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Extended set of OpenVX HAL calls disabled for small images

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This commit is contained in:
Vitaly Tuzov
2017-03-28 18:02:42 +03:00
parent 62fab57c3e
commit bf5b7843e8
15 changed files with 89 additions and 50 deletions
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modules/core/include/opencv2/core/openvx/ovx_defs.hpp
+10
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@@ -24,6 +24,16 @@ 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; }
template <> inline bool skipSmallImages<VX_KERNEL_MINMAXLOC>(int w, int h) { return w*h < 1280*720; }
template <> inline bool skipSmallImages<VX_KERNEL_MEDIAN_3x3>(int w, int h) { return w*h < 1280 * 720; }
template <> inline bool skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(int w, int h) { return w*h < 1280 * 720; }
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 1280 * 720; }
template <> inline bool skipSmallImages<VX_KERNEL_HISTOGRAM>(int w, int h) { return w*h < 2048 * 1536; }
template <> inline bool skipSmallImages<VX_KERNEL_SOBEL_3x3>(int w, int h) { return w*h < 640 * 480; }
template <> inline bool skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(int w, int h) { return w*h < 1280 * 720; }
}}
#define CV_OVX_RUN(condition, func, ...) \
modules/core/src/convert.cpp
+4 -1
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@@ -4671,6 +4671,9 @@ 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();
@@ -5696,7 +5699,7 @@ 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))
CV_IPP_RUN(_src.dims() <= 2, ipp_lut(src, lut, dst));
modules/core/src/stat.cpp
+2 -2
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@@ -1843,7 +1843,7 @@ 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));
@@ -2496,7 +2496,7 @@ 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(IPP_VERSION_X100 >= 700, ipp_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))
modules/features2d/src/fast.cpp
+3
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@@ -352,6 +352,9 @@ 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();
modules/imgproc/src/accum.cpp
+2
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@@ -1945,6 +1945,8 @@ enum
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 ) ||
modules/imgproc/src/canny.cpp
+2 -1
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@@ -868,7 +868,8 @@ 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,
modules/imgproc/src/deriv.cpp
+9 -3
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@@ -191,7 +191,7 @@ namespace cv
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)
ksize != 3 || delta != 0.0)//Restrict to 3x3 kernels since otherwise convolution would be slower than separable filter
return false;
Mat src = _src.getMat();
@@ -200,6 +200,12 @@ namespace cv
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)
@@ -237,8 +243,8 @@ 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)
modules/imgproc/src/featureselect.cpp
+2 -1
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@@ -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 )
modules/imgproc/src/histogram.cpp
+3 -2
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@@ -1376,7 +1376,8 @@ 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]))
CV_IPP_RUN(nimages == 1 && images[0].type() == CV_8UC1 && dims == 1 && channels &&
@@ -3817,7 +3818,7 @@ 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;
modules/imgproc/src/imgwarp.cpp
+1
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@@ -4935,6 +4935,7 @@ 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) ||
modules/imgproc/src/pyramids.cpp
+3
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@@ -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();
modules/imgproc/src/smooth.cpp
+25 -4
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@@ -1649,11 +1649,17 @@ namespace cv
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)
ksize.width != 3 || ksize.height != 3)
return false;
Mat src = _src.getMat();
if (ddepth == CV_8U && ksize.width == 3 && ksize.height == 3 && normalize ?
ovx::skipSmallImages<VX_KERNEL_BOX_3x3>(src.cols, src.rows) :
ovx::skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(src.cols, src.rows)
)
return false;
_dst.create(src.size(), CV_MAKETYPE(ddepth, 1));
Mat dst = _dst.getMat();
@@ -1678,8 +1684,8 @@ namespace cv
try
{
ivx::Context ctx = ovx::getOpenVXContext();
if ((vx_size)(ksize.width) > ctx.convolutionMaxDimension() || (vx_size)(ksize.height) > ctx.convolutionMaxDimension())
return false;
//if ((vx_size)(ksize.width) > ctx.convolutionMaxDimension() || (vx_size)(ksize.height) > ctx.convolutionMaxDimension())
// return false;
Mat a;
if (dst.data != src.data)
@@ -2210,6 +2216,7 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
if (stype != CV_8UC1 ||
ksize.width < 3 || ksize.height < 3 ||
ksize.width > 5 || ksize.height > 5 ||
ksize.width % 2 != 1 || ksize.height % 2 != 1)
return false;
@@ -2219,6 +2226,12 @@ static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (ksize.width == 3 && ksize.height == 3 && (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) :
ovx::skipSmallImages<VX_KERNEL_CUSTOM_CONVOLUTION>(src.cols, src.rows)
)
return false;
if (src.cols < ksize.width || src.rows < ksize.height)
return false;
@@ -3359,6 +3372,14 @@ 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();
modules/imgproc/src/thresh.cpp
+1 -1
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@@ -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;
modules/video/src/lkpyramid.cpp
+3
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@@ -1074,6 +1074,9 @@ 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);