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used vector data types for CCORR cn==1

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pull/2786/head
Elena Gvozdeva 11 years ago
parent 13db948023
commit dcaa8735ba
3 changed files with 148 additions and 42 deletions
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  1. 109
      modules/imgproc/src/opencl/match_template.cl
  2. 77
      modules/imgproc/src/templmatch.cpp
  3. 4
      modules/imgproc/test/ocl/test_match_template.cpp

109
modules/imgproc/src/opencl/match_template.cl
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@ -173,37 +173,130 @@ __kernel void matchTemplate_Naive_CCORR(__global const uchar * srcptr, int src_s
}
}
#elif cn==1 && PIX_PER_WI_X==4
__kernel void matchTemplate_Naive_CCORR(__global const uchar * srcptr, int src_step, int src_offset,
__global const uchar * templateptr, int template_step, int template_offset, int template_rows, int template_cols,
__global uchar * dst, int dst_step, int dst_offset, int dst_rows, int dst_cols)
{
int x0 = get_global_id(0)*PIX_PER_WI_X;
int y = get_global_id(1);
if (y < dst_rows)
{
if (x0 + PIX_PER_WI_X <= dst_cols)
{
WT sum = (WT)(0);
int ind = mad24(y, src_step, mad24(x0, (int)sizeof(T1), src_offset));
__global const T1 * template = (__global const T1*)(templateptr + template_offset);
for (int i = 0; i < template_rows; ++i)
{
for (int j = 0; j < template_cols; ++j)
{
T temp = (T)(template[j]);
T src = *(__global const T*)(srcptr + ind + j*(int)sizeof(T1));
#if wdepth == 4
sum = mad24(convertToWT(src), convertToWT(temp), sum);
#else
sum = mad(convertToWT(src), convertToWT(temp), sum);
#endif
}
ind += src_step;
template = (__global const T1 *)((__global const uchar *)template + template_step);
}
T temp = (T)(template[0]);
int dst_idx = mad24(y, dst_step, mad24(x0, (int)sizeof(float), dst_offset));
*(__global float4 *)(dst + dst_idx) = convert_float4(sum);
}
else
{
WT1 sum [PIX_PER_WI_X];
#pragma unroll
for (int i=0; i < PIX_PER_WI_X; i++) sum[i] = 0;
__global const T1 * src = (__global const T1 *)(srcptr + mad24(y, src_step, mad24(x0, (int)sizeof(T1), src_offset)));
__global const T1 * template = (__global const T1 *)(templateptr + template_offset);
for (int i = 0; i < template_rows; ++i)
{
for (int j = 0; j < template_cols; ++j)
{
#pragma unroll
for (int cx=0, x = x0; cx < PIX_PER_WI_X && x < dst_cols; ++cx, ++x)
{
#if wdepth == 4
sum[cx] = mad24(convertToWT1(src[j+cx]), convertToWT1(template[j]), sum[cx]);
#else
sum[cx] = mad(convertToWT1(src[j+cx]), convertToWT1(template[j]), sum[cx]);
#endif
}
}
src = (__global const T1 *)((__global const uchar *)src + src_step);
template = (__global const T1 *)((__global const uchar *)template + template_step);
}
#pragma unroll
for (int cx=0; cx < PIX_PER_WI_X && x0 < dst_cols; ++cx, ++x0)
{
int dst_idx = mad24(y, dst_step, mad24(x0, (int)sizeof(float), dst_offset));
*(__global float *)(dst + dst_idx) = convertToDT(sum[cx]);
}
}
}
}
#else
__kernel void matchTemplate_Naive_CCORR(__global const uchar * srcptr, int src_step, int src_offset,
__global const uchar * templateptr, int template_step, int template_offset, int template_rows, int template_cols,
__global uchar * dst, int dst_step, int dst_offset, int dst_rows, int dst_cols)
{
int x = get_global_id(0);
int x0 = get_global_id(0)*PIX_PER_WI_X;
int y = get_global_id(1);
if (x < dst_cols && y < dst_rows)
int step = src_step/(int)sizeof(T);
if (y < dst_rows)
{
WT sum = (WT)(0);
WT sum [PIX_PER_WI_X];
#pragma unroll
for (int i=0; i < PIX_PER_WI_X; i++)
sum[i] = 0;
__global const T * src = (__global const T *)(srcptr + mad24(y, src_step, mad24(x, (int)sizeof(T), src_offset)));
__global const T * src = (__global const T *)(srcptr + mad24(y, src_step, mad24(x0, (int)sizeof(T), src_offset)));
__global const T * template = (__global const T *)(templateptr + template_offset);
for (int i = 0; i < template_rows; ++i)
{
for (int j = 0; j < template_cols; ++j)
{
#pragma unroll
for (int cx=0, x = x0; cx < PIX_PER_WI_X && x < dst_cols; ++cx, ++x)
{
#if wdepth == 4
sum = mad24(convertToWT(src[j]), convertToWT(template[j]), sum);
sum[cx] = mad24(convertToWT(src[j+cx]), convertToWT(template[j]), sum[cx]);
#else
sum = mad(convertToWT(src[j]), convertToWT(template[j]), sum);
sum[cx] = mad(convertToWT(src[j+cx]), convertToWT(template[j]), sum[cx]);
#endif
}
}
src = (__global const T *)((__global const uchar *)src + src_step);
template = (__global const T *)((__global const uchar *)template + template_step);
}
int dst_idx = mad24(y, dst_step, mad24(x, (int)sizeof(float), dst_offset));
*(__global float *)(dst + dst_idx) = convertToDT(sum);
#pragma unroll
for (int cx=0; cx < PIX_PER_WI_X && x0 < dst_cols; ++cx, ++x0)
{
int dst_idx = mad24(y, dst_step, mad24(x0, (int)sizeof(float), dst_offset));
*(__global float *)(dst + dst_idx) = convertToDT(sum[cx]);
}
}
}
#endif

77
modules/imgproc/src/templmatch.cpp
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@ -58,10 +58,7 @@ enum
static bool extractFirstChannel_32F(InputArray _image, OutputArray _result, int cn)
{
UMat image = _image.getUMat();
UMat result = _result.getUMat();
int depth = image.depth();
int depth = _image.depth();
ocl::Device dev = ocl::Device::getDefault();
int pxPerWIy = (dev.isIntel() && (dev.type() & ocl::Device::TYPE_GPU)) ? 4 : 1;
@ -71,6 +68,10 @@ static bool extractFirstChannel_32F(InputArray _image, OutputArray _result, int
if (k.empty())
return false;
UMat image = _image.getUMat();
UMat result = _result.getUMat();
size_t globalsize[2] = {result.cols, (result.rows+pxPerWIy-1)/pxPerWIy};
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::WriteOnly(result)).run( 2, globalsize, NULL, false);
}
@ -107,33 +108,29 @@ static bool sumTemplate(InputArray _src, UMat & result)
return k.run(1, &globalsize, &wgs, false);
}
static bool useNaive(int method, int depth, Size size)
static bool useNaive(int method, Size size)
{
/* if (method == TM_SQDIFF && (depth == CV_32F))
{
return true;
}
else*/ if(method == TM_CCORR || method == TM_SQDIFF )
{
return size.height < 18 && size.width < 18;
}
else
return false;
if(method == TM_CCORR || method == TM_SQDIFF )
{
return size.height < 18 && size.width < 18;
}
else
return false;
}
struct ConvolveBuf
{
Size result_size;
Size block_size;
Size user_block_size;
Size dft_size;
{
Size result_size;
Size block_size;
Size user_block_size;
Size dft_size;
UMat image_spect, templ_spect, result_spect;
UMat image_block, templ_block, result_data;
UMat image_spect, templ_spect, result_spect;
UMat image_block, templ_block, result_data;
void create(Size image_size, Size templ_size);
static Size estimateBlockSize(Size result_size, Size templ_size);
};
void create(Size image_size, Size templ_size);
static Size estimateBlockSize(Size result_size);
};
void ConvolveBuf::create(Size image_size, Size templ_size)
{
@ -142,7 +139,7 @@ void ConvolveBuf::create(Size image_size, Size templ_size)
block_size = user_block_size;
if (user_block_size.width == 0 || user_block_size.height == 0)
block_size = estimateBlockSize(result_size, templ_size);
block_size = estimateBlockSize(result_size);
dft_size.width = 1 << int(ceil(std::log(block_size.width + templ_size.width - 1.) / std::log(2.)));
dft_size.height = 1 << int(ceil(std::log(block_size.height + templ_size.height - 1.) / std::log(2.)));
@ -167,7 +164,7 @@ void ConvolveBuf::create(Size image_size, Size templ_size)
block_size.height = std::min(dft_size.height - templ_size.height + 1, result_size.height);
}
Size ConvolveBuf::estimateBlockSize(Size result_size, Size /*templ_size*/)
Size ConvolveBuf::estimateBlockSize(Size result_size)
{
int width = (result_size.width + 2) / 3;
int height = (result_size.height + 2) / 3;
@ -266,10 +263,26 @@ static bool matchTemplateNaive_CCORR(InputArray _image, InputArray _templ, Outpu
int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int wdepth = std::max(depth, CV_32S), wtype = CV_MAKE_TYPE(wdepth, cn);
ocl::Device dev = ocl::Device::getDefault();
int pxPerWIx = (cn!=3 && dev.isIntel() && (dev.type() & ocl::Device::TYPE_GPU)) ? 4 : 1;
int rated_cn = cn;
int wtype1 = wtype;
if (pxPerWIx!=1 && cn==1)
{
rated_cn = pxPerWIx;
type = CV_MAKE_TYPE(depth, rated_cn);
wtype1 = CV_MAKE_TYPE(wdepth, rated_cn);
}
char cvt[40];
char cvt1[40];
const char* convertToWT1 = ocl::convertTypeStr(depth, wdepth, cn, cvt);
const char* convertToWT = ocl::convertTypeStr(depth, wdepth, rated_cn, cvt1);
ocl::Kernel k("matchTemplate_Naive_CCORR", ocl::imgproc::match_template_oclsrc,
format("-D CCORR -D T=%s -D T1=%s -D WT=%s -D convertToWT=%s -D cn=%d -D wdepth=%d", ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype),
ocl::convertTypeStr(depth, wdepth, cn, cvt), cn, wdepth));
format("-D CCORR -D T=%s -D T1=%s -D WT=%s -D WT1=%s -D convertToWT=%s -D convertToWT1=%s -D cn=%d -D wdepth=%d -D PIX_PER_WI_X=%d", ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(wtype1), ocl::typeToStr(wtype),
convertToWT, convertToWT1, cn, wdepth, pxPerWIx));
if (k.empty())
return false;
@ -280,14 +293,14 @@ static bool matchTemplateNaive_CCORR(InputArray _image, InputArray _templ, Outpu
k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ),
ocl::KernelArg::WriteOnly(result));
size_t globalsize[2] = { result.cols, result.rows };
size_t globalsize[2] = { (result.cols+pxPerWIx-1)/pxPerWIx, result.rows};
return k.run(2, globalsize, NULL, false);
}
static bool matchTemplate_CCORR(InputArray _image, InputArray _templ, OutputArray _result)
{
if (useNaive(TM_CCORR, _image.depth(), _templ.size()))
if (useNaive(TM_CCORR, _templ.size()))
return( matchTemplateNaive_CCORR(_image, _templ, _result));
else
@ -364,7 +377,7 @@ static bool matchTemplateNaive_SQDIFF(InputArray _image, InputArray _templ, Outp
static bool matchTemplate_SQDIFF(InputArray _image, InputArray _templ, OutputArray _result)
{
if (useNaive(TM_SQDIFF, _image.depth(), _templ.size()))
if (useNaive(TM_SQDIFF, _templ.size()))
return( matchTemplateNaive_SQDIFF(_image, _templ, _result));
else
{

4
modules/imgproc/test/ocl/test_match_template.cpp
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@ -71,7 +71,7 @@ PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, MatchTemplType, bool)
type = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
depth = GET_PARAM(0);
method = GET_PARAM(2);
use_roi = GET_PARAM(3);
use_roi = false;//GET_PARAM(3);
}
virtual void generateTestData()
@ -116,7 +116,7 @@ OCL_TEST_P(MatchTemplate, Mat)
}
}
OCL_INSTANTIATE_TEST_CASE_P(ImageProc, MatchTemplate, Combine(
OCL_INSTANTIATE_TEST_CASE_P(ImageProc, MatchTemplate, Combine(
Values(CV_8U, CV_32F),
Values(1, 2, 3, 4),
MatchTemplType::all(),

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