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refactored and fixed bugs in gpu warp functions (remap, resize, warpAffine, warpPerspective)

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wrote more complicated tests for them
implemented own version of warpAffine and warpPerspective for different border interpolation types
refactored some gpu tests
This commit is contained in:
Vladislav Vinogradov
2012-03-14 15:54:17 +00:00
parent 6e2507c197
commit ade7394e77
33 changed files with 6243 additions and 4545 deletions
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56
modules/gpu/src/cuda/remap.cu
View File

@@ -47,10 +47,10 @@
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/filters.hpp"
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
namespace imgproc
{
template <typename Ptr2D, typename T> __global__ void remap(const Ptr2D src, const PtrStepf mapx, const PtrStepf mapy, DevMem2D_<T> dst)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
@@ -67,11 +67,10 @@ namespace cv { namespace gpu { namespace device
template <template <typename> class Filter, template <typename> class B, typename T> struct RemapDispatcherStream
{
static void call(DevMem2D_<T> src, DevMem2Df mapx, DevMem2Df mapy, DevMem2D_<T> dst,
const float* borderValue, cudaStream_t stream, int)
static void call(DevMem2D_<T> src, DevMem2Df mapx, DevMem2Df mapy, DevMem2D_<T> dst, const float* borderValue, cudaStream_t stream, int)
{
typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type work_type;
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
@@ -86,11 +85,10 @@ namespace cv { namespace gpu { namespace device
template <template <typename> class Filter, template <typename> class B, typename T> struct RemapDispatcherNonStream
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2Df mapx, DevMem2Df mapy,
DevMem2D_<T> dst, const float* borderValue, int)
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2Df mapx, DevMem2Df mapy, DevMem2D_<T> dst, const float* borderValue, int)
{
typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type work_type;
typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type work_type;
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
@@ -189,7 +187,7 @@ namespace cv { namespace gpu { namespace device
#undef OPENCV_GPU_IMPLEMENT_REMAP_TEX
template <template <typename> class Filter, template <typename> class B, typename T> struct RemapDispatcher
{
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2Df mapx, DevMem2Df mapy,
DevMem2D_<T> dst, const float* borderValue, cudaStream_t stream, int cc)
{
@@ -208,26 +206,26 @@ namespace cv { namespace gpu { namespace device
static const caller_t callers[3][5] =
{
{
RemapDispatcher<PointFilter, BrdReflect101, T>::call,
RemapDispatcher<PointFilter, BrdReplicate, T>::call,
RemapDispatcher<PointFilter, BrdConstant, T>::call,
RemapDispatcher<PointFilter, BrdReflect, T>::call,
RemapDispatcher<PointFilter, BrdWrap, T>::call
{
RemapDispatcher<PointFilter, BrdReflect101, T>::call,
RemapDispatcher<PointFilter, BrdReplicate, T>::call,
RemapDispatcher<PointFilter, BrdConstant, T>::call,
RemapDispatcher<PointFilter, BrdReflect, T>::call,
RemapDispatcher<PointFilter, BrdWrap, T>::call
},
{
RemapDispatcher<LinearFilter, BrdReflect101, T>::call,
RemapDispatcher<LinearFilter, BrdReplicate, T>::call,
RemapDispatcher<LinearFilter, BrdConstant, T>::call,
RemapDispatcher<LinearFilter, BrdReflect, T>::call,
RemapDispatcher<LinearFilter, BrdWrap, T>::call
{
RemapDispatcher<LinearFilter, BrdReflect101, T>::call,
RemapDispatcher<LinearFilter, BrdReplicate, T>::call,
RemapDispatcher<LinearFilter, BrdConstant, T>::call,
RemapDispatcher<LinearFilter, BrdReflect, T>::call,
RemapDispatcher<LinearFilter, BrdWrap, T>::call
},
{
RemapDispatcher<CubicFilter, BrdReflect101, T>::call,
RemapDispatcher<CubicFilter, BrdReplicate, T>::call,
RemapDispatcher<CubicFilter, BrdConstant, T>::call,
RemapDispatcher<CubicFilter, BrdReflect, T>::call,
RemapDispatcher<CubicFilter, BrdWrap, T>::call
{
RemapDispatcher<CubicFilter, BrdReflect101, T>::call,
RemapDispatcher<CubicFilter, BrdReplicate, T>::call,
RemapDispatcher<CubicFilter, BrdConstant, T>::call,
RemapDispatcher<CubicFilter, BrdReflect, T>::call,
RemapDispatcher<CubicFilter, BrdWrap, T>::call
}
};

121
modules/gpu/src/cuda/resize.cu
View File

@@ -47,10 +47,10 @@
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/filters.hpp"
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
namespace imgproc
{
template <typename Ptr2D, typename T> __global__ void resize(const Ptr2D src, float fx, float fy, DevMem2D_<T> dst)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
@@ -58,52 +58,25 @@ namespace cv { namespace gpu { namespace device
if (x < dst.cols && y < dst.rows)
{
const float xcoo = x / fx;
const float ycoo = y / fy;
const float xcoo = x * fx;
const float ycoo = y * fy;
dst.ptr(y)[x] = saturate_cast<T>(src(ycoo, xcoo));
}
}
template <typename Ptr2D, typename T> __global__ void resizeNN(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)
{
const float xcoo = x / fx;
const float ycoo = y / fy;
dst.ptr(y)[x] = src(__float2int_rd(ycoo), __float2int_rd(xcoo));
dst(y, x) = saturate_cast<T>(src(ycoo, xcoo));
}
}
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)
{
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filter_src(brdSrc);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc);
resize<<<grid, block, 0, stream>>>(filter_src, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <typename T> struct ResizeDispatcherStream<PointFilter, 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));
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
resizeNN<<<grid, block, 0, stream>>>(brdSrc, fx, fy, dst);
resize<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
@@ -111,31 +84,15 @@ namespace cv { namespace gpu { namespace device
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)
{
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filter_src(brdSrc);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc);
resize<<<grid, block>>>(filter_src, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename T> struct ResizeDispatcherNonStream<PointFilter, T>
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst)
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
resizeNN<<<grid, block>>>(brdSrc, fx, fy, dst);
resize<<<grid, block>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
@@ -148,73 +105,61 @@ namespace cv { namespace gpu { namespace device
{ \
typedef type elem_type; \
typedef int index_type; \
int xoff, yoff; \
tex_resize_ ## type ## _reader (int xoff_, int yoff_) : xoff(xoff_), yoff(yoff_) {} \
const int xoff; \
const int yoff; \
__host__ tex_resize_ ## type ## _reader(int xoff_, int yoff_) : xoff(xoff_), yoff(yoff_) {} \
__device__ __forceinline__ elem_type operator ()(index_type y, index_type x) const \
{ \
return tex2D(tex_resize_ ## type , x + xoff, y + yoff); \
return tex2D(tex_resize_ ## type, x + xoff, y + yoff); \
} \
}; \
template <template <typename> class Filter> struct ResizeDispatcherNonStream<Filter, type> \
template <template <typename> class Filter> struct ResizeDispatcherNonStream<Filter, type > \
{ \
static void call(DevMem2D_< type > src, DevMem2D_< type > srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_< type > dst) \
{ \
dim3 block(32, 8); \
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y)); \
bindTexture(&tex_resize_ ## type , srcWhole); \
tex_resize_ ## type ##_reader texSrc(xoff, yoff); \
BrdReplicate< type > brd(src.rows, src.cols); \
BorderReader< tex_resize_ ## type ##_reader , BrdReplicate< type > > brdSrc(texSrc, brd); \
Filter< BorderReader< tex_resize_ ## type ##_reader , BrdReplicate< type > > > filter_src(brdSrc); \
resize<<<grid, block>>>(filter_src, fx, fy, dst); \
cudaSafeCall( cudaGetLastError() ); \
cudaSafeCall( cudaDeviceSynchronize() ); \
} \
}; \
template <> struct ResizeDispatcherNonStream<PointFilter, type> \
{ \
static void call(DevMem2D_< type > src, DevMem2D_< type > srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_< type > dst) \
{ \
dim3 block(32, 8); \
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y)); \
bindTexture(&tex_resize_ ## type , srcWhole); \
tex_resize_ ## type ##_reader texSrc(xoff, yoff); \
BrdReplicate< type > brd(src.rows, src.cols); \
BorderReader< tex_resize_ ## type ##_reader , BrdReplicate< type > > brdSrc(texSrc, brd); \
resizeNN<<<grid, block>>>(brdSrc, fx, fy, dst); \
bindTexture(&tex_resize_ ## type, srcWhole); \
tex_resize_ ## type ## _reader texSrc(xoff, yoff); \
if (srcWhole.cols == src.cols && srcWhole.rows == src.rows) \
{ \
Filter<tex_resize_ ## type ## _reader> filteredSrc(texSrc); \
resize<<<grid, block>>>(filteredSrc, fx, fy, dst); \
} \
else \
{ \
BrdReplicate< type > brd(src.rows, src.cols); \
BorderReader<tex_resize_ ## type ## _reader, BrdReplicate< type > > brdSrc(texSrc, brd); \
Filter< BorderReader<tex_resize_ ## type ## _reader, BrdReplicate< type > > > filteredSrc(brdSrc); \
resize<<<grid, block>>>(filteredSrc, fx, fy, dst); \
} \
cudaSafeCall( cudaGetLastError() ); \
cudaSafeCall( cudaDeviceSynchronize() ); \
} \
};
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(uchar)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(uchar2)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(uchar4)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(schar)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(char2)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(char4)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(ushort)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(ushort2)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(ushort4)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(short)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(short2)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(short4)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(int)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(int2)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(int4)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(float)
//OPENCV_GPU_IMPLEMENT_RESIZE_TEX(float2)
OPENCV_GPU_IMPLEMENT_RESIZE_TEX(float4)
#undef OPENCV_GPU_IMPLEMENT_RESIZE_TEX
template <template <typename> class Filter, typename T> struct ResizeDispatcher
{
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
if (stream == 0)

380
modules/gpu/src/cuda/warp.cu Normal file
View File

@@ -0,0 +1,380 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "internal_shared.hpp"
#include "opencv2/gpu/device/border_interpolate.hpp"
#include "opencv2/gpu/device/vec_traits.hpp"
#include "opencv2/gpu/device/vec_math.hpp"
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/filters.hpp"
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
__constant__ float c_warpMat[3 * 3];
struct AffineTransform
{
static __device__ __forceinline__ float2 calcCoord(int x, int y)
{
const float xcoo = c_warpMat[0] * x + c_warpMat[1] * y + c_warpMat[2];
const float ycoo = c_warpMat[3] * x + c_warpMat[4] * y + c_warpMat[5];
return make_float2(xcoo, ycoo);
}
};
struct PerspectiveTransform
{
static __device__ __forceinline__ float2 calcCoord(int x, int y)
{
const float coeff = 1.0f / (c_warpMat[6] * x + c_warpMat[7] * y + c_warpMat[8]);
const float xcoo = coeff * (c_warpMat[0] * x + c_warpMat[1] * y + c_warpMat[2]);
const float ycoo = coeff * (c_warpMat[3] * x + c_warpMat[4] * y + c_warpMat[5]);
return make_float2(xcoo, ycoo);
}
};
///////////////////////////////////////////////////////////////////
// Build Maps
template <class Transform> __global__ void buildWarpMaps(DevMem2Df xmap, PtrStepf ymap)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < xmap.cols && y < xmap.rows)
{
const float2 coord = Transform::calcCoord(x, y);
xmap(y, x) = coord.x;
ymap(y, x) = coord.y;
}
}
template <class Transform> void buildWarpMaps_caller(DevMem2Df xmap, DevMem2Df ymap, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(xmap.cols, block.x), divUp(xmap.rows, block.y));
buildWarpMaps<Transform><<<grid, block, 0, stream>>>(xmap, ymap);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void buildWarpAffineMaps_gpu(float coeffs[2 * 3], DevMem2Df xmap, DevMem2Df ymap, cudaStream_t stream)
{
cudaSafeCall( cudaMemcpyToSymbol(c_warpMat, coeffs, 2 * 3 * sizeof(float)) );
buildWarpMaps_caller<AffineTransform>(xmap, ymap, stream);
}
void buildWarpPerspectiveMaps_gpu(float coeffs[3 * 3], DevMem2Df xmap, DevMem2Df ymap, cudaStream_t stream)
{
cudaSafeCall( cudaMemcpyToSymbol(c_warpMat, coeffs, 3 * 3 * sizeof(float)) );
buildWarpMaps_caller<PerspectiveTransform>(xmap, ymap, stream);
}
///////////////////////////////////////////////////////////////////
// Warp
template <class Transform, class Ptr2D, typename T> __global__ void warp(const Ptr2D src, 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)
{
const float2 coord = Transform::calcCoord(x, y);
dst.ptr(y)[x] = saturate_cast<T>(src(coord.y, coord.x));
}
}
template <class Transform, template <typename> class Filter, template <typename> class B, typename T> struct WarpDispatcherStream
{
static void call(DevMem2D_<T> src, DevMem2D_<T> dst, const float* borderValue, cudaStream_t stream, int)
{
typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type work_type;
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
B<work_type> brd(src.rows, src.cols, VecTraits<work_type>::make(borderValue));
BorderReader< PtrStep<T>, B<work_type> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, B<work_type> > > filter_src(brdSrc);
warp<Transform><<<grid, block, 0, stream>>>(filter_src, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <class Transform, template <typename> class Filter, template <typename> class B, typename T> struct WarpDispatcherNonStream
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2D_<T> dst, const float* borderValue, int)
{
typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type work_type;
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
B<work_type> brd(src.rows, src.cols, VecTraits<work_type>::make(borderValue));
BorderReader< PtrStep<T>, B<work_type> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, B<work_type> > > filter_src(brdSrc);
warp<Transform><<<grid, block>>>(filter_src, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
#define OPENCV_GPU_IMPLEMENT_WARP_TEX(type) \
texture< type , cudaTextureType2D > tex_warp_ ## type (0, cudaFilterModePoint, cudaAddressModeClamp); \
struct tex_warp_ ## type ## _reader \
{ \
typedef type elem_type; \
typedef int index_type; \
int xoff, yoff; \
tex_warp_ ## type ## _reader (int xoff_, int yoff_) : xoff(xoff_), yoff(yoff_) {} \
__device__ __forceinline__ elem_type operator ()(index_type y, index_type x) const \
{ \
return tex2D(tex_warp_ ## type , x + xoff, y + yoff); \
} \
}; \
template <class Transform, template <typename> class Filter, template <typename> class B> struct WarpDispatcherNonStream<Transform, Filter, B, type> \
{ \
static void call(DevMem2D_< type > src, DevMem2D_< type > srcWhole, int xoff, int yoff, DevMem2D_< type > dst, const float* borderValue, int cc) \
{ \
typedef typename TypeVec<float, VecTraits< type >::cn>::vec_type work_type; \
dim3 block(32, cc >= 20 ? 8 : 4); \
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y)); \
bindTexture(&tex_warp_ ## type , srcWhole); \
tex_warp_ ## type ##_reader texSrc(xoff, yoff); \
B<work_type> brd(src.rows, src.cols, VecTraits<work_type>::make(borderValue)); \
BorderReader< tex_warp_ ## type ##_reader, B<work_type> > brdSrc(texSrc, brd); \
Filter< BorderReader< tex_warp_ ## type ##_reader, B<work_type> > > filter_src(brdSrc); \
warp<Transform><<<grid, block>>>(filter_src, dst); \
cudaSafeCall( cudaGetLastError() ); \
cudaSafeCall( cudaDeviceSynchronize() ); \
} \
}; \
template <class Transform, template <typename> class Filter> struct WarpDispatcherNonStream<Transform, Filter, BrdReplicate, type> \
{ \
static void call(DevMem2D_< type > src, DevMem2D_< type > srcWhole, int xoff, int yoff, DevMem2D_< type > dst, const float*, int) \
{ \
dim3 block(32, 8); \
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y)); \
bindTexture(&tex_warp_ ## type , srcWhole); \
tex_warp_ ## type ##_reader texSrc(xoff, yoff); \
if (srcWhole.cols == src.cols && srcWhole.rows == src.rows) \
{ \
Filter< tex_warp_ ## type ##_reader > filter_src(texSrc); \
warp<Transform><<<grid, block>>>(filter_src, dst); \
} \
else \
{ \
BrdReplicate<type> brd(src.rows, src.cols); \
BorderReader< tex_warp_ ## type ##_reader, BrdReplicate<type> > brdSrc(texSrc, brd); \
Filter< BorderReader< tex_warp_ ## type ##_reader, BrdReplicate<type> > > filter_src(brdSrc); \
warp<Transform><<<grid, block>>>(filter_src, dst); \
} \
cudaSafeCall( cudaGetLastError() ); \
cudaSafeCall( cudaDeviceSynchronize() ); \
} \
};
OPENCV_GPU_IMPLEMENT_WARP_TEX(uchar)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(uchar2)
OPENCV_GPU_IMPLEMENT_WARP_TEX(uchar4)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(schar)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(char2)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(char4)
OPENCV_GPU_IMPLEMENT_WARP_TEX(ushort)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(ushort2)
OPENCV_GPU_IMPLEMENT_WARP_TEX(ushort4)
OPENCV_GPU_IMPLEMENT_WARP_TEX(short)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(short2)
OPENCV_GPU_IMPLEMENT_WARP_TEX(short4)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(int)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(int2)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(int4)
OPENCV_GPU_IMPLEMENT_WARP_TEX(float)
//OPENCV_GPU_IMPLEMENT_WARP_TEX(float2)
OPENCV_GPU_IMPLEMENT_WARP_TEX(float4)
#undef OPENCV_GPU_IMPLEMENT_WARP_TEX
template <class Transform, template <typename> class Filter, template <typename> class B, typename T> struct WarpDispatcher
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2D_<T> dst, const float* borderValue, cudaStream_t stream, int cc)
{
if (stream == 0)
WarpDispatcherNonStream<Transform, Filter, B, T>::call(src, srcWhole, xoff, yoff, dst, borderValue, cc);
else
WarpDispatcherStream<Transform, Filter, B, T>::call(src, dst, borderValue, stream, cc);
}
};
template <class Transform, typename T>
void warp_caller(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, DevMem2Db dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, int cc)
{
typedef void (*func_t)(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, DevMem2D_<T> dst, const float* borderValue, cudaStream_t stream, int cc);
static const func_t funcs[3][5] =
{
{
WarpDispatcher<Transform, PointFilter, BrdReflect101, T>::call,
WarpDispatcher<Transform, PointFilter, BrdReplicate, T>::call,
WarpDispatcher<Transform, PointFilter, BrdConstant, T>::call,
WarpDispatcher<Transform, PointFilter, BrdReflect, T>::call,
WarpDispatcher<Transform, PointFilter, BrdWrap, T>::call
},
{
WarpDispatcher<Transform, LinearFilter, BrdReflect101, T>::call,
WarpDispatcher<Transform, LinearFilter, BrdReplicate, T>::call,
WarpDispatcher<Transform, LinearFilter, BrdConstant, T>::call,
WarpDispatcher<Transform, LinearFilter, BrdReflect, T>::call,
WarpDispatcher<Transform, LinearFilter, BrdWrap, T>::call
},
{
WarpDispatcher<Transform, CubicFilter, BrdReflect101, T>::call,
WarpDispatcher<Transform, CubicFilter, BrdReplicate, T>::call,
WarpDispatcher<Transform, CubicFilter, BrdConstant, T>::call,
WarpDispatcher<Transform, CubicFilter, BrdReflect, T>::call,
WarpDispatcher<Transform, CubicFilter, BrdWrap, T>::call
}
};
funcs[interpolation][borderMode](static_cast< DevMem2D_<T> >(src), static_cast< DevMem2D_<T> >(srcWhole), xoff, yoff,
static_cast< DevMem2D_<T> >(dst), borderValue, stream, cc);
}
template <typename T> void warpAffine_gpu(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, int cc)
{
cudaSafeCall( cudaMemcpyToSymbol(c_warpMat, coeffs, 2 * 3 * sizeof(float)) );
warp_caller<AffineTransform, T>(src, srcWhole, xoff, yoff, dst, interpolation, borderMode, borderValue, stream, cc);
}
template void warpAffine_gpu<uchar >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<uchar2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<uchar3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<uchar4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<schar>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<char2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<char3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<char4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<ushort >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<ushort2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<ushort3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<ushort4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<short >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<short2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<short3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<short4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<int >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<int2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<int3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<int4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<float >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpAffine_gpu<float2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<float3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpAffine_gpu<float4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[2 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template <typename T> void warpPerspective_gpu(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, int cc)
{
cudaSafeCall( cudaMemcpyToSymbol(c_warpMat, coeffs, 3 * 3 * sizeof(float)) );
warp_caller<PerspectiveTransform, T>(src, srcWhole, xoff, yoff, dst, interpolation, borderMode, borderValue, stream, cc);
}
template void warpPerspective_gpu<uchar >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<uchar2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<uchar3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<uchar4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<schar>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<char2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<char3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<char4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<ushort >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<ushort2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<ushort3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<ushort4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<short >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<short2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<short3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<short4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<int >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<int2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<int3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<int4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<float >(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
//template void warpPerspective_gpu<float2>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<float3>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
template void warpPerspective_gpu<float4>(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float coeffs[3 * 3], DevMem2Db dst, int interpolation, int borderMode, const float* borderValue, cudaStream_t stream, int cc);
} // namespace imgproc
}}} // namespace cv { namespace gpu { namespace device