#include "precomp.hpp"
-void
-icvCrossCorr( const CvArr* _img, const CvArr* _templ, CvArr* _corr,
- CvPoint anchor, double delta, int borderType )
+namespace cv
{
- const int CV_MAX_THREADS = 1;
- const double block_scale = 4.5;
- const int min_block_size = 256;
- cv::Ptr<CvMat> dft_img[CV_MAX_THREADS];
- cv::Ptr<CvMat> dft_templ;
- std::vector<uchar> buf[CV_MAX_THREADS];
- int k, num_threads = 0;
+
+void crossCorr( const Mat& img, const Mat& templ, Mat& corr,
+ Size corrsize, int ctype,
+ Point anchor, double delta, int borderType )
+{
+ const double blockScale = 4.5;
+ const int minBlockSize = 256;
+ std::vector<uchar> buf;
+
+ int depth = img.depth(), cn = img.channels();
+ int tdepth = templ.depth(), tcn = templ.channels();
+ int cdepth = CV_MAT_DEPTH(ctype), ccn = CV_MAT_CN(ctype);
+
+ CV_Assert( img.dims <= 2 && templ.dims <= 2 && corr.dims <= 2 );
+ CV_Assert( depth == CV_8U || depth == CV_16U || depth == CV_32F || depth == CV_64F );
+ CV_Assert( depth == tdepth || tdepth == CV_32F );
+
+ CV_Assert( corrsize.height <= img.rows + templ.rows - 1 &&
+ corrsize.width <= img.cols + templ.cols - 1 );
+
+ CV_Assert( ccn == 1 || delta == 0 );
- 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;
-
- img = cvGetMat( img, &istub );
- templ = cvGetMat( templ, &tstub );
- 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_MAT_DEPTH( img->type ) != CV_64F )
- 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" );
+ corr.create(corrsize, ctype);
+
+ int maxDepth = depth > CV_8U ? CV_64F : std::max(std::max(CV_32F, tdepth), cdepth);
+ Size blocksize, dftsize;
- 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);
-
- CV_Assert( corr_cn == 1 || delta == 0 );
-
- 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);
+ blocksize.width = cvRound(templ.cols*blockScale);
+ blocksize.width = std::max( blocksize.width, minBlockSize - templ.cols + 1 );
+ blocksize.width = std::min( blocksize.width, corr.cols );
+ blocksize.height = cvRound(templ.rows*blockScale);
+ blocksize.height = std::max( blocksize.height, minBlockSize - templ.rows + 1 );
+ blocksize.height = std::min( blocksize.height, corr.rows );
+
+ dftsize.width = std::max(getOptimalDFTSize(blocksize.width + templ.cols - 1), 2);
+ dftsize.height = getOptimalDFTSize(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 );
-
- dft_templ = cvCreateMat( dftsize.height*templ_cn, dftsize.width, max_depth );
-
-#ifdef USE_OPENMP
- num_threads = cvGetNumThreads();
-#else
- num_threads = 1;
-#endif
+ 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 );
- for( k = 0; k < num_threads; k++ )
- dft_img[k] = cvCreateMat( dftsize.height, dftsize.width, max_depth );
+ Mat dftTempl( dftsize.height*tcn, dftsize.width, maxDepth );
+ Mat dftImg( dftsize, maxDepth );
- if( templ_cn > 1 && templ_depth != max_depth )
- buf_size = templ->cols*templ->rows*CV_ELEM_SIZE(templ_depth);
+ int i, k, bufSize = 0;
+ if( tcn > 1 && tdepth != maxDepth )
+ bufSize = templ.cols*templ.rows*CV_ELEM_SIZE(tdepth);
- 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( cn > 1 && depth != maxDepth )
+ bufSize = std::max( bufSize, (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++ )
- buf[k].resize(buf_size);
- }
+ if( (ccn > 1 || cn > 1) && cdepth != maxDepth )
+ bufSize = std::max( bufSize, blocksize.width*blocksize.height*CV_ELEM_SIZE(cdepth));
+ buf.resize(bufSize);
+
// compute DFT of each template plane
- for( k = 0; k < templ_cn; k++ )
+ for( k = 0; k < tcn; k++ )
{
- CvMat dstub, *src, *dst, temp;
- CvMat* planes[] = { 0, 0, 0, 0 };
int yofs = k*dftsize.height;
+ Mat src = templ;
+ Mat dst(dftTempl, Rect(0, yofs, dftsize.width, dftsize.height));
+ Mat dst1(dftTempl, Rect(0, yofs, templ.cols, templ.rows));
- src = templ;
- dst = cvGetSubRect( dft_templ, &dstub, cvRect(0,yofs,templ->cols,templ->rows));
-
- if( templ_cn > 1 )
+ if( tcn > 1 )
{
- planes[k] = templ_depth == max_depth ? dst :
- cvInitMatHeader( &temp, templ->rows, templ->cols, templ_depth, &buf[0][0] );
- cvSplit( templ, planes[0], planes[1], planes[2], planes[3] );
- src = planes[k];
- planes[k] = 0;
+ src = tdepth == maxDepth ? dst1 : Mat(templ.size(), tdepth, &buf[0]);
+ int pairs[] = {k, 0};
+ mixChannels(&templ, 1, &src, 1, pairs, 1);
}
- if( dst != src )
- cvConvert( src, dst );
+ if( dst1.data != src.data )
+ src.convertTo(dst1, dst1.depth());
- if( dft_templ->cols > templ->cols )
+ if( dst.cols > templ.cols )
{
- cvGetSubRect( dft_templ, dst, cvRect(templ->cols, yofs,
- dft_templ->cols - templ->cols, templ->rows) );
- cvZero( dst );
+ Mat part(dst, Range(0, templ.rows), Range(templ.cols, dst.cols));
+ part = Scalar::all(0);
}
- cvGetSubRect( dft_templ, dst, cvRect(0,yofs,dftsize.width,dftsize.height) );
- cvDFT( dst, dst, CV_DXT_FORWARD + CV_DXT_SCALE, templ->rows );
+ dft(dst, dst, 0, 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;
-
-#if defined _OPENMP && defined USE_OPENMP
- #pragma omp parallel for num_threads(num_threads) schedule(dynamic)
-#endif
+ int tileCountX = (corr.cols + blocksize.width - 1)/blocksize.width;
+ int tileCountY = (corr.rows + blocksize.height - 1)/blocksize.height;
+ int tileCount = tileCountX * tileCountY;
+
+ Size wholeSize = img.size();
+ Point roiofs(0,0);
+ Mat img0 = img;
+
+ if( !(borderType & BORDER_ISOLATED) )
+ {
+ img.locateROI(wholeSize, roiofs);
+ img0.adjustROI(roiofs.y, wholeSize.height-img.rows-roiofs.y,
+ roiofs.x, wholeSize.width-img.cols-roiofs.x);
+ }
+
// calculate correlation by blocks
- for( k = 0; k < tile_count; k++ )
+ for( i = 0; i < tileCount; i++ )
{
-#ifdef USE_OPENMP
- int thread_idx = cvGetThreadNum();
-#else
- int thread_idx = 0;
-#endif
- 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];
- uchar* _buf = buf_size > 0 ? &buf[thread_idx][0] : 0;
- 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 );
+ int x = (i%tileCountX)*blocksize.width;
+ int y = (i/tileCountX)*blocksize.height;
+
+ Size bsz(std::min(blocksize.width, corr.cols - x),
+ std::min(blocksize.height, corr.rows - y));
+ Size dsz(bsz.width + templ.cols - 1, bsz.height + templ.rows - 1);
+ int x0 = x - anchor.x + roiofs.x, y0 = y - anchor.y + roiofs.y;
+ int x1 = std::max(0, x0), y1 = std::max(0, y0);
+ int x2 = std::min(img0.cols, x0 + dsz.width);
+ int y2 = std::min(img0.rows, y0 + dsz.height);
+ Mat src0(img0, Range(y1, y2), Range(x1, x2));
+ Mat dst(dftImg, Rect(0, 0, dsz.width, dsz.height));
+ Mat dst1(dftImg, Rect(x1-x0, y1-y0, x2-x1, y2-y1));
+ Mat cdst(corr, Rect(x, y, bsz.width, bsz.height));
- for( i = 0; i < cn; i++ )
+ for( k = 0; k < cn; k++ )
{
- 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;
+ Mat src = src0;
- 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;
+ src = depth == maxDepth ? dst1 : Mat(y2-y1, x2-x1, depth, &buf[0]);
+ int pairs[] = {k, 0};
+ mixChannels(&src0, 1, &src, 1, pairs, 1);
}
- if( dst1 != src )
- cvConvert( src, dst1 );
+ if( dst1.data != src.data )
+ src.convertTo(dst1, dst1.depth());
- if( dst != dst1 )
- cvCopyMakeBorder( dst1, dst, cvPoint(x1 - x0, y1 - y0), borderType );
+ if( x2 - x1 < dsz.width || y2 - y1 < dsz.height )
+ copyMakeBorder(dst1, dst, y1-y0, dst.rows-dst1.rows-(y1-y0),
+ x1-x0, dst.cols-dst1.cols-(x1-x0), borderType);
- if( dftsize.width > isz.width )
+ if( dftsize.width > dsz.width )
{
- cvGetSubRect( _dft_img, dst, cvRect(isz.width, 0,
- dftsize.width - isz.width,dftsize.height) );
- cvZero( dst );
+ Mat part(dftImg, Range(0, dsz.height), Range(dsz.width, dftsize.width));
+ part = Scalar::all(0);
}
- 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 );
+ dft( dftImg, dftImg, 0, dsz.height );
+ Mat dftTempl1(dftTempl, Rect(0, tcn > 1 ? k*dftsize.height : 0,
+ dftsize.width, dftsize.height));
+ mulSpectrums(dftImg, dftTempl1, dftImg, 0, true);
+ dft( dftImg, dftImg, DFT_INVERSE + DFT_SCALE, bsz.height );
- src = cvGetSubRect( _dft_img, &sstub, cvRect(0,0,csz.width,csz.height) );
- dst = cvGetSubRect( corr, &dstub, cvRect(x,y,csz.width,csz.height) );
+ src = dftImg(Rect(0, 0, bsz.width, bsz.height));
- if( corr_cn > 1 )
+ if( ccn > 1 )
{
- planes[i] = src;
- if( corr_depth != max_depth )
+ if( cdepth != maxDepth )
{
- planes[i] = cvInitMatHeader( &temp, csz.height, csz.width,
- corr_depth, _buf );
- cvConvertScale( src, planes[i], 1, delta );
+ Mat plane(bsz, cdepth, &buf[0]);
+ src.convertTo(plane, cdepth, 1, delta);
+ src = plane;
}
- cvMerge( planes[0], planes[1], planes[2], planes[3], dst );
- planes[i] = 0;
+ int pairs[] = {0, k};
+ mixChannels(&src, 1, &cdst, 1, pairs, 1);
}
else
{
- if( i == 0 )
- cvConvertScale( src, dst, 1, delta );
+ if( k == 0 )
+ src.convertTo(cdst, cdepth, 1, delta);
else
{
- if( max_depth > corr_depth )
+ if( maxDepth != cdepth )
{
- cvInitMatHeader( &temp, csz.height, csz.width,
- corr_depth, _buf );
- cvConvert( src, &temp );
- src = &temp;
+ Mat plane(bsz, cdepth, &buf[0]);
+ src.convertTo(plane, cdepth);
+ src = plane;
}
- cvAcc( src, dst );
+ add(src, cdst, cdst);
}
}
}
}
}
-void
+/*void
cv::crossCorr( const Mat& img, const Mat& templ, Mat& corr,
Point anchor, double delta, int borderType )
{
CvMat _img = img, _templ = templ, _corr = corr;
icvCrossCorr( &_img, &_templ, &_corr, anchor, delta, borderType );
-}
+}*/
/*****************************************************************************************/
-CV_IMPL void
-cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )
+void matchTemplate( const Mat& _img, const Mat& _templ, Mat& result, int method )
{
- cv::Ptr<CvMat> sum, sqsum;
+ CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
- 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 ||
+ int numType = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
+ method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
+ bool isNormed = method == CV_TM_CCORR_NORMED ||
method == CV_TM_SQDIFF_NORMED ||
method == CV_TM_CCOEFF_NORMED;
- img = cvGetMat( img, &stub, &coi1 );
- templ = cvGetMat( templ, &tstub, &coi2 );
- 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);
+ Mat img = _img, templ = _templ;
+ if( img.rows < templ.rows || img.cols < templ.cols )
+ std::swap(img, templ);
+
+ CV_Assert( (img.depth() == CV_8U || img.depth() == CV_32F) &&
+ img.type() == templ.type() );
- icvCrossCorr( img, templ, result );
+ int cn = img.channels();
+ crossCorr( img, templ, result,
+ Size(img.cols - templ.cols + 1, img.rows - templ.rows + 1),
+ CV_32F, Point(0,0), 0, 0);
if( method == CV_TM_CCORR )
return;
- inv_area = 1./((double)templ->rows * templ->cols);
+ double invArea = 1./((double)templ.rows * templ.cols);
- sum = cvCreateMat( img->rows + 1, img->cols + 1, CV_MAKETYPE( CV_64F, cn ));
+ Mat sum, sqsum;
+ Scalar templMean, templSdv;
+ double *q0 = 0, *q1 = 0, *q2 = 0, *q3 = 0;
+ double templNorm = 0, templSum2 = 0;
+
if( method == CV_TM_CCOEFF )
{
- cvIntegral( img, sum, 0, 0 );
- templ_mean = cvAvg( templ );
- q0 = q1 = q2 = q3 = 0;
+ integral(img, sum, CV_64F);
+ templMean = mean(templ);
}
else
{
- CvScalar _templ_sdv = cvScalarAll(0);
- sqsum = cvCreateMat( img->rows + 1, img->cols + 1, CV_MAKETYPE( CV_64F, cn ));
- cvIntegral( img, sum, sqsum, 0 );
- cvAvgSdv( templ, &templ_mean, &_templ_sdv );
+ integral(img, sum, sqsum, CV_64F);
+ meanStdDev( templ, templMean, templSdv );
- 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]);
+ templNorm = CV_SQR(templSdv[0]) + CV_SQR(templSdv[1]) +
+ CV_SQR(templSdv[2]) + CV_SQR(templSdv[3]);
- if( templ_norm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
+ if( templNorm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
{
- cvSet( result, cvScalarAll(1.) );
+ result = Scalar::all(1);
return;
}
- 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]);
+ templSum2 = templNorm +
+ CV_SQR(templMean[0]) + CV_SQR(templMean[1]) +
+ CV_SQR(templMean[2]) + CV_SQR(templMean[3]);
- if( num_type != 1 )
+ if( numType != 1 )
{
- templ_mean = cvScalarAll(0);
- templ_norm = templ_sum2;
+ templMean = Scalar::all(0);
+ templNorm = templSum2;
}
- 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;
+ templSum2 /= invArea;
+ templNorm = sqrt(templNorm);
+ templNorm /= sqrt(invArea); // care of accuracy here
+
+ q0 = (double*)sqsum.data;
+ q1 = q0 + templ.cols*cn;
+ q2 = (double*)(sqsum.data + 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;
+ double* p0 = (double*)sum.data;
+ double* p1 = p0 + templ.cols*cn;
+ double* p2 = (double*)(sum.data + templ.rows*sum.step);
+ double* p3 = p2 + templ.cols*cn;
- sum_step = sum ? sum->step / sizeof(double) : 0;
- sqsum_step = sqsum ? sqsum->step / sizeof(double) : 0;
+ int sumstep = sum.data ? sum.step / sizeof(double) : 0;
+ int sqstep = sqsum.data ? sqsum.step / sizeof(double) : 0;
- for( i = 0; i < result->rows; i++ )
+ int i, j, k;
+
+ for( i = 0; i < result.rows; i++ )
{
- float* rrow = (float*)(result->data.ptr + i*result->step);
- idx = i * sum_step;
- idx2 = i * sqsum_step;
+ float* rrow = (float*)(result.data + i*result.step);
+ int idx = i * sumstep;
+ int idx2 = i * sqstep;
- for( j = 0; j < result->cols; j++, idx += cn, idx2 += cn )
+ for( j = 0; j < result.cols; j++, idx += cn, idx2 += cn )
{
double num = rrow[j], t;
- double wnd_mean2 = 0, wnd_sum2 = 0;
+ double wndMean2 = 0, wndSum2 = 0;
- if( num_type == 1 )
+ if( numType == 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];
+ wndMean2 += CV_SQR(t);
+ num -= t*templMean[k];
}
- wnd_mean2 *= inv_area;
+ wndMean2 *= invArea;
}
- if( is_normed || num_type == 2 )
+ if( isNormed || numType == 2 )
{
for( k = 0; k < cn; k++ )
{
t = q0[idx2+k] - q1[idx2+k] - q2[idx2+k] + q3[idx2+k];
- wnd_sum2 += t;
+ wndSum2 += t;
}
- if( num_type == 2 )
- num = wnd_sum2 - 2*num + templ_sum2;
+ if( numType == 2 )
+ num = wndSum2 - 2*num + templSum2;
}
- if( is_normed )
+ if( isNormed )
{
- t = sqrt(MAX(wnd_sum2 - wnd_mean2,0))*templ_norm;
+ t = sqrt(MAX(wndSum2 - wndMean2,0))*templNorm;
if( fabs(num) < t )
num /= t;
else if( fabs(num) < t*1.125 )
}
}
-void cv::matchTemplate( const Mat& image, const Mat& templ, Mat& result, int method )
+}
+
+
+CV_IMPL void
+cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )
{
- result.create( std::abs(image.rows - templ.rows) + 1,
- std::abs(image.cols - templ.cols) + 1, CV_32F );
- CvMat _image = image, _templ = templ, _result = result;
- cvMatchTemplate( &_image, &_templ, &_result, method );
+ cv::Mat img = cv::cvarrToMat(_img), templ = cv::cvarrToMat(_templ),
+ result = cv::cvarrToMat(_result);
+ CV_Assert( result.size() == cv::Size(std::abs(img.cols - templ.cols) + 1,
+ std::abs(img.rows - templ.rows) + 1) &&
+ result.type() == CV_32F );
+ matchTemplate(img, templ, result, method);
}
/* End of file. */
projects / platform / upstream / opencv.git / commitdiff