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Merge pull request #2256 from ilya-lavrenov:tapi_matchTempl

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pull/2258/merge
Andrey Pavlenko 11 years ago committed by OpenCV Buildbot
parent 206df7fdb1 e844c08203
commit cb1e4b2ede
5 changed files with 125 additions and 165 deletions
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  1. 2
      modules/core/include/opencv2/core/opencl/ocl_defs.hpp
  2. 2
      modules/imgproc/perf/opencl/perf_matchTemplate.cpp
  3. 6
      modules/imgproc/src/opencl/match_template.cl
  4. 256
      modules/imgproc/src/templmatch.cpp
  5. 24
      modules/imgproc/test/ocl/test_match_template.cpp

2
modules/core/include/opencv2/core/opencl/ocl_defs.hpp
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@ -28,7 +28,7 @@
if (cv::ocl::useOpenCL() && (condition)) \
{ \
CV_Assert(func); \
return; \
return __VA_ARGS__; \
} \
}
#else

2
modules/imgproc/perf/opencl/perf_matchTemplate.cpp
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@ -54,4 +54,4 @@ namespace ocl {
}
}
#endif // HAVE_OPENCL
#endif // HAVE_OPENCL

6
modules/imgproc/src/opencl/match_template.cl
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@ -98,7 +98,7 @@ __kernel void matchTemplate_Naive_CCORR (__global const uchar * img,int img_step
__kernel void matchTemplate_CCORR_NORMED ( __global const uchar * img_sqsums, int img_sqsums_step, int img_sqsums_offset,
__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
int tpl_rows, int tpl_cols, ulong tpl_sqsum)
int tpl_rows, int tpl_cols, float tpl_sqsum)
{
int gidx = get_global_id(0);
int gidy = get_global_id(1);
@ -157,7 +157,7 @@ __kernel void matchTemplate_Naive_SQDIFF(__global const uchar * img,int img_step
__kernel void matchTemplate_SQDIFF_NORMED ( __global const uchar * img_sqsums, int img_sqsums_step, int img_sqsums_offset,
__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
int tpl_rows, int tpl_cols, ulong tpl_sqsum)
int tpl_rows, int tpl_cols, float tpl_sqsum)
{
int gidx = get_global_id(0);
int gidy = get_global_id(1);
@ -394,4 +394,4 @@ __kernel void matchTemplate_CCOEFF_NORMED_C4 (__global const uchar * img_sums, i
__global float * result = (__global float *)(res+res_idx);
*result = normAcc((*result) - num, denum);
}
}
}

256
modules/imgproc/src/templmatch.cpp
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@ -49,7 +49,7 @@ namespace cv
#ifdef HAVE_OPENCL
static bool useNaive(int method, int depth, Size size)
static bool useNaive(int method, int depth, const Size & size)
{
#ifdef HAVE_CLAMDFFT
if (method == TM_SQDIFF && depth == CV_32F)
@ -59,135 +59,128 @@ static bool useNaive(int method, int depth, Size size)
else
return false;
#else
#define UNUSED(x) (void)(x);
UNUSED(method) UNUSED(depth) UNUSED(size)
#undef UNUSED
return true;
(void)(method);
(void)(depth);
(void)(size);
return true;
#endif
}
/////////////////////////////////////////////////// CCORR //////////////////////////////////////////////////////////////
static bool matchTemplateNaive_CCORR (InputArray _image, InputArray _templ, OutputArray _result, int cn)
static bool matchTemplateNaive_CCORR(InputArray _image, InputArray _templ, OutputArray _result)
{
int type = _image.type();
int depth = CV_MAT_DEPTH(type);
const char * kernelName = "matchTemplate_Naive_CCORR";
int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
ocl::Kernel k (kernelName, ocl::imgproc::match_template_oclsrc, format("-D type=%s -D elem_type=%s -D cn=%d",ocl::typeToStr(type), ocl::typeToStr(depth), cn));
ocl::Kernel k("matchTemplate_Naive_CCORR", ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d", ocl::typeToStr(type), ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat templ = _templ.getUMat(), result;
UMat image = _image.getUMat(), templ = _templ.getUMat();
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
result = _result.getUMat();
UMat result = _result.getUMat();
size_t globalsize[2] = {result.cols, result.rows};
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,NULL,false);
size_t globalsize[2] = { result.cols, result.rows };
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ),
ocl::KernelArg::WriteOnly(result)).run(2, globalsize, NULL, false);
}
static bool matchTemplate_CCORR_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
int type = _image.type();
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
const char * kernelName = "matchTemplate_CCORR_NORMED";
int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
ocl::Kernel k(kernelName, ocl::imgproc::match_template_oclsrc, format("-D type=%s -D elem_type=%s -D cn=%d",ocl::typeToStr(type), ocl::typeToStr(depth), cn));
ocl::Kernel k("matchTemplate_CCORR_NORMED", ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d", ocl::typeToStr(type),
ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat templ = _templ.getUMat(), result;
UMat image = _image.getUMat(), templ = _templ.getUMat();
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
result = _result.getUMat();
UMat result = _result.getUMat();
UMat image_sums, image_sqsums;
integral(image.reshape(1), image_sums, image_sqsums, CV_32F, CV_32F);
UMat templ_resh, temp;
templ.reshape(1).convertTo(templ_resh, CV_32F);
UMat temp;
multiply(templ, templ, temp, 1, CV_32F);
Scalar s = sum(temp);
float templ_sqsum = 0;
for (int i = 0; i < cn; ++i)
templ_sqsum += static_cast<float>(s[i]);
multiply(templ_resh, templ_resh, temp);
unsigned long long templ_sqsum = (unsigned long long)sum(temp)[0];
size_t globalsize[2] = {result.cols, result.rows};
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,NULL,false);
size_t globalsize[2] = { result.cols, result.rows };
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::ReadWrite(result),
templ.rows, templ.cols, templ_sqsum).run(2, globalsize, NULL, false);
}
static bool matchTemplate_CCORR(InputArray _image, InputArray _templ, OutputArray _result)
{
if (useNaive(TM_CCORR, _image.depth(), _templ.size()) )
return matchTemplateNaive_CCORR(_image, _templ, _result, _image.channels());
return matchTemplateNaive_CCORR(_image, _templ, _result);
else
return false;
}
////////////////////////////////////// SQDIFF //////////////////////////////////////////////////////////////
static bool matchTemplateNaive_SQDIFF(InputArray _image, InputArray _templ, OutputArray _result, int cn)
static bool matchTemplateNaive_SQDIFF(InputArray _image, InputArray _templ, OutputArray _result)
{
int type = _image.type();
int depth = CV_MAT_DEPTH(type);
int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
const char * kernelName = "matchTemplate_Naive_SQDIFF";
ocl::Kernel k (kernelName, ocl::imgproc::match_template_oclsrc, format("-D type=%s -D elem_type=%s -D cn=%d",ocl::typeToStr(type), ocl::typeToStr(depth), cn));
ocl::Kernel k("matchTemplate_Naive_SQDIFF", ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d", ocl::typeToStr(type),
ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat templ = _templ.getUMat(), result;
UMat image = _image.getUMat(), templ = _templ.getUMat();
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
result = _result.getUMat();
size_t globalsize[2] = {result.cols, result.rows};
UMat result = _result.getUMat();
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,NULL,false);
size_t globalsize[2] = { result.cols, result.rows };
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ),
ocl::KernelArg::WriteOnly(result)).run(2, globalsize, NULL, false);
}
static bool matchTemplate_SQDIFF_NORMED (InputArray _image, InputArray _templ, OutputArray _result)
static bool matchTemplate_SQDIFF_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
int type = _image.type();
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
const char * kernelName = "matchTemplate_SQDIFF_NORMED";
ocl::Kernel k(kernelName, ocl::imgproc::match_template_oclsrc, format("-D type=%s -D elem_type=%s -D cn=%d",ocl::typeToStr(type), ocl::typeToStr(depth), cn));
ocl::Kernel k("matchTemplate_SQDIFF_NORMED", ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d",
ocl::typeToStr(type), ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat templ = _templ.getUMat(), result;
UMat image = _image.getUMat(), templ = _templ.getUMat();
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
result = _result.getUMat();
UMat result = _result.getUMat();
UMat image_sums, image_sqsums;
integral(image.reshape(1), image_sums, image_sqsums, CV_32F, CV_32F);
UMat temp, templ_resh;
templ.reshape(1).convertTo(templ_resh, CV_32F);
multiply(templ_resh, templ_resh, temp);
unsigned long long templ_sqsum = (unsigned long long)sum(temp)[0];
UMat temp;
multiply(templ, templ, temp, 1, CV_32F);
Scalar s = sum(temp);
float templ_sqsum = 0;
for (int i = 0; i < cn; ++i)
templ_sqsum += (float)s[i];
size_t globalsize[2] = {result.cols, result.rows};
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,NULL,false);
size_t globalsize[2] = { result.cols, result.rows };
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::ReadWrite(result),
templ.rows, templ.cols, templ_sqsum).run(2, globalsize, NULL, false);
}
static bool matchTemplate_SQDIFF(InputArray _image, InputArray _templ, OutputArray _result)
{
if (useNaive(TM_SQDIFF, _image.depth(), _templ.size()))
return matchTemplateNaive_SQDIFF(_image, _templ, _result, _image.channels());
return matchTemplateNaive_SQDIFF(_image, _templ, _result);
else
return false;
}
@ -201,91 +194,66 @@ static bool matchTemplate_CCOEFF(InputArray _image, InputArray _templ, OutputArr
UMat image_sums;
integral(_image, image_sums);
int type = image_sums.type();
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
const char * kernelName;
int type = image_sums.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (cn==1)
kernelName = "matchTemplate_Prepared_CCOEFF_C1";
else if (cn==2)
kernelName = "matchTemplate_Prepared_CCOEFF_C2";
else
kernelName = "matchTemplate_Prepared_CCOEFF_C4";
ocl::Kernel k(kernelName, ocl::imgproc::match_template_oclsrc, format("-D type=%s -D elem_type=%s -D cn=%d",ocl::typeToStr(type), ocl::typeToStr(depth), cn));
ocl::Kernel k(cv::format("matchTemplate_Prepared_CCOEFF_C%d", cn).c_str(), ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d", ocl::typeToStr(type), ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat templ = _templ.getUMat(), result;
Size size = _image.size();
UMat templ = _templ.getUMat();
Size size = _image.size(), tsize = templ.size();
_result.create(size.height - templ.rows + 1, size.width - templ.cols + 1, CV_32F);
result = _result.getUMat();
UMat result = _result.getUMat();
size_t globalsize[2] = {result.cols, result.rows};
size_t globalsize[2] = { result.cols, result.rows };
if (cn==1)
if (cn == 1)
{
float templ_sum = (float)sum(_templ)[0]/ _templ.size().area();
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sum).run(2,globalsize,NULL,false);
float templ_sum = static_cast<float>(sum(_templ)[0]) / tsize.area();
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadWrite(result),
templ.rows, templ.cols, templ_sum).run(2, globalsize, NULL, false);
}
else
{
Vec4f templ_sum = Vec4f::all(0);
templ_sum = sum(templ)/ templ.size().area();
if (cn==2)
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols,
templ_sum[0],templ_sum[1]).run(2,globalsize,NULL,false);
templ_sum = sum(templ) / tsize.area();
if (cn == 2)
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols,
templ_sum[0], templ_sum[1]).run(2, globalsize, NULL, false);
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols,
templ_sum[0],templ_sum[1],templ_sum[2],templ_sum[3]).run(2,globalsize,NULL,false);
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols,
templ_sum[0], templ_sum[1], templ_sum[2], templ_sum[3]).run(2, globalsize, NULL, false);
}
}
static bool matchTemplate_CCOEFF_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
{
UMat imagef, templf;
_image.getUMat().convertTo(imagef, CV_32F);
_templ.getUMat().convertTo(templf, CV_32F);
matchTemplate(imagef, templf, _result, CV_TM_CCORR);
const char * kernelName;
matchTemplate(_image, _templ, _result, CV_TM_CCORR);
UMat temp, image_sums, image_sqsums;
integral(_image,image_sums, image_sqsums, CV_32F, CV_32F);
integral(_image, image_sums, image_sqsums, CV_32F, CV_32F);
int type = image_sums.type();
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (cn== 1)
kernelName = "matchTemplate_CCOEFF_NORMED_C1";
else if (cn==2)
kernelName = "matchTemplate_CCOEFF_NORMED_C2";
else
kernelName = "matchTemplate_CCOEFF_NORMED_C4";
int type = image_sums.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
ocl::Kernel k(kernelName, ocl::imgproc::match_template_oclsrc,
ocl::Kernel k(format("matchTemplate_CCOEFF_NORMED_C%d", cn).c_str(), ocl::imgproc::match_template_oclsrc,
format("-D type=%s -D elem_type=%s -D cn=%d", ocl::typeToStr(type), ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat templ = _templ.getUMat(), result;
int image_rows = _image.size().height, image_cols = _image.size().width;
_result.create(image_rows - templ.rows + 1, image_cols - templ.cols + 1, CV_32F);
result = _result.getUMat();
size_t globalsize[2] = {result.cols, result.rows};
UMat templ = _templ.getUMat();
Size size = _image.size(), tsize = templ.size();
_result.create(size.height - templ.rows + 1, size.width - templ.cols + 1, CV_32F);
UMat result = _result.getUMat();
float scale = 1.f / templ.size().area();
size_t globalsize[2] = { result.cols, result.rows };
float scale = 1.f / tsize.area();
if (cn==1)
if (cn == 1)
{
float templ_sum = (float)sum(templ)[0];
multiply(templf, templf, temp);
multiply(templ, templ, temp, 1, CV_32F);
float templ_sqsum = (float)sum(temp)[0];
templ_sqsum -= scale * templ_sum * templ_sum;
@ -297,27 +265,23 @@ static bool matchTemplate_CCOEFF_NORMED(InputArray _image, InputArray _templ, Ou
return true;
}
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums),ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale, templ_sum, templ_sqsum)
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols, scale, templ_sum, templ_sqsum)
.run(2,globalsize,NULL,false);
}
else
{
Vec4f templ_sum = Vec4f::all(0);
Vec4f templ_sqsum = Vec4f::all(0);
Vec4f templ_sum = Vec4f::all(0), templ_sqsum = Vec4f::all(0);
templ_sum = sum(templ);
multiply(templf, templf, temp);
multiply(templ, templ, temp, 1, CV_32F);
templ_sqsum = sum(temp);
float templ_sqsum_sum = 0;
for(int i = 0; i < cn; i ++)
{
templ_sqsum_sum += templ_sqsum[i] - scale * templ_sum[i] * templ_sum[i];
}
for (int i = 0; i < cn; i ++)
templ_sqsum_sum += templ_sqsum[i] - scale * templ_sum[i] * templ_sum[i];
templ_sum *= scale;
templ_sum *= scale;
if (templ_sqsum_sum < DBL_EPSILON)
{
@ -325,38 +289,35 @@ static bool matchTemplate_CCOEFF_NORMED(InputArray _image, InputArray _templ, Ou
return true;
}
if (cn==2)
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale,
templ_sum[0],templ_sum[1], templ_sqsum_sum)
.run(2,globalsize,NULL,false);
if (cn == 2)
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols, scale,
templ_sum[0], templ_sum[1], templ_sqsum_sum).run(2, globalsize, NULL, false);
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale,
templ_sum[0],templ_sum[1],templ_sum[2],templ_sum[3], templ_sqsum_sum)
.run(2,globalsize,NULL,false);
ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols, scale,
templ_sum[0], templ_sum[1], templ_sum[2], templ_sum[3],
templ_sqsum_sum).run(2, globalsize, NULL, false);
}
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////
static bool ocl_matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method)
{
int cn = CV_MAT_CN(_img.type());
int cn = _img.channels();
if (cn == 3 || cn > 4)
return false;
typedef bool (*Caller)(InputArray _img, InputArray _templ, OutputArray _result);
const Caller callers[] =
static const Caller callers[] =
{
matchTemplate_SQDIFF, matchTemplate_SQDIFF_NORMED, matchTemplate_CCORR,
matchTemplate_CCORR_NORMED, matchTemplate_CCOEFF, matchTemplate_CCOEFF_NORMED
};
Caller caller = callers[method];
const Caller caller = callers[method];
return caller(_img, _templ, _result);
}
@ -552,17 +513,16 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method )
{
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
CV_Assert( (_img.depth() == CV_8U || _img.depth() == CV_32F) && _img.type() == _templ.type() );
CV_Assert(_img.dims() <= 2);
CV_Assert( (_img.depth() == CV_8U || _img.depth() == CV_32F) && _img.type() == _templ.type() && _img.dims() <= 2 );
bool swapNotNeed = (_img.size().height >= _templ.size().height && _img.size().width >= _templ.size().width);
if (!swapNotNeed)
bool needswap = _img.size().height < _templ.size().height || _img.size().width < _templ.size().width;
if (needswap)
{
CV_Assert(_img.size().height <= _templ.size().height && _img.size().width <= _templ.size().width);
}
CV_OCL_RUN(_img.dims() <= 2 && _result.isUMat(),
(swapNotNeed ? ocl_matchTemplate(_img,_templ,_result,method) : ocl_matchTemplate(_templ,_img,_result,method)))
(!needswap ? ocl_matchTemplate(_img, _templ, _result, method) : ocl_matchTemplate(_templ, _img, _result, method)))
int numType = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
@ -571,7 +531,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
method == CV_TM_CCOEFF_NORMED;
Mat img = _img.getMat(), templ = _templ.getMat();
if(!swapNotNeed )
if (needswap)
std::swap(img, templ);
Size corrSize(img.cols - templ.cols + 1, img.rows - templ.rows + 1);

24
modules/imgproc/test/ocl/test_match_template.cpp
Unescape View File

@ -51,9 +51,12 @@
namespace cvtest {
namespace ocl {
/////////////////////////////////////////////matchTemplate//////////////////////////////////////////////////////////
///////////////////////////////////////////// matchTemplate //////////////////////////////////////////////////////////
PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, int, bool)
CV_ENUM(MatchTemplType, CV_TM_SQDIFF, CV_TM_SQDIFF_NORMED, CV_TM_CCORR,
CV_TM_CCORR_NORMED, CV_TM_CCOEFF, CV_TM_CCOEFF_NORMED)
PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, MatchTemplType, bool)
{
int type;
int depth;
@ -88,7 +91,7 @@ PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, int, bool)
randomSubMat(templ, templ_roi, templ_roiSize, templBorder, type, -upValue, upValue);
Border resultBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
randomSubMat(result, result_roi, result_roiSize, resultBorder, CV_32F, -upValue, upValue);
randomSubMat(result, result_roi, result_roiSize, resultBorder, CV_32FC1, -upValue, upValue);
UMAT_UPLOAD_INPUT_PARAMETER(image)
UMAT_UPLOAD_INPUT_PARAMETER(templ)
@ -97,7 +100,7 @@ PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, int, bool)
void Near(double threshold = 0.0)
{
OCL_EXPECT_MATS_NEAR(result,threshold);
OCL_EXPECT_MATS_NEAR_RELATIVE(result, threshold);
}
};
@ -107,22 +110,19 @@ OCL_TEST_P(MatchTemplate, Mat)
{
generateTestData();
OCL_OFF(cv::matchTemplate(image_roi,templ_roi,result_roi, method));
OCL_ON(cv::matchTemplate(uimage_roi,utempl_roi,uresult_roi, method));
OCL_OFF(cv::matchTemplate(image_roi, templ_roi, result_roi, method));
OCL_ON(cv::matchTemplate(uimage_roi, utempl_roi, uresult_roi, method));
if (method == 0)
Near(10.0f);
else
Near(method % 2 == 1 ? 0.001f : 1.0f);
Near(1.5e-4);
}
}
OCL_INSTANTIATE_TEST_CASE_P(ImageProc, MatchTemplate, Combine(
Values(CV_8U, CV_32F),
Values(1, 2, 4),
Values(0,1,2,3,4,5),
MatchTemplType::all(),
Bool())
);
} } // namespace cvtest::ocl
#endif
#endif

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