+++ /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 "_cv.h"
-
-void
-icvCrossCorr( const CvArr* _img, const CvArr* _templ, CvArr* _corr, CvPoint anchor )
-{
- const double block_scale = 4.5;
- const int min_block_size = 256;
- CvMat* dft_img[CV_MAX_THREADS] = {0};
- CvMat* dft_templ = 0;
- void* buf[CV_MAX_THREADS] = {0};
- int k, num_threads = 0;
-
- CV_FUNCNAME( "icvCrossCorr" );
-
- __BEGIN__;
-
- CvMat istub, *img = (CvMat*)_img;
- CvMat tstub, *templ = (CvMat*)_templ;
- CvMat cstub, *corr = (CvMat*)_corr;
- CvSize dftsize, blocksize;
- int depth, templ_depth, corr_depth, max_depth = CV_32F,
- cn, templ_cn, corr_cn, buf_size = 0,
- tile_count_x, tile_count_y, tile_count;
-
- CV_CALL( img = cvGetMat( img, &istub ));
- CV_CALL( templ = cvGetMat( templ, &tstub ));
- CV_CALL( corr = cvGetMat( corr, &cstub ));
-
- if( CV_MAT_DEPTH( img->type ) != CV_8U &&
- CV_MAT_DEPTH( img->type ) != CV_16U &&
- CV_MAT_DEPTH( img->type ) != CV_32F )
- CV_ERROR( CV_StsUnsupportedFormat,
- "The function supports only 8u, 16u and 32f data types" );
-
- if( !CV_ARE_DEPTHS_EQ( img, templ ) && CV_MAT_DEPTH( templ->type ) != CV_32F )
- CV_ERROR( CV_StsUnsupportedFormat,
- "Template (kernel) must be of the same depth as the input image, or be 32f" );
-
- if( !CV_ARE_DEPTHS_EQ( img, corr ) && CV_MAT_DEPTH( corr->type ) != CV_32F &&
- CV_MAT_DEPTH( corr->type ) != CV_64F )
- CV_ERROR( CV_StsUnsupportedFormat,
- "The output image must have the same depth as the input image, or be 32f/64f" );
-
- if( (!CV_ARE_CNS_EQ( img, corr ) || CV_MAT_CN(templ->type) > 1) &&
- (CV_MAT_CN( corr->type ) > 1 || !CV_ARE_CNS_EQ( img, templ)) )
- CV_ERROR( CV_StsUnsupportedFormat,
- "The output must have the same number of channels as the input (when the template has 1 channel), "
- "or the output must have 1 channel when the input and the template have the same number of channels" );
-
- depth = CV_MAT_DEPTH(img->type);
- cn = CV_MAT_CN(img->type);
- templ_depth = CV_MAT_DEPTH(templ->type);
- templ_cn = CV_MAT_CN(templ->type);
- corr_depth = CV_MAT_DEPTH(corr->type);
- corr_cn = CV_MAT_CN(corr->type);
- max_depth = MAX( max_depth, templ_depth );
- max_depth = MAX( max_depth, depth );
- max_depth = MAX( max_depth, corr_depth );
- if( depth > CV_8U )
- max_depth = CV_64F;
-
- if( img->cols < templ->cols || img->rows < templ->rows )
- CV_ERROR( CV_StsUnmatchedSizes,
- "Such a combination of image and template/filter size is not supported" );
-
- if( corr->rows > img->rows + templ->rows - 1 ||
- corr->cols > img->cols + templ->cols - 1 )
- CV_ERROR( CV_StsUnmatchedSizes,
- "output image should not be greater than (W + w - 1)x(H + h - 1)" );
-
- blocksize.width = cvRound(templ->cols*block_scale);
- blocksize.width = MAX( blocksize.width, min_block_size - templ->cols + 1 );
- blocksize.width = MIN( blocksize.width, corr->cols );
- blocksize.height = cvRound(templ->rows*block_scale);
- blocksize.height = MAX( blocksize.height, min_block_size - templ->rows + 1 );
- blocksize.height = MIN( blocksize.height, corr->rows );
-
- dftsize.width = cvGetOptimalDFTSize(blocksize.width + templ->cols - 1);
- if( dftsize.width == 1 )
- dftsize.width = 2;
- dftsize.height = cvGetOptimalDFTSize(blocksize.height + templ->rows - 1);
- if( dftsize.width <= 0 || dftsize.height <= 0 )
- CV_ERROR( CV_StsOutOfRange, "the input arrays are too big" );
-
- // recompute block size
- blocksize.width = dftsize.width - templ->cols + 1;
- blocksize.width = MIN( blocksize.width, corr->cols );
- blocksize.height = dftsize.height - templ->rows + 1;
- blocksize.height = MIN( blocksize.height, corr->rows );
-
- CV_CALL( dft_templ = cvCreateMat( dftsize.height*templ_cn, dftsize.width, max_depth ));
-
- num_threads = cvGetNumThreads();
-
- for( k = 0; k < num_threads; k++ )
- CV_CALL( dft_img[k] = cvCreateMat( dftsize.height, dftsize.width, max_depth ));
-
- if( templ_cn > 1 && templ_depth != max_depth )
- buf_size = templ->cols*templ->rows*CV_ELEM_SIZE(templ_depth);
-
- if( cn > 1 && depth != max_depth )
- buf_size = MAX( buf_size, (blocksize.width + templ->cols - 1)*
- (blocksize.height + templ->rows - 1)*CV_ELEM_SIZE(depth));
-
- if( (corr_cn > 1 || cn > 1) && corr_depth != max_depth )
- buf_size = MAX( buf_size, blocksize.width*blocksize.height*CV_ELEM_SIZE(corr_depth));
-
- if( buf_size > 0 )
- {
- for( k = 0; k < num_threads; k++ )
- CV_CALL( buf[k] = cvAlloc(buf_size) );
- }
-
- // compute DFT of each template plane
- for( k = 0; k < templ_cn; k++ )
- {
- CvMat dstub, *src, *dst, temp;
- CvMat* planes[] = { 0, 0, 0, 0 };
- int yofs = k*dftsize.height;
-
- src = templ;
- dst = cvGetSubRect( dft_templ, &dstub, cvRect(0,yofs,templ->cols,templ->rows));
-
- if( templ_cn > 1 )
- {
- planes[k] = templ_depth == max_depth ? dst :
- cvInitMatHeader( &temp, templ->rows, templ->cols, templ_depth, buf[0] );
- cvSplit( templ, planes[0], planes[1], planes[2], planes[3] );
- src = planes[k];
- planes[k] = 0;
- }
-
- if( dst != src )
- cvConvert( src, dst );
-
- if( dft_templ->cols > templ->cols )
- {
- cvGetSubRect( dft_templ, dst, cvRect(templ->cols, yofs,
- dft_templ->cols - templ->cols, templ->rows) );
- cvZero( dst );
- }
- cvGetSubRect( dft_templ, dst, cvRect(0,yofs,dftsize.width,dftsize.height) );
- cvDFT( dst, dst, CV_DXT_FORWARD + CV_DXT_SCALE, templ->rows );
- }
-
- tile_count_x = (corr->cols + blocksize.width - 1)/blocksize.width;
- tile_count_y = (corr->rows + blocksize.height - 1)/blocksize.height;
- tile_count = tile_count_x*tile_count_y;
-
- {
-#ifdef _OPENMP
- #pragma omp parallel for num_threads(num_threads), schedule(dynamic)
-#endif
- // calculate correlation by blocks
- for( k = 0; k < tile_count; k++ )
- {
- int thread_idx = cvGetThreadNum();
- int x = (k%tile_count_x)*blocksize.width;
- int y = (k/tile_count_x)*blocksize.height;
- int i, yofs;
- CvMat sstub, dstub, *src, *dst, temp;
- CvMat* planes[] = { 0, 0, 0, 0 };
- CvMat* _dft_img = dft_img[thread_idx];
- void* _buf = buf[thread_idx];
- CvSize csz = { blocksize.width, blocksize.height }, isz;
- int x0 = x - anchor.x, y0 = y - anchor.y;
- int x1 = MAX( 0, x0 ), y1 = MAX( 0, y0 ), x2, y2;
- csz.width = MIN( csz.width, corr->cols - x );
- csz.height = MIN( csz.height, corr->rows - y );
- isz.width = csz.width + templ->cols - 1;
- isz.height = csz.height + templ->rows - 1;
- x2 = MIN( img->cols, x0 + isz.width );
- y2 = MIN( img->rows, y0 + isz.height );
-
- for( i = 0; i < cn; i++ )
- {
- CvMat dstub1, *dst1;
- yofs = i*dftsize.height;
-
- src = cvGetSubRect( img, &sstub, cvRect(x1,y1,x2-x1,y2-y1) );
- dst = cvGetSubRect( _dft_img, &dstub,
- cvRect(0,0,isz.width,isz.height) );
- dst1 = dst;
-
- if( x2 - x1 < isz.width || y2 - y1 < isz.height )
- dst1 = cvGetSubRect( _dft_img, &dstub1,
- cvRect( x1 - x0, y1 - y0, x2 - x1, y2 - y1 ));
-
- if( cn > 1 )
- {
- planes[i] = dst1;
- if( depth != max_depth )
- planes[i] = cvInitMatHeader( &temp, y2 - y1, x2 - x1, depth, _buf );
- cvSplit( src, planes[0], planes[1], planes[2], planes[3] );
- src = planes[i];
- planes[i] = 0;
- }
-
- if( dst1 != src )
- cvConvert( src, dst1 );
-
- if( dst != dst1 )
- cvCopyMakeBorder( dst1, dst, cvPoint(x1 - x0, y1 - y0), IPL_BORDER_REPLICATE );
-
- if( dftsize.width > isz.width )
- {
- cvGetSubRect( _dft_img, dst, cvRect(isz.width, 0,
- dftsize.width - isz.width,dftsize.height) );
- cvZero( dst );
- }
-
- cvDFT( _dft_img, _dft_img, CV_DXT_FORWARD, isz.height );
- cvGetSubRect( dft_templ, dst,
- cvRect(0,(templ_cn>1?yofs:0),dftsize.width,dftsize.height) );
-
- cvMulSpectrums( _dft_img, dst, _dft_img, CV_DXT_MUL_CONJ );
- cvDFT( _dft_img, _dft_img, CV_DXT_INVERSE, csz.height );
-
- src = cvGetSubRect( _dft_img, &sstub, cvRect(0,0,csz.width,csz.height) );
- dst = cvGetSubRect( corr, &dstub, cvRect(x,y,csz.width,csz.height) );
-
- if( corr_cn > 1 )
- {
- planes[i] = src;
- if( corr_depth != max_depth )
- {
- planes[i] = cvInitMatHeader( &temp, csz.height, csz.width,
- corr_depth, _buf );
- cvConvert( src, planes[i] );
- }
- cvMerge( planes[0], planes[1], planes[2], planes[3], dst );
- planes[i] = 0;
- }
- else
- {
- if( i == 0 )
- cvConvert( src, dst );
- else
- {
- if( max_depth > corr_depth )
- {
- cvInitMatHeader( &temp, csz.height, csz.width,
- corr_depth, _buf );
- cvConvert( src, &temp );
- src = &temp;
- }
- cvAcc( src, dst );
- }
- }
- }
- }
- }
-
- __END__;
-
- cvReleaseMat( &dft_templ );
-
- for( k = 0; k < num_threads; k++ )
- {
- cvReleaseMat( &dft_img[k] );
- cvFree( &buf[k] );
- }
-}
-
-
-/***************************** IPP Match Template Functions ******************************/
-
-icvCrossCorrValid_Norm_8u32f_C1R_t icvCrossCorrValid_Norm_8u32f_C1R_p = 0;
-icvCrossCorrValid_NormLevel_8u32f_C1R_t icvCrossCorrValid_NormLevel_8u32f_C1R_p = 0;
-icvSqrDistanceValid_Norm_8u32f_C1R_t icvSqrDistanceValid_Norm_8u32f_C1R_p = 0;
-icvCrossCorrValid_Norm_32f_C1R_t icvCrossCorrValid_Norm_32f_C1R_p = 0;
-icvCrossCorrValid_NormLevel_32f_C1R_t icvCrossCorrValid_NormLevel_32f_C1R_p = 0;
-icvSqrDistanceValid_Norm_32f_C1R_t icvSqrDistanceValid_Norm_32f_C1R_p = 0;
-
-typedef CvStatus (CV_STDCALL * CvTemplMatchIPPFunc)
- ( const void* img, int imgstep, CvSize imgsize,
- const void* templ, int templstep, CvSize templsize,
- void* result, int rstep );
-
-/*****************************************************************************************/
-
-CV_IMPL void
-cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )
-{
- CvMat* sum = 0;
- CvMat* sqsum = 0;
-
- CV_FUNCNAME( "cvMatchTemplate" );
-
- __BEGIN__;
-
- int coi1 = 0, coi2 = 0;
- int depth, cn;
- int i, j, k;
- CvMat stub, *img = (CvMat*)_img;
- CvMat tstub, *templ = (CvMat*)_templ;
- CvMat rstub, *result = (CvMat*)_result;
- CvScalar templ_mean = cvScalarAll(0);
- double templ_norm = 0, templ_sum2 = 0;
-
- int idx = 0, idx2 = 0;
- double *p0, *p1, *p2, *p3;
- double *q0, *q1, *q2, *q3;
- double inv_area;
- int sum_step, sqsum_step;
- int num_type = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
- method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
- int is_normed = method == CV_TM_CCORR_NORMED ||
- method == CV_TM_SQDIFF_NORMED ||
- method == CV_TM_CCOEFF_NORMED;
-
- CV_CALL( img = cvGetMat( img, &stub, &coi1 ));
- CV_CALL( templ = cvGetMat( templ, &tstub, &coi2 ));
- CV_CALL( result = cvGetMat( result, &rstub ));
-
- if( CV_MAT_DEPTH( img->type ) != CV_8U &&
- CV_MAT_DEPTH( img->type ) != CV_32F )
- CV_ERROR( CV_StsUnsupportedFormat,
- "The function supports only 8u and 32f data types" );
-
- if( !CV_ARE_TYPES_EQ( img, templ ))
- CV_ERROR( CV_StsUnmatchedSizes, "image and template should have the same type" );
-
- if( CV_MAT_TYPE( result->type ) != CV_32FC1 )
- CV_ERROR( CV_StsUnsupportedFormat, "output image should have 32f type" );
-
- if( img->rows < templ->rows || img->cols < templ->cols )
- {
- CvMat* t;
- CV_SWAP( img, templ, t );
- }
-
- if( result->rows != img->rows - templ->rows + 1 ||
- result->cols != img->cols - templ->cols + 1 )
- CV_ERROR( CV_StsUnmatchedSizes, "output image should be (W - w + 1)x(H - h + 1)" );
-
- if( method < CV_TM_SQDIFF || method > CV_TM_CCOEFF_NORMED )
- CV_ERROR( CV_StsBadArg, "unknown comparison method" );
-
- depth = CV_MAT_DEPTH(img->type);
- cn = CV_MAT_CN(img->type);
-
- if( is_normed && cn == 1 && templ->rows > 8 && templ->cols > 8 &&
- img->rows > templ->cols && img->cols > templ->cols )
- {
- CvTemplMatchIPPFunc ipp_func =
- depth == CV_8U ?
- (method == CV_TM_SQDIFF_NORMED ? (CvTemplMatchIPPFunc)icvSqrDistanceValid_Norm_8u32f_C1R_p :
- method == CV_TM_CCORR_NORMED ? (CvTemplMatchIPPFunc)icvCrossCorrValid_Norm_8u32f_C1R_p :
- (CvTemplMatchIPPFunc)icvCrossCorrValid_NormLevel_8u32f_C1R_p) :
- (method == CV_TM_SQDIFF_NORMED ? (CvTemplMatchIPPFunc)icvSqrDistanceValid_Norm_32f_C1R_p :
- method == CV_TM_CCORR_NORMED ? (CvTemplMatchIPPFunc)icvCrossCorrValid_Norm_32f_C1R_p :
- (CvTemplMatchIPPFunc)icvCrossCorrValid_NormLevel_32f_C1R_p);
-
- if( ipp_func )
- {
- CvSize img_size = cvGetMatSize(img), templ_size = cvGetMatSize(templ);
-
- IPPI_CALL( ipp_func( img->data.ptr, img->step ? img->step : CV_STUB_STEP,
- img_size, templ->data.ptr,
- templ->step ? templ->step : CV_STUB_STEP,
- templ_size, result->data.ptr,
- result->step ? result->step : CV_STUB_STEP ));
- for( i = 0; i < result->rows; i++ )
- {
- float* rrow = (float*)(result->data.ptr + i*result->step);
- for( j = 0; j < result->cols; j++ )
- {
- if( fabs(rrow[j]) > 1. )
- rrow[j] = rrow[j] < 0 ? -1.f : 1.f;
- }
- }
- EXIT;
- }
- }
-
- CV_CALL( icvCrossCorr( img, templ, result ));
-
- if( method == CV_TM_CCORR )
- EXIT;
-
- inv_area = 1./((double)templ->rows * templ->cols);
-
- CV_CALL( sum = cvCreateMat( img->rows + 1, img->cols + 1,
- CV_MAKETYPE( CV_64F, cn )));
- if( method == CV_TM_CCOEFF )
- {
- CV_CALL( cvIntegral( img, sum, 0, 0 ));
- CV_CALL( templ_mean = cvAvg( templ ));
- q0 = q1 = q2 = q3 = 0;
- }
- else
- {
- CvScalar _templ_sdv = cvScalarAll(0);
- CV_CALL( sqsum = cvCreateMat( img->rows + 1, img->cols + 1,
- CV_MAKETYPE( CV_64F, cn )));
- CV_CALL( cvIntegral( img, sum, sqsum, 0 ));
- CV_CALL( cvAvgSdv( templ, &templ_mean, &_templ_sdv ));
-
- templ_norm = CV_SQR(_templ_sdv.val[0]) + CV_SQR(_templ_sdv.val[1]) +
- CV_SQR(_templ_sdv.val[2]) + CV_SQR(_templ_sdv.val[3]);
-
- if( templ_norm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
- {
- cvSet( result, cvScalarAll(1.) );
- EXIT;
- }
-
- templ_sum2 = templ_norm +
- CV_SQR(templ_mean.val[0]) + CV_SQR(templ_mean.val[1]) +
- CV_SQR(templ_mean.val[2]) + CV_SQR(templ_mean.val[3]);
-
- if( num_type != 1 )
- {
- templ_mean = cvScalarAll(0);
- templ_norm = templ_sum2;
- }
-
- templ_sum2 /= inv_area;
- templ_norm = sqrt(templ_norm);
- templ_norm /= sqrt(inv_area); // care of accuracy here
-
- q0 = (double*)sqsum->data.ptr;
- q1 = q0 + templ->cols*cn;
- q2 = (double*)(sqsum->data.ptr + templ->rows*sqsum->step);
- q3 = q2 + templ->cols*cn;
- }
-
- p0 = (double*)sum->data.ptr;
- p1 = p0 + templ->cols*cn;
- p2 = (double*)(sum->data.ptr + templ->rows*sum->step);
- p3 = p2 + templ->cols*cn;
-
- sum_step = sum ? sum->step / sizeof(double) : 0;
- sqsum_step = sqsum ? sqsum->step / sizeof(double) : 0;
-
- for( i = 0; i < result->rows; i++ )
- {
- float* rrow = (float*)(result->data.ptr + i*result->step);
- idx = i * sum_step;
- idx2 = i * sqsum_step;
-
- for( j = 0; j < result->cols; j++, idx += cn, idx2 += cn )
- {
- double num = rrow[j], t;
- double wnd_mean2 = 0, wnd_sum2 = 0;
-
- if( num_type == 1 )
- {
- for( k = 0; k < cn; k++ )
- {
- t = p0[idx+k] - p1[idx+k] - p2[idx+k] + p3[idx+k];
- wnd_mean2 += CV_SQR(t);
- num -= t*templ_mean.val[k];
- }
-
- wnd_mean2 *= inv_area;
- }
-
- if( is_normed || num_type == 2 )
- {
- for( k = 0; k < cn; k++ )
- {
- t = q0[idx2+k] - q1[idx2+k] - q2[idx2+k] + q3[idx2+k];
- wnd_sum2 += t;
- }
-
- if( num_type == 2 )
- num = wnd_sum2 - 2*num + templ_sum2;
- }
-
- if( is_normed )
- {
- t = sqrt(MAX(wnd_sum2 - wnd_mean2,0))*templ_norm;
- if( t > DBL_EPSILON )
- {
- num /= t;
- if( fabs(num) > 1. )
- num = num > 0 ? 1 : -1;
- }
- else
- num = method != CV_TM_SQDIFF_NORMED || num < DBL_EPSILON ? 0 : 1;
- }
-
- rrow[j] = (float)num;
- }
- }
-
- __END__;
-
- cvReleaseMat( &sum );
- cvReleaseMat( &sqsum );
-}
-
-/* End of file. */
projects / opencv / blobdiff