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opencv/modules/imgproc/src/deriv.cpp

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/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Copyright (C) 2014, Itseez, Inc, 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 Intel Corporation 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*/
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "filter.hpp"
/****************************************************************************************\
Sobel & Scharr Derivative Filters
\****************************************************************************************/
namespace cv
{
static void getScharrKernels( OutputArray _kx, OutputArray _ky,
int dx, int dy, bool normalize, int ktype )
{
const int ksize = 3;
CV_Assert( ktype == CV_32F || ktype == CV_64F );
_kx.create(ksize, 1, ktype, -1, true);
_ky.create(ksize, 1, ktype, -1, true);
Mat kx = _kx.getMat();
Mat ky = _ky.getMat();
CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 );
for( int k = 0; k < 2; k++ )
{
Mat* kernel = k == 0 ? &kx : &ky;
int order = k == 0 ? dx : dy;
int kerI[3];
if( order == 0 )
kerI[0] = 3, kerI[1] = 10, kerI[2] = 3;
else if( order == 1 )
kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;
Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]);
double scale = !normalize || order == 1 ? 1. : 1./32;
temp.convertTo(*kernel, ktype, scale);
}
}
static void getSobelKernels( OutputArray _kx, OutputArray _ky,
int dx, int dy, int _ksize, bool normalize, int ktype )
{
int i, j, ksizeX = _ksize, ksizeY = _ksize;
if( ksizeX == 1 && dx > 0 )
ksizeX = 3;
if( ksizeY == 1 && dy > 0 )
ksizeY = 3;
CV_Assert( ktype == CV_32F || ktype == CV_64F );
_kx.create(ksizeX, 1, ktype, -1, true);
_ky.create(ksizeY, 1, ktype, -1, true);
Mat kx = _kx.getMat();
Mat ky = _ky.getMat();
if( _ksize % 2 == 0 || _ksize > 31 )
CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" );
std::vector<int> kerI(std::max(ksizeX, ksizeY) + 1);
CV_Assert( dx >= 0 && dy >= 0 && dx+dy > 0 );
for( int k = 0; k < 2; k++ )
{
Mat* kernel = k == 0 ? &kx : &ky;
int order = k == 0 ? dx : dy;
int ksize = k == 0 ? ksizeX : ksizeY;
CV_Assert( ksize > order );
if( ksize == 1 )
kerI[0] = 1;
else if( ksize == 3 )
{
if( order == 0 )
kerI[0] = 1, kerI[1] = 2, kerI[2] = 1;
else if( order == 1 )
kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;
else
kerI[0] = 1, kerI[1] = -2, kerI[2] = 1;
}
else
{
int oldval, newval;
kerI[0] = 1;
for( i = 0; i < ksize; i++ )
kerI[i+1] = 0;
for( i = 0; i < ksize - order - 1; i++ )
{
oldval = kerI[0];
for( j = 1; j <= ksize; j++ )
{
newval = kerI[j]+kerI[j-1];
kerI[j-1] = oldval;
oldval = newval;
}
}
for( i = 0; i < order; i++ )
{
oldval = -kerI[0];
for( j = 1; j <= ksize; j++ )
{
newval = kerI[j-1] - kerI[j];
kerI[j-1] = oldval;
oldval = newval;
}
}
}
Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]);
double scale = !normalize ? 1. : 1./(1 << (ksize-order-1));
temp.convertTo(*kernel, ktype, scale);
}
}
}
void cv::getDerivKernels( OutputArray kx, OutputArray ky, int dx, int dy,
int ksize, bool normalize, int ktype )
{
if( ksize <= 0 )
getScharrKernels( kx, ky, dx, dy, normalize, ktype );
else
getSobelKernels( kx, ky, dx, dy, ksize, normalize, ktype );
}
cv::Ptr<cv::FilterEngine> cv::createDerivFilter(int srcType, int dstType,
int dx, int dy, int ksize, int borderType )
{
Mat kx, ky;
getDerivKernels( kx, ky, dx, dy, ksize, false, CV_32F );
return createSeparableLinearFilter(srcType, dstType,
kx, ky, Point(-1,-1), 0, borderType );
}
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_SOBEL_3x3>(int w, int h) { return w*h < 320 * 240; }
}
static bool openvx_sobel(InputArray _src, OutputArray _dst,
int dx, int dy, int ksize,
double scale, double delta, int borderType)
{
if (_src.type() != CV_8UC1 || _dst.type() != CV_16SC1 ||
ksize != 3 || scale != 1.0 || delta != 0.0 ||
(dx | dy) != 1 || (dx + dy) != 1 ||
_src.cols() < ksize || _src.rows() < ksize ||
ovx::skipSmallImages<VX_KERNEL_SOBEL_3x3>(_src.cols(), _src.rows())
)
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
// border = VX_BORDER_REPLICATE;
// break;
default:
return false;
}
try
{
ivx::Context ctx = ovx::getOpenVXContext();
//if ((vx_size)ksize > ctx.convolutionMaxDimension())
// return false;
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_S16,
ivx::Image::createAddressing(dst.cols, dst.rows, 2, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
if(dx)
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, ib, NULL));
else
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, NULL, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
}
#endif
#if 0 //defined HAVE_IPP
namespace cv
{
static bool ipp_Deriv(InputArray _src, OutputArray _dst, int dx, int dy, int ksize, double scale, double delta, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
::ipp::IwiSize size(_src.size().width, _src.size().height);
IppDataType srcType = ippiGetDataType(_src.depth());
IppDataType dstType = ippiGetDataType(_dst.depth());
int channels = _src.channels();
bool useScale = false;
bool useScharr = false;
if(channels != _dst.channels() || channels > 1)
return false;
if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON)
useScale = true;
if(ksize <= 0)
{
ksize = 3;
useScharr = true;
}
IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize);
if((int)maskSize < 0)
return false;
#if IPP_VERSION_X100 <= 201703
// Bug with mirror wrap
if(borderType == BORDER_REFLECT_101 && (ksize/2+1 > size.width || ksize/2+1 > size.height))
return false;
#endif
IwiDerivativeType derivType = ippiGetDerivType(dx, dy, (useScharr)?false:true);
if((int)derivType < 0)
return false;
// Acquire data and begin processing
try
{
Mat src = _src.getMat();
Mat dst = _dst.getMat();
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiImage iwSrcProc = iwSrc;
::ipp::IwiImage iwDstProc = iwDst;
::ipp::IwiBorderSize borderSize(maskSize);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
if(srcType == ipp8u && dstType == ipp8u)
{
iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
useScale = true;
}
else if(srcType == ipp8u && dstType == ipp32f)
{
iwSrc -= borderSize;
iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0, ::ipp::IwiScaleParams(ippAlgHintFast));
iwSrcProc += borderSize;
}
if(useScharr)
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterScharr, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder);
else
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterSobel, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder);
if(useScale)
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta, ::ipp::IwiScaleParams(ippAlgHintFast));
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(dx); CV_UNUSED(dy); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType);
return false;
#endif
}
}
#endif
#ifdef HAVE_OPENCL
namespace cv
{
static bool ocl_sepFilter3x3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
InputArray _kernelX, InputArray _kernelY, double delta, int borderType)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
return false;
Mat kernelX = _kernelX.getMat().reshape(1, 1);
if (kernelX.cols % 2 != 1)
return false;
Mat kernelY = _kernelY.getMat().reshape(1, 1);
if (kernelY.cols % 2 != 1)
return false;
if (ddepth < 0)
ddepth = sdepth;
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
char build_opts[1024];
sprintf(build_opts, "-D %s %s%s", borderMap[borderType],
ocl::kernelToStr(kernelX, CV_32F, "KERNEL_MATRIX_X").c_str(),
ocl::kernelToStr(kernelY, CV_32F, "KERNEL_MATRIX_Y").c_str());
ocl::Kernel kernel("sepFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::sepFilter3x3_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
idxArg = kernel.set(idxArg, static_cast<float>(delta));
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
}
#endif
void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
int ksize, double scale, double delta, int borderType )
{
CV_INSTRUMENT_REGION();
CV_Assert(!_src.empty());
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if (ddepth < 0)
ddepth = sdepth;
int dtype = CV_MAKE_TYPE(ddepth, cn);
_dst.create( _src.size(), dtype );
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
Mat kx, ky;
getDerivKernels( kx, ky, dx, dy, ksize, false, ktype );
if( scale != 1 )
{
// usually the smoothing part is the slowest to compute,
// so try to scale it instead of the faster differentiating part
if( dx == 0 )
kx *= scale;
else
ky *= scale;
}
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && ksize == 3 &&
(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType))
Mat src = _src.getMat();
Mat dst = _dst.getMat();
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType & BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(sobel, cv_hal_sobel, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, ksize, scale, delta, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_sobel(src, dst, dx, dy, ksize, scale, delta, borderType))
//CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, ksize, scale, delta, borderType));
sepFilter2D(src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType );
}
void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
double scale, double delta, int borderType )
{
CV_INSTRUMENT_REGION();
CV_Assert(!_src.empty());
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if (ddepth < 0)
ddepth = sdepth;
int dtype = CV_MAKETYPE(ddepth, cn);
_dst.create( _src.size(), dtype );
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
Mat kx, ky;
getScharrKernels( kx, ky, dx, dy, false, ktype );
if( scale != 1 )
{
// usually the smoothing part is the slowest to compute,
// so try to scale it instead of the faster differentiating part
if( dx == 0 )
kx *= scale;
else
ky *= scale;
}
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
(size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType));
CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
(size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType))
Mat src = _src.getMat();
Mat dst = _dst.getMat();
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType & BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(scharr, cv_hal_scharr, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, scale, delta, borderType&~BORDER_ISOLATED);
//CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, 0, scale, delta, borderType));
sepFilter2D( src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType );
}
#ifdef HAVE_OPENCL
namespace cv {
#define LAPLACIAN_LOCAL_MEM(tileX, tileY, ksize, elsize) (((tileX) + 2 * (int)((ksize) / 2)) * (3 * (tileY) + 2 * (int)((ksize) / 2)) * elsize)
static bool ocl_Laplacian5(InputArray _src, OutputArray _dst,
const Mat & kd, const Mat & ks, double scale, double delta,
int borderType, int depth, int ddepth)
{
const size_t tileSizeX = 16;
const size_t tileSizeYmin = 8;
const ocl::Device dev = ocl::Device::getDefault();
int stype = _src.type();
int sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype), esz = CV_ELEM_SIZE(stype);
bool doubleSupport = dev.doubleFPConfig() > 0;
if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
return false;
Mat kernelX = kd.reshape(1, 1);
if (kernelX.cols % 2 != 1)
return false;
Mat kernelY = ks.reshape(1, 1);
if (kernelY.cols % 2 != 1)
return false;
CV_Assert(kernelX.cols == kernelY.cols);
size_t wgs = dev.maxWorkGroupSize();
size_t lmsz = dev.localMemSize();
size_t src_step = _src.step(), src_offset = _src.offset();
const size_t tileSizeYmax = wgs / tileSizeX;
CV_Assert(src_step != 0 && esz != 0);
// workaround for NVIDIA: 3 channel vector type takes 4*elem_size in local memory
int loc_mem_cn = dev.vendorID() == ocl::Device::VENDOR_NVIDIA && cn == 3 ? 4 : cn;
if (((src_offset % src_step) % esz == 0) &&
(
(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE) ||
((borderType == BORDER_REFLECT || borderType == BORDER_WRAP || borderType == BORDER_REFLECT_101) &&
(_src.cols() >= (int) (kernelX.cols + tileSizeX) && _src.rows() >= (int) (kernelY.cols + tileSizeYmax)))
) &&
(tileSizeX * tileSizeYmin <= wgs) &&
(LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeYmin, kernelX.cols, loc_mem_cn * 4) <= lmsz)
&& OCL_PERFORMANCE_CHECK(!dev.isAMD()) // TODO FIXIT 2018: Problem with AMDGPU on Linux (2482.3)
)
{
Size size = _src.size(), wholeSize;
Point origin;
int dtype = CV_MAKE_TYPE(ddepth, cn);
int wdepth = CV_32F;
size_t tileSizeY = tileSizeYmax;
while ((tileSizeX * tileSizeY > wgs) || (LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeY, kernelX.cols, loc_mem_cn * 4) > lmsz))
{
tileSizeY /= 2;
}
size_t lt2[2] = { tileSizeX, tileSizeY};
size_t gt2[2] = { lt2[0] * (1 + (size.width - 1) / lt2[0]), lt2[1] };
char cvt[2][40];
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP",
"BORDER_REFLECT_101" };
String opts = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUS=%d%s%s"
" -D convertToWT=%s -D convertToDT=%s"
" -D %s -D srcT1=%s -D dstT1=%s -D WT1=%s"
" -D srcT=%s -D dstT=%s -D WT=%s"
" -D CN=%d ",
(int)lt2[0], (int)lt2[1], kernelX.cols / 2,
ocl::kernelToStr(kernelX, wdepth, "KERNEL_MATRIX_X").c_str(),
ocl::kernelToStr(kernelY, wdepth, "KERNEL_MATRIX_Y").c_str(),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]),
borderMap[borderType],
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), ocl::typeToStr(wdepth),
ocl::typeToStr(CV_MAKETYPE(sdepth, cn)),
ocl::typeToStr(CV_MAKETYPE(ddepth, cn)),
ocl::typeToStr(CV_MAKETYPE(wdepth, cn)),
cn);
ocl::Kernel k("laplacian", ocl::imgproc::laplacian5_oclsrc, opts);
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, dtype);
UMat dst = _dst.getUMat();
int src_offset_x = static_cast<int>((src_offset % src_step) / esz);
int src_offset_y = static_cast<int>(src_offset / src_step);
src.locateROI(wholeSize, origin);
k.args(ocl::KernelArg::PtrReadOnly(src), (int)src_step, src_offset_x, src_offset_y,
wholeSize.height, wholeSize.width, ocl::KernelArg::WriteOnly(dst),
static_cast<float>(scale), static_cast<float>(delta));
return k.run(2, gt2, lt2, false);
}
int iscale = cvRound(scale), idelta = cvRound(delta);
bool floatCoeff = std::fabs(delta - idelta) > DBL_EPSILON || std::fabs(scale - iscale) > DBL_EPSILON;
int wdepth = std::max(depth, floatCoeff ? CV_32F : CV_32S), kercn = 1;
if (!doubleSupport && wdepth == CV_64F)
return false;
char cvt[2][40];
ocl::Kernel k("sumConvert", ocl::imgproc::laplacian5_oclsrc,
format("-D ONLY_SUM_CONVERT "
"-D srcT=%s -D WT=%s -D dstT=%s -D coeffT=%s -D wdepth=%d "
"-D convertToWT=%s -D convertToDT=%s%s",
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)),
ocl::typeToStr(CV_MAKE_TYPE(ddepth, kercn)),
ocl::typeToStr(wdepth), wdepth,
ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]),
ocl::convertTypeStr(wdepth, ddepth, kercn, cvt[1]),
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
UMat d2x, d2y;
sepFilter2D(_src, d2x, depth, kd, ks, Point(-1, -1), 0, borderType);
sepFilter2D(_src, d2y, depth, ks, kd, Point(-1, -1), 0, borderType);
UMat dst = _dst.getUMat();
ocl::KernelArg d2xarg = ocl::KernelArg::ReadOnlyNoSize(d2x),
d2yarg = ocl::KernelArg::ReadOnlyNoSize(d2y),
dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn);
if (wdepth >= CV_32F)
k.args(d2xarg, d2yarg, dstarg, (float)scale, (float)delta);
else
k.args(d2xarg, d2yarg, dstarg, iscale, idelta);
size_t globalsize[] = { (size_t)dst.cols * cn / kercn, (size_t)dst.rows };
return k.run(2, globalsize, NULL, false);
}
static bool ocl_Laplacian3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
InputArray _kernel, double delta, int borderType)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
(borderType != BORDER_WRAP) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
return false;
Mat kernel = _kernel.getMat().reshape(1, 1);
if (ddepth < 0)
ddepth = sdepth;
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
char build_opts[1024];
sprintf(build_opts, "-D %s %s", borderMap[borderType],
ocl::kernelToStr(kernel, CV_32F, "KERNEL_MATRIX").c_str());
ocl::Kernel k("laplacian3_8UC1_cols16_rows2", cv::ocl::imgproc::laplacian3_oclsrc, build_opts);
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = k.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = k.set(idxArg, (int)src.step);
idxArg = k.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = k.set(idxArg, (int)dst.step);
idxArg = k.set(idxArg, (int)dst.rows);
idxArg = k.set(idxArg, (int)dst.cols);
idxArg = k.set(idxArg, static_cast<float>(delta));
return k.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
}
#endif
#if defined(HAVE_IPP)
namespace cv
{
static bool ipp_Laplacian(InputArray _src, OutputArray _dst, int ksize, double scale, double delta, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
::ipp::IwiSize size(_src.size().width, _src.size().height);
IppDataType srcType = ippiGetDataType(_src.depth());
IppDataType dstType = ippiGetDataType(_dst.depth());
int channels = _src.channels();
bool useScale = false;
if(channels != _dst.channels() || channels > 1)
return false;
if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON)
useScale = true;
IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize);
if((int)maskSize < 0)
return false;
// Acquire data and begin processing
try
{
Mat src = _src.getMat();
Mat dst = _dst.getMat();
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiImage iwSrcProc = iwSrc;
::ipp::IwiImage iwDstProc = iwDst;
::ipp::IwiBorderSize borderSize(maskSize);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
if(srcType == ipp8u && dstType == ipp8u)
{
iwDstProc.Alloc(iwDst.m_size, ipp16s, channels);
useScale = true;
}
else if(srcType == ipp8u && dstType == ipp32f)
{
iwSrc -= borderSize;
iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0);
iwSrcProc += borderSize;
}
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterLaplacian, iwSrcProc, iwDstProc, maskSize, ::ipp::IwDefault(), ippBorder);
if(useScale)
CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta);
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType);
return false;
#endif
}
}
#endif
void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
double scale, double delta, int borderType )
{
CV_INSTRUMENT_REGION();
CV_Assert(!_src.empty());
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if (ddepth < 0)
ddepth = sdepth;
_dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) );
if( ksize == 1 || ksize == 3 )
{
float K[2][9] =
{
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 },
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 }
};
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
if( scale != 1 )
kernel *= scale;
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
ocl_Laplacian3_8UC1(_src, _dst, ddepth, kernel, delta, borderType));
}
CV_IPP_RUN(!(cv::ocl::isOpenCLActivated() && _dst.isUMat()), ipp_Laplacian(_src, _dst, ksize, scale, delta, borderType));
if( ksize == 1 || ksize == 3 )
{
float K[2][9] =
{
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 },
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 }
};
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
if( scale != 1 )
kernel *= scale;
filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType );
}
else
{
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F;
int wtype = CV_MAKETYPE(wdepth, cn);
Mat kd, ks;
getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );
CV_OCL_RUN(_dst.isUMat(),
ocl_Laplacian5(_src, _dst, kd, ks, scale,
delta, borderType, wdepth, ddepth))
Mat src = _src.getMat(), dst = _dst.getMat();
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType&BORDER_ISOLATED))
src.locateROI( wsz, ofs );
borderType = (borderType&~BORDER_ISOLATED);
const size_t STRIPE_SIZE = 1 << 14;
Ptr<FilterEngine> fx = createSeparableLinearFilter(stype,
wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
Ptr<FilterEngine> fy = createSeparableLinearFilter(stype,
wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );
int y = fx->start(src, wsz, ofs), dsty = 0, dy = 0;
fy->start(src, wsz, ofs);
const uchar* sptr = src.ptr() + src.step[0] * y;
int dy0 = std::min(std::max((int)(STRIPE_SIZE/(CV_ELEM_SIZE(stype)*src.cols)), 1), src.rows);
Mat d2x( dy0 + kd.rows - 1, src.cols, wtype );
Mat d2y( dy0 + kd.rows - 1, src.cols, wtype );
for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy )
{
fx->proceed( sptr, (int)src.step, dy0, d2x.ptr(), (int)d2x.step );
dy = fy->proceed( sptr, (int)src.step, dy0, d2y.ptr(), (int)d2y.step );
if( dy > 0 )
{
Mat dstripe = dst.rowRange(dsty, dsty + dy);
d2x.rows = d2y.rows = dy; // modify the headers, which should work
d2x += d2y;
d2x.convertTo( dstripe, ddepth, scale, delta );
}
}
}
}
/////////////////////////////////////////////////////////////////////////////////////////
CV_IMPL void
cvSobel( const void* srcarr, void* dstarr, int dx, int dy, int aperture_size )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() );
cv::Sobel( src, dst, dst.depth(), dx, dy, aperture_size, 1, 0, cv::BORDER_REPLICATE );
if( CV_IS_IMAGE(srcarr) && ((IplImage*)srcarr)->origin && dy % 2 != 0 )
dst *= -1;
}
CV_IMPL void
cvLaplace( const void* srcarr, void* dstarr, int aperture_size )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() );
cv::Laplacian( src, dst, dst.depth(), aperture_size, 1, 0, cv::BORDER_REPLICATE );
}
/* End of file. */