Skip to content

O
opencv
Commit dfe7c980 authored by krodyush's avatar krodyush
Browse files
Options

optimize separable filter by 

Added "sep_filter_singlepass" kernel that performs separable filtering in one kernel call
Added appropriate host part - sepFilter2D_SinglePass function and SingleStepSeparableFilterEngine_GPU class
Changed function declarations to enable their usage
parent 5d5527d0
Hide whitespace changes
Inline Side-by-side
Showing with 369 additions and 14 deletions
modules/ocl/include/opencv2/ocl/ocl.hpp
View file @ dfe7c980
......@@ -706,17 +706,17 @@ namespace cv
//! returns the separable linear filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat &rowKernel,
const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT);
const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1));
//! returns the separable filter engine with the specified filters
CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableFilter_GPU(const Ptr<BaseRowFilter_GPU> &rowFilter,
const Ptr<BaseColumnFilter_GPU> &columnFilter);
//! returns the Gaussian filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT);
CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1));
//! returns filter engine for the generalized Sobel operator
CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT );
CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT, Size imgSize = Size(-1,-1) );
//! applies Laplacian operator to the image
// supports only ksize = 1 and ksize = 3
......@@ -869,7 +869,6 @@ namespace cv
CV_EXPORTS void cornerMinEigenVal(const oclMat &src, oclMat &dst, int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
CV_EXPORTS void cornerMinEigenVal_dxdy(const oclMat &src, oclMat &dst, oclMat &Dx, oclMat &Dy,
int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
/////////////////////////////////// ML ///////////////////////////////////////////
//! Compute closest centers for each lines in source and lable it after center's index
......
modules/ocl/src/filtering.cpp
View file @ dfe7c980
......@@ -739,6 +739,135 @@ void cv::ocl::filter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &ke
f->apply(src, dst);
}
const int optimizedSepFilterLocalSize = 16;
static void sepFilter2D_SinglePass(const oclMat &src, oclMat &dst,
const Mat &row_kernel, const Mat &col_kernel, int bordertype = BORDER_DEFAULT)
{
size_t lt2[3] = {optimizedSepFilterLocalSize, optimizedSepFilterLocalSize, 1};
size_t gt2[3] = {lt2[0]*(1 + (src.cols-1) / lt2[0]), lt2[1]*(1 + (src.rows-1) / lt2[1]), 1};
unsigned int src_pitch = src.step;
unsigned int dst_pitch = dst.step;
int src_offset_x = (src.offset % src.step) / src.elemSize();
int src_offset_y = src.offset / src.step;
std::vector<std::pair<size_t , const void *> > args;
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&src.data ));
args.push_back( std::make_pair( sizeof(cl_uint) , (void *)&src_pitch ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src_offset_x ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src_offset_y ));
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.offset ));
args.push_back( std::make_pair( sizeof(cl_uint) , (void *)&dst_pitch ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.wholecols ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.wholerows ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.cols ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.rows ));
string option = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUSX=%d -D RADIUSY=%d",(int)lt2[0], (int)lt2[1],
row_kernel.rows / 2, col_kernel.rows / 2 );
option += " -D KERNEL_MATRIX_X=";
for(int i=0; i<row_kernel.rows; i++)
option += cv::format("0x%x,", *reinterpret_cast<const unsigned int*>( &row_kernel.at<float>(i) ) );
option += "0x0";
option += " -D KERNEL_MATRIX_Y=";
for(int i=0; i<col_kernel.rows; i++)
option += cv::format("0x%x,", *reinterpret_cast<const unsigned int*>( &col_kernel.at<float>(i) ) );
option += "0x0";
switch(src.type())
{
case CV_8UC1:
option += " -D SRCTYPE=uchar -D CONVERT_SRCTYPE=convert_float -D WORKTYPE=float";
break;
case CV_32FC1:
option += " -D SRCTYPE=float -D CONVERT_SRCTYPE= -D WORKTYPE=float";
break;
case CV_8UC2:
option += " -D SRCTYPE=uchar2 -D CONVERT_SRCTYPE=convert_float2 -D WORKTYPE=float2";
break;
case CV_32FC2:
option += " -D SRCTYPE=float2 -D CONVERT_SRCTYPE= -D WORKTYPE=float2";
break;
case CV_8UC3:
option += " -D SRCTYPE=uchar3 -D CONVERT_SRCTYPE=convert_float3 -D WORKTYPE=float3";
break;
case CV_32FC3:
option += " -D SRCTYPE=float3 -D CONVERT_SRCTYPE= -D WORKTYPE=float3";
break;
case CV_8UC4:
option += " -D SRCTYPE=uchar4 -D CONVERT_SRCTYPE=convert_float4 -D WORKTYPE=float4";
break;
case CV_32FC4:
option += " -D SRCTYPE=float4 -D CONVERT_SRCTYPE= -D WORKTYPE=float4";
break;
default:
CV_Error(CV_StsUnsupportedFormat, "Image type is not supported!");
break;
}
switch(dst.type())
{
case CV_8UC1:
option += " -D DSTTYPE=uchar -D CONVERT_DSTTYPE=convert_uchar_sat";
break;
case CV_8UC2:
option += " -D DSTTYPE=uchar2 -D CONVERT_DSTTYPE=convert_uchar2_sat";
break;
case CV_8UC3:
option += " -D DSTTYPE=uchar3 -D CONVERT_DSTTYPE=convert_uchar3_sat";
break;
case CV_8UC4:
option += " -D DSTTYPE=uchar4 -D CONVERT_DSTTYPE=convert_uchar4_sat";
break;
case CV_32FC1:
option += " -D DSTTYPE=float -D CONVERT_DSTTYPE=";
break;
case CV_32FC2:
option += " -D DSTTYPE=float2 -D CONVERT_DSTTYPE=";
break;
case CV_32FC3:
option += " -D DSTTYPE=float3 -D CONVERT_DSTTYPE=";
break;
case CV_32FC4:
option += " -D DSTTYPE=float4 -D CONVERT_DSTTYPE=";
break;
default:
CV_Error(CV_StsUnsupportedFormat, "Image type is not supported!");
break;
}
switch(bordertype)
{
case cv::BORDER_CONSTANT:
option += " -D BORDER_CONSTANT";
break;
case cv::BORDER_REPLICATE:
option += " -D BORDER_REPLICATE";
break;
case cv::BORDER_REFLECT:
option += " -D BORDER_REFLECT";
break;
case cv::BORDER_REFLECT101:
option += " -D BORDER_REFLECT_101";
break;
case cv::BORDER_WRAP:
option += " -D BORDER_WRAP";
break;
default:
CV_Error(CV_StsBadFlag, "BORDER type is not supported!");
break;
}
openCLExecuteKernel(src.clCxt, &filtering_sep_filter_singlepass, "sep_filter_singlepass", gt2, lt2, args,
-1, -1, option.c_str() );
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// SeparableFilter
......@@ -788,6 +917,35 @@ Ptr<FilterEngine_GPU> cv::ocl::createSeparableFilter_GPU(const Ptr<BaseRowFilter
return Ptr<FilterEngine_GPU>(new SeparableFilterEngine_GPU(rowFilter, columnFilter));
}
namespace
{
class SingleStepSeparableFilterEngine_GPU : public FilterEngine_GPU
{
public:
SingleStepSeparableFilterEngine_GPU( const Mat &rowKernel_, const Mat &columnKernel_, const int btype )
{
bordertype = btype;
rowKernel = rowKernel_;
columnKernel = columnKernel_;
}
virtual void apply(const oclMat &src, oclMat &dst, Rect roi = Rect(0, 0, -1, -1))
{
normalizeROI(roi, Size(rowKernel.rows, columnKernel.rows), Point(-1,-1), src.size());
oclMat srcROI = src(roi);
oclMat dstROI = dst(roi);
sepFilter2D_SinglePass(src, dst, rowKernel, columnKernel, bordertype);
}
Mat rowKernel;
Mat columnKernel;
int bordertype;
};
}
static void GPUFilterBox(const oclMat &src, oclMat &dst,
Size &ksize, const Point anchor, const int borderType)
{
......@@ -1241,17 +1399,30 @@ Ptr<BaseColumnFilter_GPU> cv::ocl::getLinearColumnFilter_GPU(int /*bufType*/, in
}
Ptr<FilterEngine_GPU> cv::ocl::createSeparableLinearFilter_GPU(int srcType, int dstType,
const Mat &rowKernel, const Mat &columnKernel, const Point &anchor, double delta, int bordertype)
const Mat &rowKernel, const Mat &columnKernel, const Point &anchor, double delta, int bordertype, Size imgSize )
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(dstType);
int cn = CV_MAT_CN(srcType);
int bdepth = std::max(std::max(sdepth, ddepth), CV_32F);
int bufType = CV_MAKETYPE(bdepth, cn);
Ptr<BaseRowFilter_GPU> rowFilter = getLinearRowFilter_GPU(srcType, bufType, rowKernel, anchor.x, bordertype);
Ptr<BaseColumnFilter_GPU> columnFilter = getLinearColumnFilter_GPU(bufType, dstType, columnKernel, anchor.y, bordertype, delta);
//if image size is non-degenerate and large enough
//and if filter support is reasonable to satisfy larger local memory requirements,
//then we can use single pass routine to avoid extra runtime calls overhead
if( rowKernel.rows <= 21 && columnKernel.rows <= 21 &&
(rowKernel.rows & 1) == 1 && (columnKernel.rows & 1) == 1 &&
imgSize.width > optimizedSepFilterLocalSize + (rowKernel.rows>>1) &&
imgSize.height > optimizedSepFilterLocalSize + (columnKernel.rows>>1) )
{
return Ptr<FilterEngine_GPU>(new SingleStepSeparableFilterEngine_GPU(rowKernel, columnKernel, bordertype));
}
else
{
Ptr<BaseRowFilter_GPU> rowFilter = getLinearRowFilter_GPU(srcType, bufType, rowKernel, anchor.x, bordertype);
Ptr<BaseColumnFilter_GPU> columnFilter = getLinearColumnFilter_GPU(bufType, dstType, columnKernel, anchor.y, bordertype, delta);
return createSeparableFilter_GPU(rowFilter, columnFilter);
return createSeparableFilter_GPU(rowFilter, columnFilter);
}
}
void cv::ocl::sepFilter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &kernelX, const Mat &kernelY, Point anchor, double delta, int bordertype)
......@@ -1275,16 +1446,16 @@ void cv::ocl::sepFilter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat
dst.create(src.size(), CV_MAKETYPE(ddepth, src.channels()));
Ptr<FilterEngine_GPU> f = createSeparableLinearFilter_GPU(src.type(), dst.type(), kernelX, kernelY, anchor, delta, bordertype);
Ptr<FilterEngine_GPU> f = createSeparableLinearFilter_GPU(src.type(), dst.type(), kernelX, kernelY, anchor, delta, bordertype, src.size());
f->apply(src, dst);
}
Ptr<FilterEngine_GPU> cv::ocl::createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int borderType)
Ptr<FilterEngine_GPU> cv::ocl::createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int borderType, Size imgSize )
{
Mat kx, ky;
getDerivKernels(kx, ky, dx, dy, ksize, false, CV_32F);
return createSeparableLinearFilter_GPU(srcType, dstType,
kx, ky, Point(-1, -1), 0, borderType);
kx, ky, Point(-1, -1), 0, borderType, imgSize);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
......@@ -1354,7 +1525,7 @@ void cv::ocl::Laplacian(const oclMat &src, oclMat &dst, int ddepth, int ksize, d
////////////////////////////////////////////////////////////////////////////////////////////////////
// Gaussian Filter
Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2, int bordertype)
Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2, int bordertype, Size imgSize)
{
int depth = CV_MAT_DEPTH(type);
......@@ -1381,7 +1552,7 @@ Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, do
else
ky = getGaussianKernel(ksize.height, sigma2, std::max(depth, CV_32F));
return createSeparableLinearFilter_GPU(type, type, kx, ky, Point(-1, -1), 0.0, bordertype);
return createSeparableLinearFilter_GPU(type, type, kx, ky, Point(-1, -1), 0.0, bordertype, imgSize);
}
void cv::ocl::GaussianBlur(const oclMat &src, oclMat &dst, Size ksize, double sigma1, double sigma2, int bordertype)
......@@ -1417,7 +1588,7 @@ void cv::ocl::GaussianBlur(const oclMat &src, oclMat &dst, Size ksize, double si
dst.create(src.size(), src.type());
Ptr<FilterEngine_GPU> f = createGaussianFilter_GPU(src.type(), ksize, sigma1, sigma2, bordertype);
Ptr<FilterEngine_GPU> f = createGaussianFilter_GPU(src.type(), ksize, sigma1, sigma2, bordertype, src.size());
f->apply(src, dst);
}
......
modules/ocl/src/opencl/filtering_sep_filter_singlepass.cl 0 → 100644
View file @ dfe7c980
/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, 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 the copyright holders 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*/
///////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////Macro for border type////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////////////////
#ifdef BORDER_CONSTANT
//CCCCCC|abcdefgh|CCCCCCC
#define EXTRAPOLATE(x, maxV)
#elif defined BORDER_REPLICATE
//aaaaaa|abcdefgh|hhhhhhh
#define EXTRAPOLATE(x, maxV) \
{ \
(x) = max(min((x), (maxV) - 1), 0); \
}
#elif defined BORDER_WRAP
//cdefgh|abcdefgh|abcdefg
#define EXTRAPOLATE(x, maxV) \
{ \
(x) = ( (x) + (maxV) ) % (maxV); \
}
#elif defined BORDER_REFLECT
//fedcba|abcdefgh|hgfedcb
#define EXTRAPOLATE(x, maxV) \
{ \
(x) = min(((maxV)-1)*2-(x)+1, max((x),-(x)-1) ); \
}
#elif defined BORDER_REFLECT_101
//gfedcb|abcdefgh|gfedcba
#define EXTRAPOLATE(x, maxV) \
{ \
(x) = min(((maxV)-1)*2-(x), max((x),-(x)) ); \
}
#else
#error No extrapolation method
#endif
#define SRC(_x,_y) CONVERT_SRCTYPE(((global SRCTYPE*)(Src+(_y)*SrcPitch))[_x])
#ifdef BORDER_CONSTANT
//CCCCCC|abcdefgh|CCCCCCC
#define ELEM(_x,_y,r_edge,t_edge,const_v) (_x)<0 | (_x) >= (r_edge) | (_y)<0 | (_y) >= (t_edge) ? (const_v) : SRC((_x),(_y))
#else
#define ELEM(_x,_y,r_edge,t_edge,const_v) SRC((_x),(_y))
#endif
#define DST(_x,_y) (((global DSTTYPE*)(Dst+DstOffset+(_y)*DstPitch))[_x])
//horizontal and vertical filter kernels
//should be defined on host during compile time to avoid overhead
__constant uint mat_kernelX[] = {KERNEL_MATRIX_X};
__constant uint mat_kernelY[] = {KERNEL_MATRIX_Y};
__kernel __attribute__((reqd_work_group_size(BLK_X,BLK_Y,1))) void sep_filter_singlepass
(
__global uchar* Src,
const uint SrcPitch,
const int srcOffsetX,
const int srcOffsetY,
__global uchar* Dst,
const int DstOffset,
const uint DstPitch,
int width,
int height,
int dstWidth,
int dstHeight
)
{
//RADIUSX, RADIUSY are filter dimensions
//BLK_X, BLK_Y are local wrogroup sizes
//all these should be defined on host during compile time
//first lsmem array for source pixels used in first pass,
//second lsmemDy for storing first pass results
__local WORKTYPE lsmem[BLK_Y+2*RADIUSY][BLK_X+2*RADIUSX];
__local WORKTYPE lsmemDy[BLK_Y][BLK_X+2*RADIUSX];
//get local and global ids - used as image and local memory array indexes
int lix = get_local_id(0);
int liy = get_local_id(1);
int x = (int)get_global_id(0);
int y = (int)get_global_id(1);
//calculate pixel position in source image taking image offset into account
int srcX = x + srcOffsetX - RADIUSX;
int srcY = y + srcOffsetY - RADIUSY;
int xb = srcX;
int yb = srcY;
//extrapolate coordinates, if needed
//and read my own source pixel into local memory
//with account for extra border pixels, which will be read by starting workitems
int clocY = liy;
int cSrcY = srcY;
do
{
int yb = cSrcY;
EXTRAPOLATE(yb, (height));
int clocX = lix;
int cSrcX = srcX;
do
{
int xb = cSrcX;
EXTRAPOLATE(xb,(width));
lsmem[clocY][clocX] = ELEM(xb, yb, (width), (height), 0 );
clocX += BLK_X;
cSrcX += BLK_X;
}
while(clocX < BLK_X+(RADIUSX*2));
clocY += BLK_Y;
cSrcY += BLK_Y;
}
while(clocY < BLK_Y+(RADIUSY*2));
barrier(CLK_LOCAL_MEM_FENCE);
//do vertical filter pass
//and store intermediate results to second local memory array
int i;
WORKTYPE sum = 0.0f;
int clocX = lix;
do
{
sum = 0.0f;
for(i=0; i<=2*RADIUSY; i++)
sum = mad(lsmem[liy+i][clocX], as_float(mat_kernelY[i]), sum);
lsmemDy[liy][clocX] = sum;
clocX += BLK_X;
}
while(clocX < BLK_X+(RADIUSX*2));
barrier(CLK_LOCAL_MEM_FENCE);
//if this pixel happened to be out of image borders because of global size rounding,
//then just return
if( x >= dstWidth || y >=dstHeight ) return;
//do second horizontal filter pass
//and calculate final result
sum = 0.0f;
for(i=0; i<=2*RADIUSX; i++)
sum = mad(lsmemDy[liy][lix+i], as_float(mat_kernelX[i]), sum);
//store result into destination image
DST(x,y) = CONVERT_DSTTYPE(sum);
}
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment