/*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. */