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Disabled vxuConvolution call for Sobel, GaussianBlur and Box filter evaluation

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This commit is contained in:
Vitaly Tuzov
2017-04-11 13:22:38 +03:00
parent 0f1a56da7c
commit 87bb74312b
3 changed files with 31 additions and 139 deletions
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modules/imgproc/src/deriv.cpp
+11 -60
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@@ -188,43 +188,17 @@ namespace cv
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 || delta != 0.0)//Restrict to 3x3 kernels since otherwise convolution would be slower than separable filter
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 (src.cols < ksize || src.rows < ksize)
return false;
if (dtype == CV_16SC1 && ksize == 3 && ((dx | dy) == 1) && (dx + dy) == 1 ?
ovx::skipSmallImages<VX_KERNEL_SOBEL_3x3>(src.cols, src.rows) :
ovx::skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(src.cols, src.rows)
)
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_enum border;
@@ -255,40 +229,17 @@ namespace cv
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);
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 standart says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
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));
}
if(dx)
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, ib, NULL));
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.setImmediateBorder(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));
}
ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, NULL, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (ivx::RuntimeError & e)