- \
- return CV_OK; \
-}
-
-
-#define ICV_ACC_COLS_FUNC_C3( name, flavor, arrtype, worktype, acctype, __op__ ) \
-static CvStatus CV_STDCALL \
-icv##name##Cols_##flavor##_C3R( const arrtype* src, int srcstep, \
- acctype* dst, int dststep, CvSize size )\
-{ \
- int i, width = size.width*3; \
- srcstep /= sizeof(src[0]); \
- dststep /= sizeof(dst[0]); \
- \
- for( ; size.height--; src += srcstep, dst += dststep ) \
- { \
- worktype a0 = src[0], a1 = src[1], a2 = src[2]; \
- for( i = 3; i < width; i += 3 ) \
- { \
- worktype s0 = src[i], s1 = src[i+1], s2 = src[i+2]; \
- a0 = __op__(a0, s0); \
- a1 = __op__(a1, s1); \
- a2 = __op__(a2, s2); \
- } \
- \
- dst[0] = (acctype)a0; \
- dst[1] = (acctype)a1; \
- dst[2] = (acctype)a2; \
- } \
- \
- return CV_OK; \
-}
-
-
-#define ICV_ACC_COLS_FUNC_C4( name, flavor, arrtype, worktype, acctype, __op__ ) \
-static CvStatus CV_STDCALL \
-icv##name##Cols_##flavor##_C4R( const arrtype* src, int srcstep, \
- acctype* dst, int dststep, CvSize size )\
-{ \
- int i, width = size.width*4; \
- srcstep /= sizeof(src[0]); \
- dststep /= sizeof(dst[0]); \
- \
- for( ; size.height--; src += srcstep, dst += dststep ) \
- { \
- worktype a0 = src[0], a1 = src[1], a2 = src[2], a3 = src[3]; \
- for( i = 4; i < width; i += 4 ) \
- { \
- worktype s0 = src[i], s1 = src[i+1]; \
- a0 = __op__(a0, s0); \
- a1 = __op__(a1, s1); \
- s0 = src[i+2]; s1 = src[i+3]; \
- a2 = __op__(a2, s0); \
- a3 = __op__(a3, s1); \
- } \
- \
- dst[0] = (acctype)a0; \
- dst[1] = (acctype)a1; \
- dst[2] = (acctype)a2; \
- dst[3] = (acctype)a3; \
- } \
- \
- return CV_OK; \
-}
-
-
-ICV_ACC_ROWS_FUNC( Sum, 8u32s, uchar, int, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 8u32f, uchar, float, CV_ADD, CV_8TO32F )
-ICV_ACC_ROWS_FUNC( Sum, 16u32f, ushort, float, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 16u64f, ushort, double, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 16s32f, short, float, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 16s64f, short, double, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 32f, float, float, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 32f64f, float, double, CV_ADD, CV_NOP )
-ICV_ACC_ROWS_FUNC( Sum, 64f, double, double, CV_ADD, CV_NOP )
-
-ICV_ACC_ROWS_FUNC( Max, 8u, uchar, uchar, CV_MAX_8U, CV_NOP )
-ICV_ACC_ROWS_FUNC( Max, 32f, float, float, MAX, CV_NOP )
-ICV_ACC_ROWS_FUNC( Max, 64f, double, double, MAX, CV_NOP )
-
-ICV_ACC_ROWS_FUNC( Min, 8u, uchar, uchar, CV_MIN_8U, CV_NOP )
-ICV_ACC_ROWS_FUNC( Min, 32f, float, float, MIN, CV_NOP )
-ICV_ACC_ROWS_FUNC( Min, 64f, double, double, MIN, CV_NOP )
-
-ICV_ACC_COLS_FUNC_C1( Sum, 8u32s, uchar, int, int, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 8u32f, uchar, int, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 16u32f, ushort, float, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 16u64f, ushort, double, double, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 16s32f, short, float, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 16s64f, short, double, double, CV_ADD )
-
-ICV_ACC_COLS_FUNC_C1( Sum, 32f, float, float, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 32f64f, float, double, double, CV_ADD )
-ICV_ACC_COLS_FUNC_C1( Sum, 64f, double, double, double, CV_ADD )
-ICV_ACC_COLS_FUNC_C3( Sum, 8u32s, uchar, int, int, CV_ADD )
-ICV_ACC_COLS_FUNC_C3( Sum, 8u32f, uchar, int, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C3( Sum, 32f, float, float, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C3( Sum, 64f, double, double, double, CV_ADD )
-ICV_ACC_COLS_FUNC_C4( Sum, 8u32s, uchar, int, int, CV_ADD )
-ICV_ACC_COLS_FUNC_C4( Sum, 8u32f, uchar, int, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C4( Sum, 32f, float, float, float, CV_ADD )
-ICV_ACC_COLS_FUNC_C4( Sum, 64f, double, double, double, CV_ADD )
-
-ICV_ACC_COLS_FUNC_C1( Max, 8u, uchar, int, uchar, CV_MAX_8U )
-ICV_ACC_COLS_FUNC_C1( Max, 32f, float, float, float, MAX )
-ICV_ACC_COLS_FUNC_C1( Max, 64f, double, double, double, MAX )
-
-ICV_ACC_COLS_FUNC_C1( Min, 8u, uchar, int, uchar, CV_MIN_8U )
-ICV_ACC_COLS_FUNC_C1( Min, 32f, float, float, float, MIN )
-ICV_ACC_COLS_FUNC_C1( Min, 64f, double, double, double, MIN )
-
-typedef CvStatus (CV_STDCALL * CvReduceToRowFunc)
- ( const void* src, int srcstep, void* dst, CvSize size );
-
-typedef CvStatus (CV_STDCALL * CvReduceToColFunc)
- ( const void* src, int srcstep, void* dst, int dststep, CvSize size );
-
-
-CV_IMPL void
-cvReduce( const CvArr* srcarr, CvArr* dstarr, int dim, int op )
-{
- CvMat* temp = 0;
-
- CV_FUNCNAME( "cvReduce" );
-
- __BEGIN__;
-
- CvMat sstub, *src = (CvMat*)srcarr;
- CvMat dstub, *dst = (CvMat*)dstarr, *dst0;
- int sdepth, ddepth, cn, op0 = op;
- CvSize size;
-
- if( !CV_IS_MAT(src) )
- CV_CALL( src = cvGetMat( src, &sstub ));
-
- if( !CV_IS_MAT(dst) )
- CV_CALL( dst = cvGetMat( dst, &dstub ));
-
- if( !CV_ARE_CNS_EQ(src, dst) )
- CV_ERROR( CV_StsUnmatchedFormats, "Input and output arrays must have the same number of channels" );
-
- sdepth = CV_MAT_DEPTH(src->type);
- ddepth = CV_MAT_DEPTH(dst->type);
- cn = CV_MAT_CN(src->type);
- dst0 = dst;
-
- size = cvGetMatSize(src);
-
- if( dim < 0 )
- dim = src->rows > dst->rows ? 0 : src->cols > dst->cols ? 1 : dst->cols == 1;
-
- if( dim > 1 )
- CV_ERROR( CV_StsOutOfRange, "The reduced dimensionality index is out of range" );
-
- if( dim == 0 && (dst->cols != src->cols || dst->rows != 1) ||
- dim == 1 && (dst->rows != src->rows || dst->cols != 1) )
- CV_ERROR( CV_StsBadSize, "The output array size is incorrect" );
-
- if( op == CV_REDUCE_AVG )
- {
- int ttype = sdepth == CV_8U ? CV_MAKETYPE(CV_32S,cn) : dst->type;
- if( ttype != dst->type )
- CV_CALL( dst = temp = cvCreateMat( dst->rows, dst->cols, ttype ));
- op = CV_REDUCE_SUM;
- ddepth = CV_MAT_DEPTH(ttype);
- }
-
- if( op != CV_REDUCE_SUM && op != CV_REDUCE_MAX && op != CV_REDUCE_MIN )
- CV_ERROR( CV_StsBadArg, "Unknown reduce operation index, must be one of CV_REDUCE_*" );
-
- if( dim == 0 )
- {
- CvReduceToRowFunc rfunc =
- op == CV_REDUCE_SUM ?
- (sdepth == CV_8U && ddepth == CV_32S ? (CvReduceToRowFunc)icvSumRows_8u32s_C1R :
- sdepth == CV_8U && ddepth == CV_32F ? (CvReduceToRowFunc)icvSumRows_8u32f_C1R :
- sdepth == CV_16U && ddepth == CV_32F ? (CvReduceToRowFunc)icvSumRows_16u32f_C1R :
- sdepth == CV_16U && ddepth == CV_64F ? (CvReduceToRowFunc)icvSumRows_16u64f_C1R :
- sdepth == CV_16S && ddepth == CV_32F ? (CvReduceToRowFunc)icvSumRows_16s32f_C1R :
- sdepth == CV_16S && ddepth == CV_64F ? (CvReduceToRowFunc)icvSumRows_16s64f_C1R :
- sdepth == CV_32F && ddepth == CV_32F ? (CvReduceToRowFunc)icvSumRows_32f_C1R :
- sdepth == CV_32F && ddepth == CV_64F ? (CvReduceToRowFunc)icvSumRows_32f64f_C1R :
- sdepth == CV_64F && ddepth == CV_64F ? (CvReduceToRowFunc)icvSumRows_64f_C1R : 0) :
- op == CV_REDUCE_MAX ?
- (sdepth == CV_8U && ddepth == CV_8U ? (CvReduceToRowFunc)icvMaxRows_8u_C1R :
- sdepth == CV_32F && ddepth == CV_32F ? (CvReduceToRowFunc)icvMaxRows_32f_C1R :
- sdepth == CV_64F && ddepth == CV_64F ? (CvReduceToRowFunc)icvMaxRows_64f_C1R : 0) :
-
- (sdepth == CV_8U && ddepth == CV_8U ? (CvReduceToRowFunc)icvMinRows_8u_C1R :
- sdepth == CV_32F && ddepth == CV_32F ? (CvReduceToRowFunc)icvMinRows_32f_C1R :
- sdepth == CV_64F && ddepth == CV_64F ? (CvReduceToRowFunc)icvMinRows_64f_C1R : 0);
-
- if( !rfunc )
- CV_ERROR( CV_StsUnsupportedFormat,
- "Unsupported combination of input and output array formats" );
-
- size.width *= cn;
- IPPI_CALL( rfunc( src->data.ptr, src->step ? src->step : CV_STUB_STEP,
- dst->data.ptr, size ));
- }
- else
- {
- CvReduceToColFunc cfunc =
- op == CV_REDUCE_SUM ?
- (sdepth == CV_8U && ddepth == CV_32S ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_8u32s_C1R :
- cn == 3 ? icvSumCols_8u32s_C3R :
- cn == 4 ? icvSumCols_8u32s_C4R : 0) :
- sdepth == CV_8U && ddepth == CV_32F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_8u32f_C1R :
- cn == 3 ? icvSumCols_8u32f_C3R :
- cn == 4 ? icvSumCols_8u32f_C4R : 0) :
- sdepth == CV_16U && ddepth == CV_32F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_16u32f_C1R : 0) :
- sdepth == CV_16U && ddepth == CV_64F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_16u64f_C1R : 0) :
- sdepth == CV_16S && ddepth == CV_32F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_16s32f_C1R : 0) :
- sdepth == CV_16S && ddepth == CV_64F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_16s64f_C1R : 0) :
- sdepth == CV_32F && ddepth == CV_32F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_32f_C1R :
- cn == 3 ? icvSumCols_32f_C3R :
- cn == 4 ? icvSumCols_32f_C4R : 0) :
- sdepth == CV_32F && ddepth == CV_64F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_32f64f_C1R : 0) :
- sdepth == CV_64F && ddepth == CV_64F ?
- (CvReduceToColFunc)(cn == 1 ? icvSumCols_64f_C1R :
- cn == 3 ? icvSumCols_64f_C3R :
- cn == 4 ? icvSumCols_64f_C4R : 0) : 0) :
- op == CV_REDUCE_MAX && cn == 1 ?
- (sdepth == CV_8U && ddepth == CV_8U ? (CvReduceToColFunc)icvMaxCols_8u_C1R :
- sdepth == CV_32F && ddepth == CV_32F ? (CvReduceToColFunc)icvMaxCols_32f_C1R :
- sdepth == CV_64F && ddepth == CV_64F ? (CvReduceToColFunc)icvMaxCols_64f_C1R : 0) :
- op == CV_REDUCE_MIN && cn == 1 ?
- (sdepth == CV_8U && ddepth == CV_8U ? (CvReduceToColFunc)icvMinCols_8u_C1R :
- sdepth == CV_32F && ddepth == CV_32F ? (CvReduceToColFunc)icvMinCols_32f_C1R :
- sdepth == CV_64F && ddepth == CV_64F ? (CvReduceToColFunc)icvMinCols_64f_C1R : 0) : 0;
-
- if( !cfunc )
- CV_ERROR( CV_StsUnsupportedFormat,
- "Unsupported combination of input and output array formats" );
-
- IPPI_CALL( cfunc( src->data.ptr, src->step ? src->step : CV_STUB_STEP,
- dst->data.ptr, dst->step ? dst->step : CV_STUB_STEP, size ));
- }
-
- if( op0 == CV_REDUCE_AVG )
- cvScale( dst, dst0, 1./(dim == 0 ? src->rows : src->cols) );
-
- __END__;
-
- if( temp )
- cvReleaseMat( &temp );
-}
-
-/* End of file. */
projects / opencv / blobdiff