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提交 d192117e 编写于 作者: M Marina Kolpakova
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GPU resize with INTER_AREA

上级 bc541951
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Showing with 273 addition and 28 deletion
modules/gpu/src/cuda/resize.cu
浏览文件 @ d192117e
......@@ -46,6 +46,7 @@
#include "opencv2/gpu/device/vec_math.hpp"
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/filters.hpp"
# include <cfloat>
namespace cv { namespace gpu { namespace device
{
......@@ -65,6 +66,17 @@ namespace cv { namespace gpu { namespace device
}
}
template <typename Ptr2D, typename T> __global__ void resize_area(const Ptr2D src, float fx, float fy, DevMem2D_<T> dst)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < dst.cols && y < dst.rows)
{
dst(y, x) = saturate_cast<T>(src(y, x));
}
}
template <template <typename> class Filter, typename T> struct ResizeDispatcherStream
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
......@@ -74,13 +86,43 @@ namespace cv { namespace gpu { namespace device
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc, fx, fy);
resize<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <typename T> struct ResizeDispatcherStream<AreaFilter, T>
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdConstant<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdConstant<T> > brdSrc(src, brd);
AreaFilter< BorderReader< PtrStep<T>, BrdConstant<T> > > filteredSrc(brdSrc, fx, fy);
resize_area<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <typename T> struct ResizeDispatcherStream<IntegerAreaFilter, T>
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdConstant<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdConstant<T> > brdSrc(src, brd);
IntegerAreaFilter< BorderReader< PtrStep<T>, BrdConstant<T> > > filteredSrc(brdSrc, fx, fy);
resize_area<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <template <typename> class Filter, typename T> struct ResizeDispatcherNonStream
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst)
......@@ -169,14 +211,31 @@ namespace cv { namespace gpu { namespace device
}
};
template <typename T> struct ResizeDispatcher<AreaFilter, T>
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
int iscale_x = round(fx);
int iscale_y = round(fy);
if( std::abs(fx - iscale_x) < FLT_MIN && std::abs(fy - iscale_y) < FLT_MIN)
ResizeDispatcherStream<IntegerAreaFilter, T>::call(src, fx, fy, dst, stream);
else
ResizeDispatcherStream<AreaFilter, T>::call(src, fx, fy, dst, stream);
}
};
template <typename T> void resize_gpu(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float fx, float fy,
DevMem2Db dst, int interpolation, cudaStream_t stream)
{
typedef void (*caller_t)(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream);
static const caller_t callers[3] =
static const caller_t callers[4] =
{
ResizeDispatcher<PointFilter, T>::call, ResizeDispatcher<LinearFilter, T>::call, ResizeDispatcher<CubicFilter, T>::call
ResizeDispatcher<PointFilter, T>::call,
ResizeDispatcher<LinearFilter, T>::call,
ResizeDispatcher<CubicFilter, T>::call,
ResizeDispatcher<AreaFilter, T>::call
};
callers[interpolation](static_cast< DevMem2D_<T> >(src), static_cast< DevMem2D_<T> >(srcWhole), xoff, yoff, fx, fy,
......
modules/gpu/src/opencv2/gpu/device/filters.hpp
浏览文件 @ d192117e
......@@ -55,7 +55,7 @@ namespace cv { namespace gpu { namespace device
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
......@@ -70,7 +70,7 @@ namespace cv { namespace gpu { namespace device
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
......@@ -107,7 +107,7 @@ namespace cv { namespace gpu { namespace device
typedef float index_type;
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
static __device__ __forceinline__ float bicubicCoeff(float x_)
{
......@@ -154,6 +154,111 @@ namespace cv { namespace gpu { namespace device
const Ptr2D src;
};
// for integer scaling
template <typename Ptr2D> struct IntegerAreaFilter
{
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ IntegerAreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
: src(src_), scale_x(scale_x_), scale_y(scale_y_), scale(1.f / (scale_x * scale_y)) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
float fsx1 = x * scale_x;
float fsx2 = fsx1 + scale_x;
int sx1 = __float2int_ru(fsx1);
int sx2 = __float2int_rd(fsx2);
float fsy1 = y * scale_y;
float fsy2 = fsy1 + scale_y;
int sy1 = __float2int_ru(fsy1);
int sy2 = __float2int_rd(fsy2);
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
work_type out = VecTraits<work_type>::all(0.f);
for(int dy = sy1; dy < sy2; ++dy)
for(int dx = sx1; dx < sx2; ++dx)
{
out = out + src(dy, dx) * scale;
}
return saturate_cast<elem_type>(out);
}
const Ptr2D src;
float scale_x, scale_y ,scale;
};
template <typename Ptr2D> struct AreaFilter
{
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ AreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
: src(src_), scale_x(scale_x_), scale_y(scale_y_){}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
float fsx1 = x * scale_x;
float fsx2 = fsx1 + scale_x;
int sx1 = __float2int_ru(fsx1);
int sx2 = __float2int_rd(fsx2);
float fsy1 = y * scale_y;
float fsy2 = fsy1 + scale_y;
int sy1 = __float2int_ru(fsy1);
int sy2 = __float2int_rd(fsy2);
float scale = 1.f / (fminf(scale_x, src.width - fsx1) * fminf(scale_y, src.height - fsy1));
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
work_type out = VecTraits<work_type>::all(0.f);
for (int dy = sy1; dy < sy2; ++dy)
{
for (int dx = sx1; dx < sx2; ++dx)
out = out + src(dy, dx) * scale;
if (sx1 > fsx1)
out = out + src(dy, (sx1 -1) ) * ((sx1 - fsx1) * scale);
if (sx2 < fsx2)
out = out + src(dy, sx2) * ((fsx2 -sx2) * scale);
}
if (sy1 > fsy1)
for (int dx = sx1; dx < sx2; ++dx)
out = out + src( (sy1 - 1) , dx) * ((sy1 -fsy1) * scale);
if (sy2 < fsy2)
for (int dx = sx1; dx < sx2; ++dx)
out = out + src(sy2, dx) * ((fsy2 -sy2) * scale);
if ((sy1 > fsy1) && (sx1 > fsx1))
out = out + src( (sy1 - 1) , (sx1 - 1)) * ((sy1 -fsy1) * (sx1 -fsx1) * scale);
if ((sy1 > fsy1) && (sx2 < fsx2))
out = out + src( (sy1 - 1) , sx2) * ((sy1 -fsy1) * (fsx2 -sx2) * scale);
if ((sy2 < fsy2) && (sx2 < fsx2))
out = out + src(sy2, sx2) * ((fsy2 -sy2) * (fsx2 -sx2) * scale);
if ((sy2 < fsy2) && (sx1 > fsx1))
out = out + src(sy2, (sx1 - 1)) * ((fsy2 -sy2) * (sx1 -fsx1) * scale);
return saturate_cast<elem_type>(out);
}
const Ptr2D src;
float scale_x, scale_y;
int width, haight;
};
}}} // namespace cv { namespace gpu { namespace device
#endif // __OPENCV_GPU_FILTERS_HPP__
modules/gpu/src/opencv2/gpu/device/vec_traits.hpp
浏览文件 @ d192117e
......@@ -221,7 +221,7 @@ namespace cv { namespace gpu { namespace device
template<> struct VecTraits<char>
{
typedef char elem_type;
typedef char elem_type;
enum {cn=1};
static __device__ __host__ __forceinline__ char all(char v) {return v;}
static __device__ __host__ __forceinline__ char make(char x) {return x;}
......@@ -229,7 +229,7 @@ namespace cv { namespace gpu { namespace device
};
template<> struct VecTraits<schar>
{
typedef schar elem_type;
typedef schar elem_type;
enum {cn=1};
static __device__ __host__ __forceinline__ schar all(schar v) {return v;}
static __device__ __host__ __forceinline__ schar make(schar x) {return x;}
......
modules/gpu/src/resize.cpp
浏览文件 @ d192117e
......@@ -61,7 +61,8 @@ namespace cv { namespace gpu { namespace device
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
{
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR
|| interpolation == INTER_CUBIC || interpolation == INTER_AREA);
CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));
if (dsize == Size())
......
modules/gpu/test/test_resize.cpp
浏览文件 @ d192117e
......@@ -48,7 +48,8 @@
namespace
{
template <typename T, template <typename> class Interpolator> void resizeImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
template <typename T, template <typename> class Interpolator>
void resizeImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
{
const int cn = src.channels();
......@@ -156,6 +157,51 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
WHOLE_SUBMAT));
/////////////////
PARAM_TEST_CASE(ResizeArea, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
double coeff;
int interpolation;
int type;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
coeff = GET_PARAM(3);
interpolation = GET_PARAM(4);
useRoi = GET_PARAM(5);
cv::gpu::setDevice(devInfo.deviceID());
}
};
TEST_P(ResizeArea, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
cv::Mat dst_cpu;
cv::resize(src, dst_cpu, cv::Size(), coeff, coeff, interpolation);
EXPECT_MAT_NEAR(dst_cpu, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeArea, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(/*0.3,*/0.5),
testing::Values(Interpolation(cv::INTER_AREA)),
WHOLE_SUBMAT));
///////////////////////////////////////////////////////////////////
// Test NPP
......
modules/gpu/test/utility.hpp
浏览文件 @ d192117e
......@@ -277,7 +277,7 @@ IMPLEMENT_PARAM_CLASS(Channels, int)
CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::INTER_AREA)
CV_ENUM(BorderType, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP)
#define ALL_BORDER_TYPES testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP))
......
modules/imgproc/src/imgwarp.cpp
浏览文件 @ d192117e
......@@ -878,8 +878,8 @@ struct VResizeLinear
VecOp vecOp;
int x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT t0, t1;
t0 = S0[x]*b0 + S1[x]*b1;
......@@ -1035,7 +1035,7 @@ struct VResizeLanczos4
CastOp castOp;
VecOp vecOp;
int k, x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT b = beta[0];
......@@ -1130,7 +1130,7 @@ static void resizeGeneric_( const Mat& src, Mat& dst,
if( k0 < ksize )
hresize( srows + k0, rows + k0, ksize - k0, xofs, alpha,
ssize.width, dsize.width, cn, xmin, xmax );
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
}
}
......@@ -1163,8 +1163,8 @@ static void resizeAreaFast_( const Mat& src, Mat& dst, const int* ofs, const int
{
const T* S = (const T*)(src.data + src.step*sy0) + xofs[dx];
WT sum = 0;
k=0;
#if CV_ENABLE_UNROLLED
k=0;
#if CV_ENABLE_UNROLLED
for( ; k <= area - 4; k += 4 )
sum += S[ofs[k]] + S[ofs[k+1]] + S[ofs[k+2]] + S[ofs[k+3]];
#endif
......@@ -1329,11 +1329,11 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
resizeGeneric_<
HResizeLinear<uchar, int, short,
INTER_RESIZE_COEF_SCALE,
HResizeLinearVec_8u32s>,
HResizeLinearVec_8u32s>,
VResizeLinear<uchar, int, short,
FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
VResizeLinearVec_32s8u> >,
0,
VResizeLinearVec_32s8u> >,
0,
resizeGeneric_<
HResizeLinear<ushort, float, float, 1,
HResizeLinearVec_16u32f>,
......@@ -1344,7 +1344,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
HResizeLinearVec_16s32f>,
VResizeLinear<short, float, float, Cast<float, short>,
VResizeLinearVec_32f16s> >,
0,
0,
resizeGeneric_<
HResizeLinear<float, float, float, 1,
HResizeLinearVec_32f>,
......@@ -1374,7 +1374,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
HResizeCubic<short, float, float>,
VResizeCubic<short, float, float, Cast<float, short>,
VResizeCubicVec_32f16s> >,
0,
0,
resizeGeneric_<
HResizeCubic<float, float, float>,
VResizeCubic<float, float, float, Cast<float, float>,
......@@ -1396,10 +1396,10 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
resizeGeneric_<HResizeLanczos4<ushort, float, float>,
VResizeLanczos4<ushort, float, float, Cast<float, ushort>,
VResizeNoVec> >,
resizeGeneric_<HResizeLanczos4<short, float, float>,
resizeGeneric_<HResizeLanczos4<short, float, float>,
VResizeLanczos4<short, float, float, Cast<float, short>,
VResizeNoVec> >,
0,
0,
resizeGeneric_<HResizeLanczos4<float, float, float>,
VResizeLanczos4<float, float, float, Cast<float, float>,
VResizeNoVec> >,
......@@ -1412,8 +1412,8 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
static ResizeAreaFastFunc areafast_tab[] =
{
resizeAreaFast_<uchar, int>, 0,
resizeAreaFast_<ushort, float>,
resizeAreaFast_<short, float>,
resizeAreaFast_<ushort, float>,
resizeAreaFast_<short, float>,
0,
resizeAreaFast_<float, float>,
resizeAreaFast_<double, double>,
......@@ -1528,7 +1528,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
assert( k < ssize.width*2 );
xofs[k].di = dx*cn;
xofs[k].si = sx2*cn;
xofs[k++].alpha = (float)((fsx2 - sx2)*scale);
xofs[k++].alpha = (float)(min(fsx2 - sx2, 1.)*scale);
}
}
......@@ -3480,7 +3480,7 @@ void cvLinearPolar( const CvArr* srcarr, CvArr* dstarr,
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedFormats, "" );
ssize.width = src->cols;
ssize.width = src->cols;
ssize.height = src->rows;
dsize.width = dst->cols;
dsize.height = dst->rows;
......
modules/imgproc/test/test_imgwarp.cpp
浏览文件 @ d192117e
......@@ -1462,6 +1462,40 @@ TEST(Imgproc_fitLine_Mat_3dC1, regression)
ASSERT_EQ(line2.size(), (size_t)6);
}
TEST(Imgproc_resize_area, regression)
{
static ushort input_data[16 * 16] = {
90, 94, 80, 3, 231, 2, 186, 245, 188, 165, 10, 19, 201, 169, 8, 228,
86, 5, 203, 120, 136, 185, 24, 94, 81, 150, 163, 137, 88, 105, 132, 132,
236, 48, 250, 218, 19, 52, 54, 221, 159, 112, 45, 11, 152, 153, 112, 134,
78, 133, 136, 83, 65, 76, 82, 250, 9, 235, 148, 26, 236, 179, 200, 50,
99, 51, 103, 142, 201, 65, 176, 33, 49, 226, 177, 109, 46, 21, 67, 130,
54, 125, 107, 154, 145, 51, 199, 189, 161, 142, 231, 240, 139, 162, 240, 22,
231, 86, 79, 106, 92, 47, 146, 156, 36, 207, 71, 33, 2, 244, 221, 71,
44, 127, 71, 177, 75, 126, 68, 119, 200, 129, 191, 251, 6, 236, 247, 6,
133, 175, 56, 239, 147, 221, 243, 154, 242, 82, 106, 99, 77, 158, 60, 229,
2, 42, 24, 174, 27, 198, 14, 204, 246, 251, 141, 31, 114, 163, 29, 147,
121, 53, 74, 31, 147, 189, 42, 98, 202, 17, 228, 123, 209, 40, 77, 49,
112, 203, 30, 12, 205, 25, 19, 106, 145, 185, 163, 201, 237, 223, 247, 38,
33, 105, 243, 117, 92, 179, 204, 248, 160, 90, 73, 126, 2, 41, 213, 204,
6, 124, 195, 201, 230, 187, 210, 167, 48, 79, 123, 159, 145, 218, 105, 209,
240, 152, 136, 235, 235, 164, 157, 9, 152, 38, 27, 209, 120, 77, 238, 196,
240, 233, 10, 241, 90, 67, 12, 79, 0, 43, 58, 27, 83, 199, 190, 182};
static ushort expected_data = {
// row 1
120, 100, 151, 101, 103,//?
// row 2
106, 115, 141, 130, suturate_cast<ushort>(0),
// row 3
91, 136, 170, 114, suturate_cast<ushort>(0),
// row 4
104, 122, 131, 147, suturate_cast<ushort>(0),
// row 5
suturate_cast<ushort>(0),suturate_cast<ushort>(0),suturate_cast<ushort>(0),suturate_cast<ushort>(0),suturate_cast<ushort>(0)
};
}
//////////////////////////////////////////////////////////////////////////
TEST(Imgproc_Resize, accuracy) { CV_ResizeTest test; test.safe_run(); }
......
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