提交 e8f34690 编写于 作者: V Vitaly Tuzov

Added OpenVX based processing to Sobel

上级 ff2747df
......@@ -43,6 +43,12 @@
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#ifdef HAVE_OPENVX
#define IVX_HIDE_INFO_WARNINGS
#define IVX_USE_OPENCV
#include "ivx.hpp"
#endif
/****************************************************************************************\
Sobel & Scharr Derivative Filters
\****************************************************************************************/
......@@ -179,6 +185,130 @@ cv::Ptr<cv::FilterEngine> cv::createDerivFilter(int srcType, int dstType,
kx, ky, Point(-1,-1), 0, borderType );
}
#ifdef HAVE_OPENVX
namespace cv
{
static bool openvx_sobel(InputArray _src, OutputArray _dst,
int dx, int dy, int ksize,
double scale, double delta, int borderType)
{
int stype = _src.type();
int dtype = _dst.type();
if (stype != CV_8UC1 || (dtype != CV_16SC1 && dtype != CV_8UC1) ||
ksize < 3 || ksize % 2 != 1 || delta != 0.0)
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (src.cols < ksize || src.rows < ksize)
return false;
int iscale = 1;
vx_uint32 cscale = 1;
if(scale != 1.0)
{
iscale = static_cast<int>(scale);
if (std::abs(scale - iscale) >= DBL_EPSILON)
{
int exp = 0;
float significand = frexp(scale, &exp);
if ((significand == 0.5f) && (exp <= 0))
{
iscale = 1;
cscale = 1 << (exp = -exp + 1);
}
else
return false;
}
}
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_border_t border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border.mode = VX_BORDER_CONSTANT;
#if VX_VERSION > VX_VERSION_1_0
border.constant_value.U8 = (vx_uint8)(0);
#else
border.constant_value = (vx_uint32)(0);
#endif
break;
case BORDER_REPLICATE:
border.mode = VX_BORDER_REPLICATE;
break;
default:
return false;
}
try
{
ivx::Context ctx = ivx::Context::create();
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, dtype == CV_16SC1 ? VX_DF_IMAGE_S16 : VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, dtype == CV_16SC1 ? 2 : 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standart says nothing about thread-safety for now
vx_border_t prevBorder = ctx.borderMode();
ctx.setBorderMode(border);
if (dtype == CV_16SC1 && ksize == 3 && ((dx | dy) == 1) && (dx + dy) == 1)
{
if(dx)
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, ib, NULL));
else
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, NULL, ib));
}
else
{
#if VX_VERSION <= VX_VERSION_1_0
if (ctx.vendorID() == VX_ID_KHRONOS && ((vx_size)(src.cols) <= ctx.convolutionMaxDimension() || (vx_size)(src.rows) <= ctx.convolutionMaxDimension()))
{
ctx.setBorderMode(prevBorder);
return false;
}
#endif
Mat kx, ky;
getDerivKernels(kx, ky, dx, dy, ksize, false);
flip(kx, kx, 0);
flip(ky, ky, 0);
Mat convData;
cv::Mat(ky*kx.t()).convertTo(convData, CV_16SC1, iscale);
ivx::Convolution cnv = ivx::Convolution::create(ctx, convData.cols, convData.rows);
cnv.copyFrom(convData);
cnv.setScale(cscale);
ivx::IVX_CHECK_STATUS(vxuConvolve(ctx, ia, cnv, ib));
}
ctx.setBorderMode(prevBorder);
return true;
}
catch (ivx::RuntimeError & e)
{
CV_Error(CV_StsInternal, e.what());
return false;
}
catch (ivx::WrapperError & e)
{
CV_Error(CV_StsInternal, e.what());
return false;
}
}
}
#endif
#ifdef HAVE_IPP
namespace cv
{
......@@ -599,6 +729,11 @@ void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
}
#endif
#ifdef HAVE_OPENVX
if (openvx_sobel(_src, _dst, dx, dy, ksize, scale, delta, borderType))
return;
#endif
CV_IPP_RUN(!(ocl::useOpenCL() && _dst.isUMat()), ipp_sobel(_src, _dst, ddepth, dx, dy, ksize, scale, delta, borderType));
int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册