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Commit 1eedc6c4 authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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refactored Linear Filter

parent fcfcd4cb
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Showing with 211 additions and 173 deletions
modules/gpufilters/include/opencv2/gpufilters.hpp
View file @ 1eedc6c4
......@@ -96,6 +96,34 @@ inline void blur(InputArray src, OutputArray dst, Size ksize, Point anchor, Stre
f->apply(src, dst, stream);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// Linear Filter
//! non-separable linear 2D filter
CV_EXPORTS Ptr<Filter> createLinearFilter(int srcType, int dstType, InputArray kernel, Point anchor = Point(-1,-1),
int borderMode = BORDER_DEFAULT, Scalar borderVal = Scalar::all(0));
__OPENCV_GPUFILTERS_DEPR_BEFORE__ void filter2D(InputArray src, OutputArray dst, int ddepth, InputArray kernel,
Point anchor = Point(-1,-1), int borderType = BORDER_DEFAULT,
Stream& stream = Stream::Null()) __OPENCV_GPUFILTERS_DEPR_AFTER__;
inline void filter2D(InputArray src, OutputArray dst, int ddepth, InputArray kernel, Point anchor, int borderType, Stream& stream)
{
Ptr<gpu::Filter> f = gpu::createLinearFilter(src.type(), ddepth, kernel, anchor, borderType);
f->apply(src, dst, stream);
}
//! applies Laplacian operator to the image
//! supports only ksize = 1 and ksize = 3
CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1, int borderType = BORDER_DEFAULT, Stream& stream = Stream::Null());
......@@ -194,13 +222,7 @@ CV_EXPORTS Ptr<FilterEngine_GPU> createMorphologyFilter_GPU(int op, int type, co
CV_EXPORTS Ptr<FilterEngine_GPU> createMorphologyFilter_GPU(int op, int type, const Mat& kernel, GpuMat& buf,
const Point& anchor = Point(-1,-1), int iterations = 1);
//! returns 2D filter with the specified kernel
//! supports CV_8U, CV_16U and CV_32F one and four channel image
CV_EXPORTS Ptr<BaseFilter_GPU> getLinearFilter_GPU(int srcType, int dstType, const Mat& kernel, Point anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
//! returns the non-separable linear filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createLinearFilter_GPU(int srcType, int dstType, const Mat& kernel,
Point anchor = Point(-1,-1), int borderType = BORDER_DEFAULT);
//! returns the primitive row filter with the specified kernel.
//! supports only CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_32SC1, CV_32FC1 source type.
......@@ -269,9 +291,6 @@ CV_EXPORTS void morphologyEx(const GpuMat& src, GpuMat& dst, int op, const Mat&
CV_EXPORTS void morphologyEx(const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, GpuMat& buf1, GpuMat& buf2,
Point anchor = Point(-1, -1), int iterations = 1, Stream& stream = Stream::Null());
//! applies non-separable 2D linear filter to the image
CV_EXPORTS void filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor=Point(-1,-1), int borderType = BORDER_DEFAULT, Stream& stream = Stream::Null());
//! applies separable 2D linear filter to the image
CV_EXPORTS void sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY,
Point anchor = Point(-1,-1), int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1);
......@@ -297,10 +316,6 @@ CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double
CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, GpuMat& buf, double sigma1, double sigma2 = 0,
int rowBorderType = BORDER_DEFAULT, int columnBorderType = -1, Stream& stream = Stream::Null());
//! applies Laplacian operator to the image
//! supports only ksize = 1 and ksize = 3
CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1, int borderType = BORDER_DEFAULT, Stream& stream = Stream::Null());
}} // namespace cv { namespace gpu {
#undef __OPENCV_GPUFILTERS_DEPR_BEFORE__
......
modules/gpufilters/perf/perf_filters.cpp
View file @ 1eedc6c4
......@@ -86,6 +86,51 @@ PERF_TEST_P(Sz_Type_KernelSz, Blur,
}
}
//////////////////////////////////////////////////////////////////////
// Filter2D
PERF_TEST_P(Sz_Type_KernelSz, Filter2D, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(3, 5, 7, 9, 11, 13, 15)))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int type = GET_PARAM(1);
const int ksize = GET_PARAM(2);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
cv::Mat kernel(ksize, ksize, CV_32FC1);
declare.in(kernel, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
cv::Ptr<cv::gpu::Filter> filter2D = cv::gpu::createLinearFilter(d_src.type(), -1, kernel);
TEST_CYCLE() filter2D->apply(d_src, dst);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::filter2D(src, dst, -1, kernel);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// Sobel
......@@ -330,39 +375,3 @@ PERF_TEST_P(Sz_Type_Op, MorphologyEx, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// Filter2D
PERF_TEST_P(Sz_Type_KernelSz, Filter2D, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(3, 5, 7, 9, 11, 13, 15)))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int type = GET_PARAM(1);
const int ksize = GET_PARAM(2);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
cv::Mat kernel(ksize, ksize, CV_32FC1);
declare.in(kernel, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::filter2D(d_src, dst, -1, kernel);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::filter2D(src, dst, -1, kernel);
CPU_SANITY_CHECK(dst);
}
}
modules/gpufilters/src/cuda/filter2d.cu
View file @ 1eedc6c4
......@@ -48,14 +48,11 @@
namespace cv { namespace gpu { namespace cudev
{
namespace imgproc
{
#define FILTER2D_MAX_KERNEL_SIZE 16
__constant__ float c_filter2DKernel[FILTER2D_MAX_KERNEL_SIZE * FILTER2D_MAX_KERNEL_SIZE];
template <class SrcT, typename D>
__global__ void filter2D(const SrcT src, PtrStepSz<D> dst, const int kWidth, const int kHeight, const int anchorX, const int anchorY)
template <class SrcPtr, typename D>
__global__ void filter2D(const SrcPtr src, PtrStepSz<D> dst,
const float* __restrict__ kernel,
const int kWidth, const int kHeight,
const int anchorX, const int anchorY)
{
typedef typename TypeVec<float, VecTraits<D>::cn>::vec_type sum_t;
......@@ -71,7 +68,7 @@ namespace cv { namespace gpu { namespace cudev
for (int i = 0; i < kHeight; ++i)
{
for (int j = 0; j < kWidth; ++j)
res = res + src(y - anchorY + i, x - anchorX + j) * c_filter2DKernel[kInd++];
res = res + src(y - anchorY + i, x - anchorX + j) * kernel[kInd++];
}
dst(y, x) = saturate_cast<D>(res);
......@@ -95,7 +92,7 @@ namespace cv { namespace gpu { namespace cudev
}; \
template <typename D, template <typename> class Brd> struct Filter2DCaller< type , D, Brd> \
{ \
static void call(const PtrStepSz< type > srcWhole, int xoff, int yoff, PtrStepSz<D> dst, \
static void call(const PtrStepSz< type > srcWhole, int xoff, int yoff, PtrStepSz<D> dst, const float* kernel, \
int kWidth, int kHeight, int anchorX, int anchorY, const float* borderValue, cudaStream_t stream) \
{ \
typedef typename TypeVec<float, VecTraits< type >::cn>::vec_type work_type; \
......@@ -105,7 +102,7 @@ namespace cv { namespace gpu { namespace cudev
tex_filter2D_ ## type ##_reader texSrc(xoff, yoff); \
Brd<work_type> brd(dst.rows, dst.cols, VecTraits<work_type>::make(borderValue)); \
BorderReader< tex_filter2D_ ## type ##_reader, Brd<work_type> > brdSrc(texSrc, brd); \
filter2D<<<grid, block, 0, stream>>>(brdSrc, dst, kWidth, kHeight, anchorX, anchorY); \
filter2D<<<grid, block, 0, stream>>>(brdSrc, dst, kernel, kWidth, kHeight, anchorX, anchorY); \
cudaSafeCall( cudaGetLastError() ); \
if (stream == 0) \
cudaSafeCall( cudaDeviceSynchronize() ); \
......@@ -124,11 +121,12 @@ namespace cv { namespace gpu { namespace cudev
#undef IMPLEMENT_FILTER2D_TEX_READER
template <typename T, typename D>
void filter2D_gpu(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst,
int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel,
void filter2D(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel,
int kWidth, int kHeight, int anchorX, int anchorY,
int borderMode, const float* borderValue, cudaStream_t stream)
{
typedef void (*func_t)(const PtrStepSz<T> srcWhole, int xoff, int yoff, PtrStepSz<D> dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* borderValue, cudaStream_t stream);
typedef void (*func_t)(const PtrStepSz<T> srcWhole, int xoff, int yoff, PtrStepSz<D> dst, const float* kernel,
int kWidth, int kHeight, int anchorX, int anchorY, const float* borderValue, cudaStream_t stream);
static const func_t funcs[] =
{
Filter2DCaller<T, D, BrdConstant>::call,
......@@ -138,21 +136,16 @@ namespace cv { namespace gpu { namespace cudev
Filter2DCaller<T, D, BrdReflect101>::call
};
if (stream == 0)
cudaSafeCall( cudaMemcpyToSymbol(c_filter2DKernel, kernel, kWidth * kHeight * sizeof(float), 0, cudaMemcpyDeviceToDevice) );
else
cudaSafeCall( cudaMemcpyToSymbolAsync(c_filter2DKernel, kernel, kWidth * kHeight * sizeof(float), 0, cudaMemcpyDeviceToDevice, stream) );
funcs[borderMode](static_cast< PtrStepSz<T> >(srcWhole), ofsX, ofsY, static_cast< PtrStepSz<D> >(dst), kWidth, kHeight, anchorX, anchorY, borderValue, stream);
funcs[borderMode]((PtrStepSz<T>) srcWhole, ofsX, ofsY, (PtrStepSz<D>) dst, kernel,
kWidth, kHeight, anchorX, anchorY, borderValue, stream);
}
template void filter2D_gpu<uchar, uchar>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D_gpu<uchar4, uchar4>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D_gpu<ushort, ushort>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D_gpu<ushort4, ushort4>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D_gpu<float, float>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D_gpu<float4, float4>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, int kWidth, int kHeight, int anchorX, int anchorY, const float* kernel, int borderMode, const float* borderValue, cudaStream_t stream);
}
template void filter2D<uchar , uchar >(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D<uchar4 , uchar4 >(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D<ushort , ushort >(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D<ushort4, ushort4>(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D<float , float >(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
template void filter2D<float4 , float4 >(PtrStepSzb srcWhole, int ofsX, int ofsY, PtrStepSzb dst, const float* kernel, int kWidth, int kHeight, int anchorX, int anchorY, int borderMode, const float* borderValue, cudaStream_t stream);
}}}
#endif // CUDA_DISABLER
modules/gpufilters/src/filtering.cpp
View file @ 1eedc6c4
This diff is collapsed.
modules/gpufilters/test/test_filters.cpp
View file @ 1eedc6c4
......@@ -118,6 +118,121 @@ INSTANTIATE_TEST_CASE_P(GPU_Filters, Blur, testing::Combine(
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Filter2D
PARAM_TEST_CASE(Filter2D, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, BorderType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
cv::Size ksize;
cv::Point anchor;
int borderType;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
anchor = GET_PARAM(4);
borderType = GET_PARAM(5);
useRoi = GET_PARAM(6);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Filter2D, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
cv::Ptr<cv::gpu::Filter> filter2D = cv::gpu::createLinearFilter(src.type(), -1, kernel, anchor, borderType);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
filter2D->apply(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::filter2D(src, dst_gold, -1, kernel, anchor, 0, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) == CV_32F ? 1e-1 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Filters, Filter2D, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC4)),
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7)), KSize(cv::Size(11, 11)), KSize(cv::Size(13, 13)), KSize(cv::Size(15, 15))),
testing::Values(Anchor(cv::Point(-1, -1)), Anchor(cv::Point(0, 0)), Anchor(cv::Point(2, 2))),
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Laplacian
PARAM_TEST_CASE(Laplacian, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
cv::Size ksize;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Laplacian, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::Laplacian(loadMat(src, useRoi), dst, -1, ksize.width);
cv::Mat dst_gold;
cv::Laplacian(src, dst_gold, -1, ksize.width);
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() < CV_32F ? 0.0 : 1e-3);
}
INSTANTIATE_TEST_CASE_P(GPU_Filters, Laplacian, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_32FC1)),
testing::Values(KSize(cv::Size(1, 1)), KSize(cv::Size(3, 3))),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Sobel
......@@ -332,49 +447,6 @@ INSTANTIATE_TEST_CASE_P(GPU_Filters, GaussianBlur, testing::Combine(
BorderType(cv::BORDER_REFLECT)),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Laplacian
PARAM_TEST_CASE(Laplacian, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
cv::Size ksize;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Laplacian, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::Laplacian(loadMat(src, useRoi), dst, -1, ksize.width);
cv::Mat dst_gold;
cv::Laplacian(src, dst_gold, -1, ksize.width);
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() < CV_32F ? 0.0 : 1e-3);
}
INSTANTIATE_TEST_CASE_P(GPU_Filters, Laplacian, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_32FC1)),
testing::Values(KSize(cv::Size(1, 1)), KSize(cv::Size(3, 3))),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Erode
......@@ -527,56 +599,4 @@ INSTANTIATE_TEST_CASE_P(GPU_Filters, MorphEx, testing::Combine(
testing::Values(Iterations(1), Iterations(2), Iterations(3)),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
// Filter2D
PARAM_TEST_CASE(Filter2D, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, BorderType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
cv::Size ksize;
cv::Point anchor;
int borderType;
bool useRoi;
cv::Mat img;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
ksize = GET_PARAM(3);
anchor = GET_PARAM(4);
borderType = GET_PARAM(5);
useRoi = GET_PARAM(6);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Filter2D, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::filter2D(loadMat(src, useRoi), dst, -1, kernel, anchor, borderType);
cv::Mat dst_gold;
cv::filter2D(src, dst_gold, -1, kernel, anchor, 0, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) == CV_32F ? 1e-1 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Filters, Filter2D, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC4)),
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7)), KSize(cv::Size(11, 11)), KSize(cv::Size(13, 13)), KSize(cv::Size(15, 15))),
testing::Values(Anchor(cv::Point(-1, -1)), Anchor(cv::Point(0, 0)), Anchor(cv::Point(2, 2))),
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
WHOLE_SUBMAT));
#endif // HAVE_CUDA
samples/gpu/performance/tests.cpp
View file @ 1eedc6c4
......@@ -961,10 +961,11 @@ TEST(filter2D)
gpu::GpuMat d_src(src);
gpu::GpuMat d_dst;
gpu::filter2D(d_src, d_dst, -1, kernel);
Ptr<gpu::Filter> filter2D = gpu::createLinearFilter(d_src.type(), -1, kernel);
filter2D->apply(d_src, d_dst);
GPU_ON;
gpu::filter2D(d_src, d_dst, -1, kernel);
filter2D->apply(d_src, d_dst);
GPU_OFF;
}
}
......
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