+++ /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"
-#include <float.h>
-
-/****************************************************************************************\
-* Mean value over the region *
-\****************************************************************************************/
-
-#define ICV_MEAN_CASE_C1( len ) \
- for( ; x <= (len) - 2; x += 2 ) \
- { \
- if( mask[x] ) \
- s0 += src[x], pix++; \
- if( mask[x+1] ) \
- s0 += src[x+1], pix++; \
- } \
- \
- for( ; x < (len); x++ ) \
- if( mask[x] ) \
- s0 += src[x], pix++
-
-
-#define ICV_MEAN_CASE_C2( len ) \
- for( ; x < (len); x++ ) \
- if( mask[x] ) \
- { \
- s0 += src[x*2]; \
- s1 += src[x*2+1]; \
- pix++; \
- }
-
-
-#define ICV_MEAN_CASE_C3( len ) \
- for( ; x < (len); x++ ) \
- if( mask[x] ) \
- { \
- s0 += src[x*3]; \
- s1 += src[x*3+1]; \
- s2 += src[x*3+2]; \
- pix++; \
- }
-
-
-#define ICV_MEAN_CASE_C4( len ) \
- for( ; x < (len); x++ ) \
- if( mask[x] ) \
- { \
- s0 += src[x*4]; \
- s1 += src[x*4+1]; \
- s2 += src[x*4+2]; \
- s3 += src[x*4+3]; \
- pix++; \
- }
-
-
-#define ICV_MEAN_COI_CASE( len, cn ) \
- for( ; x <= (len) - 2; x += 2 ) \
- { \
- if( mask[x] ) \
- s0 += src[x*(cn)], pix++; \
- if( mask[x+1] ) \
- s0+=src[(x+1)*(cn)], pix++; \
- } \
- \
- for( ; x < (len); x++ ) \
- if( mask[x] ) \
- s0 += src[x*(cn)], pix++;
-
-
-////////////////////////////////////// entry macros //////////////////////////////////////
-
-#define ICV_MEAN_ENTRY_COMMON() \
- int pix = 0; \
- step /= sizeof(src[0])
-
-#define ICV_MEAN_ENTRY_C1( sumtype ) \
- sumtype s0 = 0; \
- ICV_MEAN_ENTRY_COMMON()
-
-#define ICV_MEAN_ENTRY_C2( sumtype ) \
- sumtype s0 = 0, s1 = 0; \
- ICV_MEAN_ENTRY_COMMON()
-
-#define ICV_MEAN_ENTRY_C3( sumtype ) \
- sumtype s0 = 0, s1 = 0, s2 = 0; \
- ICV_MEAN_ENTRY_COMMON()
-
-#define ICV_MEAN_ENTRY_C4( sumtype ) \
- sumtype s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
- ICV_MEAN_ENTRY_COMMON()
-
-
-#define ICV_MEAN_ENTRY_BLOCK_COMMON( block_size ) \
- int remaining = block_size; \
- ICV_MEAN_ENTRY_COMMON()
-
-#define ICV_MEAN_ENTRY_BLOCK_C1( sumtype, worktype, block_size )\
- sumtype sum0 = 0; \
- worktype s0 = 0; \
- ICV_MEAN_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_MEAN_ENTRY_BLOCK_C2( sumtype, worktype, block_size )\
- sumtype sum0 = 0, sum1 = 0; \
- worktype s0 = 0, s1 = 0; \
- ICV_MEAN_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_MEAN_ENTRY_BLOCK_C3( sumtype, worktype, block_size )\
- sumtype sum0 = 0, sum1 = 0, sum2 = 0; \
- worktype s0 = 0, s1 = 0, s2 = 0; \
- ICV_MEAN_ENTRY_BLOCK_COMMON( block_size )
-
-#define ICV_MEAN_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_MEAN_ENTRY_BLOCK_COMMON( block_size )
-
-
-/////////////////////////////////////// exit macros //////////////////////////////////////
-
-#define ICV_MEAN_EXIT_COMMON() \
- double scale = pix ? 1./pix : 0
-
-#define ICV_MEAN_EXIT_C1( tmp ) \
- ICV_MEAN_EXIT_COMMON(); \
- mean[0] = scale*(double)tmp##0
-
-#define ICV_MEAN_EXIT_C2( tmp ) \
- ICV_MEAN_EXIT_COMMON(); \
- double t0 = scale*(double)tmp##0; \
- double t1 = scale*(double)tmp##1; \
- mean[0] = t0; \
- mean[1] = t1
-
-#define ICV_MEAN_EXIT_C3( tmp ) \
- ICV_MEAN_EXIT_COMMON(); \
- double t0 = scale*(double)tmp##0; \
- double t1 = scale*(double)tmp##1; \
- double t2 = scale*(double)tmp##2; \
- mean[0] = t0; \
- mean[1] = t1; \
- mean[2] = t2
-
-#define ICV_MEAN_EXIT_C4( tmp ) \
- ICV_MEAN_EXIT_COMMON(); \
- double t0 = scale*(double)tmp##0; \
- double t1 = scale*(double)tmp##1; \
- mean[0] = t0; \
- mean[1] = t1; \
- t0 = scale*(double)tmp##2; \
- t1 = scale*(double)tmp##3; \
- mean[2] = t0; \
- mean[3] = t1
-
-#define ICV_MEAN_EXIT_BLOCK_C1() \
- sum0 += s0; \
- ICV_MEAN_EXIT_C1( sum )
-
-#define ICV_MEAN_EXIT_BLOCK_C2() \
- sum0 += s0; sum1 += s1; \
- ICV_MEAN_EXIT_C2( sum )
-
-#define ICV_MEAN_EXIT_BLOCK_C3() \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; \
- ICV_MEAN_EXIT_C3( sum )
-
-#define ICV_MEAN_EXIT_BLOCK_C4() \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; sum3 += s3; \
- ICV_MEAN_EXIT_C4( sum )
-
-////////////////////////////////////// update macros /////////////////////////////////////
-
-#define ICV_MEAN_UPDATE_COMMON( block_size )\
- remaining = block_size
-
-#define ICV_MEAN_UPDATE_C1( block_size ) \
- ICV_MEAN_UPDATE_COMMON( block_size ); \
- sum0 += s0; \
- s0 = 0
-
-#define ICV_MEAN_UPDATE_C2( block_size ) \
- ICV_MEAN_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; \
- s0 = s1 = 0
-
-#define ICV_MEAN_UPDATE_C3( block_size ) \
- ICV_MEAN_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; sum2 += s2; \
- s0 = s1 = s2 = 0
-
-#define ICV_MEAN_UPDATE_C4( block_size ) \
- ICV_MEAN_UPDATE_COMMON( block_size ); \
- sum0 += s0; sum1 += s1; \
- sum2 += s2; sum3 += s3; \
- s0 = s1 = s2 = s3 = 0
-
-
-#define ICV_IMPL_MEAN_BLOCK_FUNC_2D( flavor, cn, \
- arrtype, sumtype, worktype, block_size ) \
-IPCVAPI_IMPL( CvStatus, icvMean_##flavor##_C##cn##MR, \
- ( const arrtype* src, int step, \
- const uchar* mask, int maskstep, \
- CvSize size, double* mean ), \
- (src, step, mask, maskstep, size, mean)) \
-{ \
- ICV_MEAN_ENTRY_BLOCK_C##cn( sumtype, worktype, block_size );\
- \
- for( ; size.height--; src += step, mask += maskstep ) \
- { \
- int x = 0; \
- while( x < size.width ) \
- { \
- int limit = MIN( remaining, size.width - x ); \
- remaining -= limit; \
- limit += x; \
- ICV_MEAN_CASE_C##cn( limit ); \
- if( remaining == 0 ) \
- { \
- ICV_MEAN_UPDATE_C##cn( block_size ); \
- } \
- } \
- } \
- \
- { ICV_MEAN_EXIT_BLOCK_C##cn(); } \
- return CV_OK; \
-}
-
-
-#define ICV_IMPL_MEAN_FUNC_2D( flavor, cn, \
- arrtype, sumtype, worktype ) \
-IPCVAPI_IMPL( CvStatus, icvMean_##flavor##_C##cn##MR, \
- ( const arrtype* src, int step, \
- const uchar* mask, int maskstep, \
- CvSize size, double* mean), \
- (src, step, mask, maskstep, size, mean)) \
-{ \
- ICV_MEAN_ENTRY_C##cn( sumtype ); \
- \
- for( ; size.height--; src += step, mask += maskstep ) \
- { \
- int x = 0; \
- ICV_MEAN_CASE_C##cn( size.width ); \
- } \
- \
- { ICV_MEAN_EXIT_C##cn( s ); } \
- return CV_OK; \
-}
-
-
-#define ICV_IMPL_MEAN_BLOCK_FUNC_2D_COI( flavor, \
- arrtype, sumtype, worktype, block_size ) \
-static CvStatus CV_STDCALL \
-icvMean_##flavor##_CnCMR( const arrtype* src, int step, \
- const uchar* mask, int maskstep, \
- CvSize size, int cn, \
- int coi, double* mean ) \
-{ \
- ICV_MEAN_ENTRY_BLOCK_C1( sumtype, worktype, block_size ); \
- src += coi - 1; \
- \
- for( ; size.height--; src += step, mask += maskstep ) \
- { \
- int x = 0; \
- while( x < size.width ) \
- { \
- int limit = MIN( remaining, size.width - x ); \
- remaining -= limit; \
- limit += x; \
- ICV_MEAN_COI_CASE( limit, cn ); \
- if( remaining == 0 ) \
- { \
- ICV_MEAN_UPDATE_C1( block_size ); \
- } \
- } \
- } \
- \
- { ICV_MEAN_EXIT_BLOCK_C1(); } \
- return CV_OK; \
-}
-
-
-#define ICV_IMPL_MEAN_FUNC_2D_COI( flavor, \
- arrtype, sumtype, worktype ) \
-static CvStatus CV_STDCALL \
-icvMean_##flavor##_CnCMR( const arrtype* src, int step, \
- const uchar* mask, int maskstep, \
- CvSize size, int cn, \
- int coi, double* mean ) \
-{ \
- ICV_MEAN_ENTRY_C1( sumtype ); \
- src += coi - 1; \
- \
- for( ; size.height--; src += step, mask += maskstep ) \
- { \
- int x = 0; \
- ICV_MEAN_COI_CASE( size.width, cn ); \
- } \
- \
- { ICV_MEAN_EXIT_C1( s ); } \
- return CV_OK; \
-}
-
-
-#define ICV_IMPL_MEAN_BLOCK_ALL( flavor, arrtype, sumtype, \
- worktype, block_size ) \
- ICV_IMPL_MEAN_BLOCK_FUNC_2D( flavor, 1, arrtype, sumtype, \
- worktype, block_size ) \
- ICV_IMPL_MEAN_BLOCK_FUNC_2D( flavor, 2, arrtype, sumtype, \
- worktype, block_size ) \
- ICV_IMPL_MEAN_BLOCK_FUNC_2D( flavor, 3, arrtype, sumtype, \
- worktype, block_size ) \
- ICV_IMPL_MEAN_BLOCK_FUNC_2D( flavor, 4, arrtype, sumtype, \
- worktype, block_size ) \
- ICV_IMPL_MEAN_BLOCK_FUNC_2D_COI( flavor, arrtype, sumtype, \
- worktype, block_size )
-
-#define ICV_IMPL_MEAN_ALL( flavor, arrtype, sumtype, worktype ) \
- ICV_IMPL_MEAN_FUNC_2D( flavor, 1, arrtype, sumtype, worktype ) \
- ICV_IMPL_MEAN_FUNC_2D( flavor, 2, arrtype, sumtype, worktype ) \
- ICV_IMPL_MEAN_FUNC_2D( flavor, 3, arrtype, sumtype, worktype ) \
- ICV_IMPL_MEAN_FUNC_2D( flavor, 4, arrtype, sumtype, worktype ) \
- ICV_IMPL_MEAN_FUNC_2D_COI( flavor, arrtype, sumtype, worktype )
-
-ICV_IMPL_MEAN_BLOCK_ALL( 8u, uchar, int64, unsigned, 1 << 24 )
-ICV_IMPL_MEAN_BLOCK_ALL( 16u, ushort, int64, unsigned, 1 << 16 )
-ICV_IMPL_MEAN_BLOCK_ALL( 16s, short, int64, int, 1 << 16 )
-ICV_IMPL_MEAN_ALL( 32s, int, double, double )
-ICV_IMPL_MEAN_ALL( 32f, float, double, double )
-ICV_IMPL_MEAN_ALL( 64f, double, double, double )
-
-#define icvMean_8s_C1MR 0
-#define icvMean_8s_C2MR 0
-#define icvMean_8s_C3MR 0
-#define icvMean_8s_C4MR 0
-#define icvMean_8s_CnCMR 0
-
-CV_DEF_INIT_BIG_FUNC_TAB_2D( Mean, MR )
-CV_DEF_INIT_FUNC_TAB_2D( Mean, CnCMR )
-
-CV_IMPL CvScalar
-cvAvg( const void* img, const void* maskarr )
-{
- CvScalar mean = {{0,0,0,0}};
-
- static CvBigFuncTable mean_tab;
- static CvFuncTable meancoi_tab;
- static int inittab = 0;
-
- CV_FUNCNAME("cvAvg");
-
- __BEGIN__;
-
- CvSize size;
- double scale;
-
- if( !maskarr )
- {
- CV_CALL( mean = cvSum(img));
- size = cvGetSize( img );
- size.width *= size.height;
- scale = size.width ? 1./size.width : 0;
-
- mean.val[0] *= scale;
- mean.val[1] *= scale;
- mean.val[2] *= scale;
- mean.val[3] *= scale;
- }
- else
- {
- int type, coi = 0;
- int mat_step, mask_step;
-
- CvMat stub, maskstub, *mat = (CvMat*)img, *mask = (CvMat*)maskarr;
-
- if( !inittab )
- {
- icvInitMeanMRTable( &mean_tab );
- icvInitMeanCnCMRTable( &meancoi_tab );
- inittab = 1;
- }
-
- if( !CV_IS_MAT(mat) )
- CV_CALL( mat = cvGetMat( mat, &stub, &coi ));
-
- if( !CV_IS_MAT(mask) )
- CV_CALL( mask = cvGetMat( mask, &maskstub ));
-
- if( !CV_IS_MASK_ARR(mask) )
- CV_ERROR( CV_StsBadMask, "" );
-
- if( !CV_ARE_SIZES_EQ( mat, mask ) )
- CV_ERROR( CV_StsUnmatchedSizes, "" );
-
- type = CV_MAT_TYPE( mat->type );
- size = cvGetMatSize( mat );
-
- mat_step = mat->step;
- mask_step = mask->step;
-
- if( CV_IS_MAT_CONT( mat->type & mask->type ))
- {
- size.width *= size.height;
- size.height = 1;
- mat_step = mask_step = CV_STUB_STEP;
- }
-
- if( CV_MAT_CN(type) == 1 || coi == 0 )
- {
- CvFunc2D_2A1P func;
-
- if( CV_MAT_CN(type) > 4 )
- CV_ERROR( CV_StsOutOfRange, "The input array must have at most 4 channels unless COI is set" );
-
- func = (CvFunc2D_2A1P)(mean_tab.fn_2d[type]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, mask->data.ptr,
- mask_step, size, mean.val ));
- }
- else
- {
- CvFunc2DnC_2A1P func = (CvFunc2DnC_2A1P)(
- meancoi_tab.fn_2d[CV_MAT_DEPTH(type)]);
-
- if( !func )
- CV_ERROR( CV_StsBadArg, cvUnsupportedFormat );
-
- IPPI_CALL( func( mat->data.ptr, mat_step, mask->data.ptr,
- mask_step, size, CV_MAT_CN(type), coi, mean.val ));
- }
- }
-
- __END__;
-
- return mean;
-}
-
-/* End of file */
projects / opencv / blobdiff