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Merge pull request #8455 from terfendail:ovxhal_skipsmall

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This commit is contained in:
Vadim Pisarevsky 2017-05-26 12:10:18 +00:00
commit ee257ffe9e
16 changed files with 155 additions and 144 deletions
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58
3rdparty/openvx/hal/openvx_hal.cpp vendored
View File

@ -81,6 +81,15 @@ inline bool dimTooBig(int size)
return false;
}
//OpenVX calls have essential overhead so it make sense to skip them for small images
template <int kernel_id> inline bool skipSmallImages(int w, int h) { return w*h < 7680 * 4320; }
template <> inline bool skipSmallImages<VX_KERNEL_MULTIPLY>(int w, int h) { return w*h < 640 * 480; }
template <> inline bool skipSmallImages<VX_KERNEL_COLOR_CONVERT>(int w, int h) { return w*h < 2048 * 1536; }
template <> inline bool skipSmallImages<VX_KERNEL_INTEGRAL_IMAGE>(int w, int h) { return w*h < 640 * 480; }
template <> inline bool skipSmallImages<VX_KERNEL_WARP_AFFINE>(int w, int h) { return w*h < 1280 * 720; }
template <> inline bool skipSmallImages<VX_KERNEL_WARP_PERSPECTIVE>(int w, int h) { return w*h < 320 * 240; }
template <> inline bool skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(int w, int h) { return w*h < 320 * 240; }
inline void setConstantBorder(ivx::border_t &border, vx_uint8 val)
{
border.mode = VX_BORDER_CONSTANT;
@ -122,10 +131,12 @@ public:
// real code starts here
// ...
#define OVX_BINARY_OP(hal_func, ovx_call) \
#define OVX_BINARY_OP(hal_func, ovx_call, kernel_id) \
template <typename T> \
int ovx_hal_##hal_func(const T *a, size_t astep, const T *b, size_t bstep, T *c, size_t cstep, int w, int h) \
{ \
if(skipSmallImages<kernel_id>(w, h)) \
return CV_HAL_ERROR_NOT_IMPLEMENTED; \
if(dimTooBig(w) || dimTooBig(h)) \
return CV_HAL_ERROR_NOT_IMPLEMENTED; \
refineStep(w, h, ivx::TypeToEnum<T>::imgType, astep); \
@ -156,18 +167,22 @@ int ovx_hal_##hal_func(const T *a, size_t astep, const T *b, size_t bstep, T *c,
return CV_HAL_ERROR_OK; \
}
OVX_BINARY_OP(add, { ivx::IVX_CHECK_STATUS(vxuAdd(ctx, ia, ib, VX_CONVERT_POLICY_SATURATE, ic)); })
OVX_BINARY_OP(sub, { ivx::IVX_CHECK_STATUS(vxuSubtract(ctx, ia, ib, VX_CONVERT_POLICY_SATURATE, ic)); })
OVX_BINARY_OP(add, { ivx::IVX_CHECK_STATUS(vxuAdd(ctx, ia, ib, VX_CONVERT_POLICY_SATURATE, ic)); }, VX_KERNEL_ADD)
OVX_BINARY_OP(sub, { ivx::IVX_CHECK_STATUS(vxuSubtract(ctx, ia, ib, VX_CONVERT_POLICY_SATURATE, ic)); }, VX_KERNEL_SUBTRACT)
OVX_BINARY_OP(absdiff, { ivx::IVX_CHECK_STATUS(vxuAbsDiff(ctx, ia, ib, ic)); })
OVX_BINARY_OP(absdiff, { ivx::IVX_CHECK_STATUS(vxuAbsDiff(ctx, ia, ib, ic)); }, VX_KERNEL_ABSDIFF)
OVX_BINARY_OP(and, { ivx::IVX_CHECK_STATUS(vxuAnd(ctx, ia, ib, ic)); })
OVX_BINARY_OP(or , { ivx::IVX_CHECK_STATUS(vxuOr(ctx, ia, ib, ic)); })
OVX_BINARY_OP(xor, { ivx::IVX_CHECK_STATUS(vxuXor(ctx, ia, ib, ic)); })
OVX_BINARY_OP(and, { ivx::IVX_CHECK_STATUS(vxuAnd(ctx, ia, ib, ic)); }, VX_KERNEL_AND)
OVX_BINARY_OP(or , { ivx::IVX_CHECK_STATUS(vxuOr(ctx, ia, ib, ic)); }, VX_KERNEL_OR)
OVX_BINARY_OP(xor, { ivx::IVX_CHECK_STATUS(vxuXor(ctx, ia, ib, ic)); }, VX_KERNEL_XOR)
template <typename T>
int ovx_hal_mul(const T *a, size_t astep, const T *b, size_t bstep, T *c, size_t cstep, int w, int h, double scale)
{
if(scale == 1.0 || sizeof(T) > 1 ?
skipSmallImages<VX_KERNEL_ADD>(w, h) : /*actually it could be any kernel with generic minimum size*/
skipSmallImages<VX_KERNEL_MULTIPLY>(w, h) )
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(w, h, ivx::TypeToEnum<T>::imgType, astep);
@ -234,6 +249,8 @@ template int ovx_hal_mul<short>(const short *a, size_t astep, const short *b, si
int ovx_hal_not(const uchar *a, size_t astep, uchar *c, size_t cstep, int w, int h)
{
if (skipSmallImages<VX_KERNEL_NOT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(w, h, VX_DF_IMAGE_U8, astep);
@ -263,6 +280,8 @@ int ovx_hal_not(const uchar *a, size_t astep, uchar *c, size_t cstep, int w, int
int ovx_hal_merge8u(const uchar **src_data, uchar *dst_data, int len, int cn)
{
if (skipSmallImages<VX_KERNEL_CHANNEL_COMBINE>(len, 1))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(len))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (cn != 3 && cn != 4)
@ -299,6 +318,8 @@ int ovx_hal_merge8u(const uchar **src_data, uchar *dst_data, int len, int cn)
int ovx_hal_resize(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, double inv_scale_x, double inv_scale_y, int interpolation)
{
if (skipSmallImages<VX_KERNEL_SCALE_IMAGE>(aw, ah))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(aw) || dimTooBig(ah) || dimTooBig(bw) || dimTooBig(bh))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(aw, ah, VX_DF_IMAGE_U8, astep);
@ -350,6 +371,8 @@ int ovx_hal_resize(int atype, const uchar *a, size_t astep, int aw, int ah, ucha
int ovx_hal_warpAffine(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[6], int interpolation, int borderType, const double borderValue[4])
{
if (skipSmallImages<VX_KERNEL_WARP_AFFINE>(aw, ah))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(aw) || dimTooBig(ah) || dimTooBig(bw) || dimTooBig(bh))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(aw, ah, VX_DF_IMAGE_U8, astep);
@ -410,6 +433,8 @@ int ovx_hal_warpAffine(int atype, const uchar *a, size_t astep, int aw, int ah,
int ovx_hal_warpPerspectve(int atype, const uchar *a, size_t astep, int aw, int ah, uchar *b, size_t bstep, int bw, int bh, const double M[9], int interpolation, int borderType, const double borderValue[4])
{
if (skipSmallImages<VX_KERNEL_WARP_PERSPECTIVE>(aw, ah))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(aw) || dimTooBig(ah) || dimTooBig(bw) || dimTooBig(bh))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(aw, ah, VX_DF_IMAGE_U8, astep);
@ -531,6 +556,7 @@ int ovx_hal_filterInit(cvhalFilter2D **filter_context, uchar *kernel_data, size_
for (int i = 0; i < kernel_width; ++i)
data.push_back(row[i]);
}
break;
default:
return CV_HAL_ERROR_NOT_IMPLEMENTED;
}
@ -558,6 +584,8 @@ int ovx_hal_filterFree(cvhalFilter2D *filter_context)
int ovx_hal_filter(cvhalFilter2D *filter_context, uchar *a, size_t astep, uchar *b, size_t bstep, int w, int h, int, int, int, int)
{
if (skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
try
@ -782,6 +810,8 @@ int ovx_hal_morphFree(cvhalFilter2D *filter_context)
int ovx_hal_morph(cvhalFilter2D *filter_context, uchar *a, size_t astep, uchar *b, size_t bstep, int w, int h, int, int, int, int, int, int, int, int)
{
if (skipSmallImages<VX_KERNEL_DILATE_3x3>(w, h))//Actually it make sense to separate checks if implementations of dilation and erosion have different performance gain
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(w, h, VX_DF_IMAGE_U8, astep);
@ -823,6 +853,8 @@ int ovx_hal_morph(cvhalFilter2D *filter_context, uchar *a, size_t astep, uchar *
int ovx_hal_cvtBGRtoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int depth, int acn, int bcn, bool swapBlue)
{
if (skipSmallImages<VX_KERNEL_COLOR_CONVERT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (depth != CV_8U || swapBlue || acn == bcn || (acn != 3 && acn != 4) || (bcn != 3 && bcn != 4))
@ -857,6 +889,8 @@ int ovx_hal_cvtBGRtoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep,
int ovx_hal_cvtGraytoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int depth, int bcn)
{
if (skipSmallImages<VX_KERNEL_CHANNEL_COMBINE>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (depth != CV_8U || (bcn != 3 && bcn != 4))
@ -890,6 +924,8 @@ int ovx_hal_cvtGraytoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep,
int ovx_hal_cvtTwoPlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int bcn, bool swapBlue, int uIdx)
{
if (skipSmallImages<VX_KERNEL_COLOR_CONVERT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (!swapBlue || (bcn != 3 && bcn != 4))
@ -934,6 +970,8 @@ int ovx_hal_cvtTwoPlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size_t
int ovx_hal_cvtThreePlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int bcn, bool swapBlue, int uIdx)
{
if (skipSmallImages<VX_KERNEL_COLOR_CONVERT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (!swapBlue || (bcn != 3 && bcn != 4) || uIdx || (size_t)w / 2 != astep - (size_t)w / 2)
@ -982,6 +1020,8 @@ int ovx_hal_cvtThreePlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size
int ovx_hal_cvtBGRtoThreePlaneYUV(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int acn, bool swapBlue, int uIdx)
{
if (skipSmallImages<VX_KERNEL_COLOR_CONVERT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (!swapBlue || (acn != 3 && acn != 4) || uIdx || (size_t)w / 2 != bstep - (size_t)w / 2)
@ -1028,6 +1068,8 @@ int ovx_hal_cvtBGRtoThreePlaneYUV(const uchar * a, size_t astep, uchar * b, size
int ovx_hal_cvtOnePlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size_t bstep, int w, int h, int bcn, bool swapBlue, int uIdx, int ycn)
{
if (skipSmallImages<VX_KERNEL_COLOR_CONVERT>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (dimTooBig(w) || dimTooBig(h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (!swapBlue || (bcn != 3 && bcn != 4) || uIdx)
@ -1065,6 +1107,8 @@ int ovx_hal_cvtOnePlaneYUVtoBGR(const uchar * a, size_t astep, uchar * b, size_t
int ovx_hal_integral(int depth, int sdepth, int, const uchar * a, size_t astep, uchar * b, size_t bstep, uchar * c, size_t, uchar * d, size_t, int w, int h, int cn)
{
if (skipSmallImages<VX_KERNEL_INTEGRAL_IMAGE>(w, h))
return CV_HAL_ERROR_NOT_IMPLEMENTED;
if (depth != CV_8U || sdepth != CV_32S || c != NULL || d != NULL || cn != 1)
return CV_HAL_ERROR_NOT_IMPLEMENTED;
refineStep(w, h, VX_DF_IMAGE_U8, astep);

12
3rdparty/openvx/hal/openvx_hal.hpp vendored
View File

@ -106,12 +106,12 @@ int ovx_hal_integral(int depth, int sdepth, int, const uchar * a, size_t astep,
#undef cv_hal_filterFree
#define cv_hal_filterFree ovx_hal_filterFree
#undef cv_hal_sepFilterInit
#define cv_hal_sepFilterInit ovx_hal_sepFilterInit
#undef cv_hal_sepFilter
#define cv_hal_sepFilter ovx_hal_filter
#undef cv_hal_sepFilterFree
#define cv_hal_sepFilterFree ovx_hal_filterFree
//#undef cv_hal_sepFilterInit
//#define cv_hal_sepFilterInit ovx_hal_sepFilterInit
//#undef cv_hal_sepFilter
//#define cv_hal_sepFilter ovx_hal_filter
//#undef cv_hal_sepFilterFree
//#define cv_hal_sepFilterFree ovx_hal_filterFree
#if VX_VERSION > VX_VERSION_1_0

2
modules/core/include/opencv2/core/openvx/ovx_defs.hpp
View File

@ -24,6 +24,8 @@ namespace cv{
namespace ovx{
// Get common thread local OpenVX context
CV_EXPORTS_W ivx::Context& getOpenVXContext();
template <int kernel_id> inline bool skipSmallImages(int w, int h) { return w*h < 3840 * 2160; }
}}
#define CV_OVX_RUN(condition, func, ...) \

5
modules/core/src/convert.cpp
View File

@ -4862,6 +4862,9 @@ static bool _openvx_cvt(const T* src, size_t sstep,
int srcType = DataType<T>::type, dstType = DataType<DT>::type;
if (ovx::skipSmallImages<VX_KERNEL_CONVERTDEPTH>(imgSize.width, imgSize.height))
return false;
try
{
Context context = ovx::getOpenVXContext();
@ -5964,7 +5967,7 @@ void cv::LUT( InputArray _src, InputArray _lut, OutputArray _dst )
_dst.create(src.dims, src.size, CV_MAKETYPE(_lut.depth(), cn));
Mat dst = _dst.getMat();
CV_OVX_RUN(true,
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_TABLE_LOOKUP>(src.cols, src.rows),
openvx_LUT(src, dst, lut))
#if !IPP_DISABLE_PERF_LUT

7
modules/core/src/stat.cpp
View File

@ -1865,7 +1865,7 @@ void cv::meanStdDev( InputArray _src, OutputArray _mean, OutputArray _sdv, Input
Mat src = _src.getMat(), mask = _mask.getMat();
CV_Assert( mask.empty() || mask.type() == CV_8UC1 );
CV_OVX_RUN(true,
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_MEAN_STDDEV>(src.cols, src.rows),
openvx_meanStdDev(src, _mean, _sdv, mask))
CV_IPP_RUN(IPP_VERSION_X100 >= 700, ipp_meanStdDev(src, _mean, _sdv, mask));
@ -2322,6 +2322,9 @@ static bool ocl_minMaxIdx( InputArray _src, double* minVal, double* maxVal, int*
#endif
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_MINMAXLOC>(int w, int h) { return w*h < 3840 * 2160; }
}
static bool openvx_minMaxIdx(Mat &src, double* minVal, double* maxVal, int* minIdx, int* maxIdx, Mat &mask)
{
int stype = src.type();
@ -2682,7 +2685,7 @@ void cv::minMaxIdx(InputArray _src, double* minVal,
Mat src = _src.getMat(), mask = _mask.getMat();
CV_OVX_RUN(true,
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_MINMAXLOC>(src.cols, src.rows),
openvx_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))
CV_IPP_RUN_FAST(ipp_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))

6
modules/features2d/src/fast.cpp
View File

@ -338,6 +338,9 @@ static bool ocl_FAST( InputArray _img, std::vector<KeyPoint>& keypoints,
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_FAST_CORNERS>(int w, int h) { return w*h < 800 * 600; }
}
static bool openvx_FAST(InputArray _img, std::vector<KeyPoint>& keypoints,
int _threshold, bool nonmaxSuppression, int type)
{
@ -352,6 +355,9 @@ static bool openvx_FAST(InputArray _img, std::vector<KeyPoint>& keypoints,
if(imgMat.empty() || imgMat.type() != CV_8UC1)
return false;
if (ovx::skipSmallImages<VX_KERNEL_FAST_CORNERS>(imgMat.cols, imgMat.rows))
return false;
try
{
Context context = ovx::getOpenVXContext();

5
modules/imgproc/src/accum.cpp
View File

@ -1942,9 +1942,14 @@ enum
VX_ACCUMULATE_WEIGHTED_OP = 2
};
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_ACCUMULATE>(int w, int h) { return w*h < 120 * 60; }
}
static bool openvx_accumulate(InputArray _src, InputOutputArray _dst, InputArray _mask, double _weight, int opType)
{
Mat srcMat = _src.getMat(), dstMat = _dst.getMat();
if (ovx::skipSmallImages<VX_KERNEL_ACCUMULATE>(srcMat.cols, srcMat.rows))
return false;
if(!_mask.empty() ||
(opType == VX_ACCUMULATE_WEIGHTED_OP && dstMat.type() != CV_8UC1 ) ||
(opType != VX_ACCUMULATE_WEIGHTED_OP && dstMat.type() != CV_16SC1 ) ||

6
modules/imgproc/src/canny.cpp
View File

@ -899,6 +899,9 @@ private:
};
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_CANNY_EDGE_DETECTOR>(int w, int h) { return w*h < 640 * 480; }
}
static bool openvx_canny(const Mat& src, Mat& dst, int loVal, int hiVal, int kSize, bool useL2)
{
using namespace ivx;
@ -989,7 +992,8 @@ void Canny( InputArray _src, OutputArray _dst,
src.type() == CV_8UC1 &&
!src.isSubmatrix() &&
src.cols >= aperture_size &&
src.rows >= aperture_size,
src.rows >= aperture_size &&
!ovx::skipSmallImages<VX_KERNEL_CANNY_EDGE_DETECTOR>(src.cols, src.rows),
openvx_canny(
src,
dst,

70
modules/imgproc/src/deriv.cpp
View File

@ -184,41 +184,24 @@ cv::Ptr<cv::FilterEngine> cv::createDerivFilter(int srcType, int dstType,
#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)
{
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)
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;
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;
@ -228,8 +211,8 @@ namespace cv
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
// border = VX_BORDER_REPLICATE;
// break;
default:
return false;
}
@ -237,8 +220,8 @@ namespace cv
try
{
ivx::Context ctx = ovx::getOpenVXContext();
if ((vx_size)ksize > ctx.convolutionMaxDimension())
return false;
//if ((vx_size)ksize > ctx.convolutionMaxDimension())
// return false;
Mat a;
if (dst.data != src.data)
@ -249,40 +232,17 @@ 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));
}
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));
}
ctx.setImmediateBorder(prevBorder);
}
catch (ivx::RuntimeError & e)

3
modules/imgproc/src/featureselect.cpp
View File

@ -377,7 +377,8 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
}
// Disabled due to bad accuracy
CV_OVX_RUN(false && useHarrisDetector && _mask.empty(),
CV_OVX_RUN(false && useHarrisDetector && _mask.empty() &&
!ovx::skipSmallImages<VX_KERNEL_HARRIS_CORNERS>(image.cols, image.rows),
openvx_harris(image, _corners, maxCorners, qualityLevel, minDistance, blockSize, harrisK))
if( useHarrisDetector )

8
modules/imgproc/src/histogram.cpp
View File

@ -1331,6 +1331,9 @@ private:
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_HISTOGRAM>(int w, int h) { return w*h < 2048 * 1536; }
}
static bool openvx_calchist(const Mat& image, OutputArray _hist, const int histSize,
const float* _range)
{
@ -1440,7 +1443,8 @@ void cv::calcHist( const Mat* images, int nimages, const int* channels,
images && histSize &&
nimages == 1 && images[0].type() == CV_8UC1 && dims == 1 && _mask.getMat().empty() &&
(!channels || channels[0] == 0) && !accumulate && uniform &&
ranges && ranges[0],
ranges && ranges[0] &&
!ovx::skipSmallImages<VX_KERNEL_HISTOGRAM>(images[0].cols, images[0].rows),
openvx_calchist(images[0], _hist, histSize[0], ranges[0]))
Mat mask = _mask.getMat();
@ -3882,7 +3886,7 @@ void cv::equalizeHist( InputArray _src, OutputArray _dst )
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
CV_OVX_RUN(true,
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_EQUALIZE_HISTOGRAM>(src.cols, src.rows),
openvx_equalize_hist(src, dst))
Mutex histogramLockInstance;

1
modules/imgproc/src/imgwarp.cpp
View File

@ -4946,6 +4946,7 @@ void cv::remap( InputArray _src, OutputArray _dst,
CV_OVX_RUN(
src.type() == CV_8UC1 && dst.type() == CV_8UC1 &&
!ovx::skipSmallImages<VX_KERNEL_REMAP>(src.cols, src.rows) &&
(borderType& ~BORDER_ISOLATED) == BORDER_CONSTANT &&
((map1.type() == CV_32FC2 && map2.empty() && map1.size == dst.size) ||
(map1.type() == CV_32FC1 && map2.type() == CV_32FC1 && map1.size == dst.size && map2.size == dst.size) ||

3
modules/imgproc/src/pyramids.cpp
View File

@ -1265,6 +1265,9 @@ static bool openvx_pyrDown( InputArray _src, OutputArray _dst, const Size& _dsz,
Mat srcMat = _src.getMat();
if (ovx::skipSmallImages<VX_KERNEL_HALFSCALE_GAUSSIAN>(srcMat.cols, srcMat.rows))
return false;
CV_Assert(!srcMat.empty());
Size ssize = _src.size();

98
modules/imgproc/src/smooth.cpp
View File

@ -1650,26 +1650,24 @@ cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ks
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 640 * 480; }
}
static bool openvx_boxfilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
int stype = _src.type();
if (ddepth < 0)
ddepth = CV_8UC1;
if (stype != CV_8UC1 || (ddepth != CV_8U && ddepth != CV_16S) ||
(anchor.x >= 0 && anchor.x != ksize.width / 2) ||
(anchor.y >= 0 && anchor.y != ksize.height / 2) ||
ksize.width % 2 != 1 || ksize.height % 2 != 1 ||
ksize.width < 3 || ksize.height < 3)
if (_src.type() != CV_8UC1 || ddepth != CV_8U || !normalize ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3 ||
(anchor.x >= 0 && anchor.x != 1) ||
(anchor.y >= 0 && anchor.y != 1) ||
ovx::skipSmallImages<VX_KERNEL_BOX_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
_dst.create(src.size(), CV_MAKETYPE(ddepth, 1));
Mat dst = _dst.getMat();
if (src.cols < ksize.width || src.rows < ksize.height)
return false;
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
@ -1686,11 +1684,12 @@ namespace cv
return false;
}
_dst.create(src.size(), CV_8UC1);
Mat dst = _dst.getMat();
try
{
ivx::Context ctx = ovx::getOpenVXContext();
if ((vx_size)(ksize.width) > ctx.convolutionMaxDimension() || (vx_size)(ksize.height) > ctx.convolutionMaxDimension())
return false;
Mat a;
if (dst.data != src.data)
@ -1701,34 +1700,14 @@ 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, ddepth == CV_16S ? VX_DF_IMAGE_S16 : VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, ddepth == CV_16S ? 2 : 1, (vx_int32)(dst.step)), dst.data);
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 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
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
if (ddepth == CV_8U && ksize.width == 3 && ksize.height == 3 && normalize)
{
ivx::IVX_CHECK_STATUS(vxuBox3x3(ctx, ia, 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.setImmediateBorder(prevBorder);
return false;
}
#endif
Mat convData(ksize, CV_16SC1);
convData = normalize ? (1 << 15) / (ksize.width * ksize.height) : 1;
ivx::Convolution cnv = ivx::Convolution::create(ctx, convData.cols, convData.rows);
cnv.copyFrom(convData);
if (normalize)
cnv.setScale(1 << 15);
ivx::IVX_CHECK_STATUS(vxuConvolve(ctx, ia, cnv, ib));
}
ctx.setImmediateBorder(prevBorder);
}
catch (ivx::RuntimeError & e)
@ -2181,10 +2160,12 @@ static bool ocl_GaussianBlur_8UC1(InputArray _src, OutputArray _dst, Size ksize,
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(int w, int h) { return w*h < 320 * 240; }
}
static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, int borderType)
{
int stype = _src.type();
if (sigma2 <= 0)
sigma2 = sigma1;
// automatic detection of kernel size from sigma
@ -2193,20 +2174,21 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
if (ksize.height <= 0 && sigma2 > 0)
ksize.height = cvRound(sigma2*6 + 1) | 1;
if (stype != CV_8UC1 ||
ksize.width < 3 || ksize.height < 3 ||
ksize.width % 2 != 1 || ksize.height % 2 != 1)
if (_src.type() != CV_8UC1 ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3)
return false;
sigma1 = std::max(sigma1, 0.);
sigma2 = std::max(sigma2, 0.);
if (!(sigma1 == 0.0 || (sigma1 - 0.8) < DBL_EPSILON) || !(sigma2 == 0.0 || (sigma2 - 0.8) < DBL_EPSILON) ||
ovx::skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (src.cols < ksize.width || src.rows < ksize.height)
return false;
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
@ -2225,8 +2207,6 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
try
{
ivx::Context ctx = ovx::getOpenVXContext();
if ((vx_size)(ksize.width) > ctx.convolutionMaxDimension() || (vx_size)(ksize.height) > ctx.convolutionMaxDimension())
return false;
Mat a;
if (dst.data != src.data)
@ -2244,26 +2224,7 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
//since OpenVX standart says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
if (ksize.width == 3 && ksize.height == 3 && (sigma1 == 0.0 || (sigma1 - 0.8) < DBL_EPSILON) && (sigma2 == 0.0 || (sigma2 - 0.8) < DBL_EPSILON))
{
ivx::IVX_CHECK_STATUS(vxuGaussian3x3(ctx, ia, ib));
}
else
{
#if VX_VERSION <= VX_VERSION_1_0
if (ctx.vendorID() == VX_ID_KHRONOS && ((vx_size)(a.cols) <= ctx.convolutionMaxDimension() || (vx_size)(a.rows) <= ctx.convolutionMaxDimension()))
{
ctx.setImmediateBorder(prevBorder);
return false;
}
#endif
Mat convData;
cv::Mat(cv::getGaussianKernel(ksize.height, sigma2)*cv::getGaussianKernel(ksize.width, sigma1).t()).convertTo(convData, CV_16SC1, (1 << 15));
ivx::Convolution cnv = ivx::Convolution::create(ctx, convData.cols, convData.rows);
cnv.copyFrom(convData);
cnv.setScale(1 << 15);
ivx::IVX_CHECK_STATUS(vxuConvolve(ctx, ia, cnv, ib));
}
ctx.setImmediateBorder(prevBorder);
}
catch (ivx::RuntimeError & e)
@ -3286,6 +3247,9 @@ static bool ocl_medianFilter(InputArray _src, OutputArray _dst, int m)
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_MEDIAN_3x3>(int w, int h) { return w*h < 1280 * 720; }
}
static bool openvx_medianFilter(InputArray _src, OutputArray _dst, int ksize)
{
if (_src.type() != CV_8UC1 || _dst.type() != CV_8U
@ -3298,6 +3262,14 @@ namespace cv
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (
#ifdef VX_VERSION_1_1
ksize != 3 ? ovx::skipSmallImages<VX_KERNEL_NON_LINEAR_FILTER>(src.cols, src.rows) :
#endif
ovx::skipSmallImages<VX_KERNEL_MEDIAN_3x3>(src.cols, src.rows)
)
return false;
try
{
ivx::Context ctx = ovx::getOpenVXContext();

2
modules/imgproc/src/thresh.cpp
View File

@ -1390,7 +1390,7 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
return thresh;
}
CV_OVX_RUN(true,
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_THRESHOLD>(src.cols, src.rows),
openvx_threshold(src, dst, ithresh, imaxval, type), (double)ithresh)
thresh = ithresh;

3
modules/video/src/lkpyramid.cpp
View File

@ -1077,6 +1077,9 @@ namespace
if(prevImgMat.type() != CV_8UC1 || nextImgMat.type() != CV_8UC1)
return false;
if (ovx::skipSmallImages<VX_KERNEL_OPTICAL_FLOW_PYR_LK>(prevImgMat.cols, prevImgMat.rows))
return false;
CV_Assert(prevImgMat.size() == nextImgMat.size());
Mat prevPtsMat = _prevPts.getMat();
int checkPrev = prevPtsMat.checkVector(2, CV_32F, false);