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Backport C-API cleanup (imgproc) from 5.x

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This commit is contained in:
Maksim Shabunin
2023-01-16 23:29:50 +03:00
parent c63d79c5b1
commit c1e5c16ff3
34 changed files with 206 additions and 397 deletions
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modules/imgproc/src/templmatch.cpp
+27 -27
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@@ -315,7 +315,7 @@ static bool matchTemplate_CCORR(InputArray _image, InputArray _templ, OutputArra
static bool matchTemplate_CCORR_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
matchTemplate(_image, _templ, _result, cv::TM_CCORR);
int type = _image.type(), cn = CV_MAT_CN(type);
@@ -373,7 +373,7 @@ static bool matchTemplate_SQDIFF(InputArray _image, InputArray _templ, OutputArr
return( matchTemplateNaive_SQDIFF(_image, _templ, _result));
else
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
matchTemplate(_image, _templ, _result, cv::TM_CCORR);
int type = _image.type(), cn = CV_MAT_CN(type);
@@ -404,7 +404,7 @@ static bool matchTemplate_SQDIFF(InputArray _image, InputArray _templ, OutputArr
static bool matchTemplate_SQDIFF_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
matchTemplate(_image, _templ, _result, cv::TM_CCORR);
int type = _image.type(), cn = CV_MAT_CN(type);
@@ -436,7 +436,7 @@ static bool matchTemplate_SQDIFF_NORMED(InputArray _image, InputArray _templ, Ou
static bool matchTemplate_CCOEFF(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
matchTemplate(_image, _templ, _result, cv::TM_CCORR);
UMat image_sums, temp;
integral(_image, image_sums, CV_32F);
@@ -471,7 +471,7 @@ static bool matchTemplate_CCOEFF(InputArray _image, InputArray _templ, OutputArr
static bool matchTemplate_CCOEFF_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
matchTemplate(_image, _templ, _result, cv::TM_CCORR);
UMat temp, image_sums, image_sqsums;
integral(_image, image_sums, image_sqsums, CV_32F, CV_32F);
@@ -796,7 +796,7 @@ static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _
merge(maskChannels.data(), templ.channels(), mask);
}
if (method == CV_TM_SQDIFF || method == CV_TM_SQDIFF_NORMED)
if (method == cv::TM_SQDIFF || method == cv::TM_SQDIFF_NORMED)
{
Mat temp_result(corrSize, CV_32F);
Mat img2 = img.mul(img);
@@ -810,19 +810,19 @@ static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _
// for normalization.
result = -2 * result + temp_result + templ2_mask2_sum;
if (method == CV_TM_SQDIFF_NORMED)
if (method == cv::TM_SQDIFF_NORMED)
{
sqrt(templ2_mask2_sum * temp_result, temp_result);
result /= temp_result;
}
}
else if (method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED)
else if (method == cv::TM_CCORR || method == cv::TM_CCORR_NORMED)
{
// If the mul() is ever unnested, declare MatExpr, *not* Mat, to be more efficient.
Mat templ_mask2 = templ.mul(mask.mul(mask));
crossCorr(img, templ_mask2, result, Point(0,0), 0, 0);
if (method == CV_TM_CCORR_NORMED)
if (method == cv::TM_CCORR_NORMED)
{
Mat temp_result(corrSize, CV_32F);
Mat img2 = img.mul(img);
@@ -834,7 +834,7 @@ static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _
result /= temp_result;
}
}
else if (method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED)
else if (method == cv::TM_CCOEFF || method == cv::TM_CCOEFF_NORMED)
{
// Do mul() inline or declare MatExpr where possible, *not* Mat, to be more efficient.
@@ -864,7 +864,7 @@ static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _
// transform back, but now with only one channel
result -= temp_res.reshape(1, result.rows);
}
if (method == CV_TM_CCOEFF_NORMED)
if (method == cv::TM_CCOEFF_NORMED)
{
// norm(T')
double norm_templx = norm(mask.mul(templ - sum(mask.mul(templ)).div(mask_sum)),
@@ -905,14 +905,14 @@ static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _
static void common_matchTemplate( Mat& img, Mat& templ, Mat& result, int method, int cn )
{
if( method == CV_TM_CCORR )
if( method == cv::TM_CCORR )
return;
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;
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;
double invArea = 1./((double)templ.rows * templ.cols);
@@ -921,7 +921,7 @@ static void common_matchTemplate( Mat& img, Mat& templ, Mat& result, int method,
double *q0 = 0, *q1 = 0, *q2 = 0, *q3 = 0;
double templNorm = 0, templSum2 = 0;
if( method == CV_TM_CCOEFF )
if( method == cv::TM_CCOEFF )
{
integral(img, sum, CV_64F);
templMean = mean(templ);
@@ -933,7 +933,7 @@ static void common_matchTemplate( Mat& img, Mat& templ, Mat& result, int method,
templNorm = templSdv[0]*templSdv[0] + templSdv[1]*templSdv[1] + templSdv[2]*templSdv[2] + templSdv[3]*templSdv[3];
if( templNorm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
if( templNorm < DBL_EPSILON && method == cv::TM_CCOEFF_NORMED )
{
result = Scalar::all(1);
return;
@@ -1020,7 +1020,7 @@ static void common_matchTemplate( Mat& img, Mat& templ, Mat& result, int method,
else if( fabs(num) < t*1.125 )
num = num > 0 ? 1 : -1;
else
num = method != CV_TM_SQDIFF_NORMED ? 0 : 1;
num = method != cv::TM_SQDIFF_NORMED ? 0 : 1;
}
rrow[j] = (float)num;
@@ -1116,30 +1116,30 @@ static bool ipp_matchTemplate( Mat& img, Mat& templ, Mat& result, int method)
if(templ.size().area()*4 > img.size().area())
return false;
if(method == CV_TM_SQDIFF)
if(method == cv::TM_SQDIFF)
{
if(ipp_sqrDistance(img, templ, result))
return true;
}
else if(method == CV_TM_SQDIFF_NORMED)
else if(method == cv::TM_SQDIFF_NORMED)
{
if(ipp_crossCorr(img, templ, result, false))
{
common_matchTemplate(img, templ, result, CV_TM_SQDIFF_NORMED, 1);
common_matchTemplate(img, templ, result, cv::TM_SQDIFF_NORMED, 1);
return true;
}
}
else if(method == CV_TM_CCORR)
else if(method == cv::TM_CCORR)
{
if(ipp_crossCorr(img, templ, result, false))
return true;
}
else if(method == CV_TM_CCORR_NORMED)
else if(method == cv::TM_CCORR_NORMED)
{
if(ipp_crossCorr(img, templ, result, true))
return true;
}
else if(method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED)
else if(method == cv::TM_CCOEFF || method == cv::TM_CCOEFF_NORMED)
{
if(ipp_crossCorr(img, templ, result, false))
{
@@ -1160,7 +1160,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
CV_INSTRUMENT_REGION();
int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
CV_Assert( cv::TM_SQDIFF <= method && method <= cv::TM_CCOEFF_NORMED );
CV_Assert( (depth == CV_8U || depth == CV_32F) && type == _templ.type() && _img.dims() <= 2 );
if (!_mask.empty())