opencv/modules/gpu/src/warp.cpp
2013-02-26 13:53:38 +04:00

455 lines
19 KiB
C++

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#include "precomp.hpp"
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
void cv::gpu::warpAffine(const GpuMat&, GpuMat&, const Mat&, Size, int, int, Scalar, Stream&) { throw_nogpu(); }
void cv::gpu::buildWarpAffineMaps(const Mat&, bool, Size, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::warpPerspective(const GpuMat&, GpuMat&, const Mat&, Size, int, int, Scalar, Stream&) { throw_nogpu(); }
void cv::gpu::buildWarpPerspectiveMaps(const Mat&, bool, Size, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
#else // HAVE_CUDA
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
void buildWarpAffineMaps_gpu(float coeffs[2 * 3], PtrStepSzf xmap, PtrStepSzf ymap, cudaStream_t stream);
template <typename T>
void warpAffine_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
void buildWarpPerspectiveMaps_gpu(float coeffs[3 * 3], PtrStepSzf xmap, PtrStepSzf ymap, cudaStream_t stream);
template <typename T>
void warpPerspective_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[3 * 3], PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
}
}}}
void cv::gpu::buildWarpAffineMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream)
{
using namespace cv::gpu::device::imgproc;
CV_Assert(M.rows == 2 && M.cols == 3);
xmap.create(dsize, CV_32FC1);
ymap.create(dsize, CV_32FC1);
float coeffs[2 * 3];
Mat coeffsMat(2, 3, CV_32F, (void*)coeffs);
if (inverse)
M.convertTo(coeffsMat, coeffsMat.type());
else
{
cv::Mat iM;
invertAffineTransform(M, iM);
iM.convertTo(coeffsMat, coeffsMat.type());
}
buildWarpAffineMaps_gpu(coeffs, xmap, ymap, StreamAccessor::getStream(stream));
}
void cv::gpu::buildWarpPerspectiveMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream)
{
using namespace cv::gpu::device::imgproc;
CV_Assert(M.rows == 3 && M.cols == 3);
xmap.create(dsize, CV_32FC1);
ymap.create(dsize, CV_32FC1);
float coeffs[3 * 3];
Mat coeffsMat(3, 3, CV_32F, (void*)coeffs);
if (inverse)
M.convertTo(coeffsMat, coeffsMat.type());
else
{
cv::Mat iM;
invert(M, iM);
iM.convertTo(coeffsMat, coeffsMat.type());
}
buildWarpPerspectiveMaps_gpu(coeffs, xmap, ymap, StreamAccessor::getStream(stream));
}
namespace
{
template<int DEPTH> struct NppTypeTraits;
template<> struct NppTypeTraits<CV_8U> { typedef Npp8u npp_t; };
template<> struct NppTypeTraits<CV_8S> { typedef Npp8s npp_t; };
template<> struct NppTypeTraits<CV_16U> { typedef Npp16u npp_t; };
template<> struct NppTypeTraits<CV_16S> { typedef Npp16s npp_t; typedef Npp16sc npp_complex_type; };
template<> struct NppTypeTraits<CV_32S> { typedef Npp32s npp_t; typedef Npp32sc npp_complex_type; };
template<> struct NppTypeTraits<CV_32F> { typedef Npp32f npp_t; typedef Npp32fc npp_complex_type; };
template<> struct NppTypeTraits<CV_64F> { typedef Npp64f npp_t; typedef Npp64fc npp_complex_type; };
template <int DEPTH> struct NppWarpFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, NppiSize srcSize, int srcStep, NppiRect srcRoi, npp_t* pDst,
int dstStep, NppiRect dstRoi, const double coeffs[][3],
int interpolation);
};
template <int DEPTH, typename NppWarpFunc<DEPTH>::func_t func> struct NppWarp
{
typedef typename NppWarpFunc<DEPTH>::npp_t npp_t;
static void call(const cv::gpu::GpuMat& src, cv::gpu::GpuMat& dst, double coeffs[][3], int interpolation, cudaStream_t stream)
{
static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC};
NppiSize srcsz;
srcsz.height = src.rows;
srcsz.width = src.cols;
NppiRect srcroi;
srcroi.x = 0;
srcroi.y = 0;
srcroi.height = src.rows;
srcroi.width = src.cols;
NppiRect dstroi;
dstroi.x = 0;
dstroi.y = 0;
dstroi.height = dst.rows;
dstroi.width = dst.cols;
cv::gpu::NppStreamHandler h(stream);
nppSafeCall( func(src.ptr<npp_t>(), srcsz, static_cast<int>(src.step), srcroi,
dst.ptr<npp_t>(), static_cast<int>(dst.step), dstroi,
coeffs, npp_inter[interpolation]) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& s)
{
CV_Assert(M.rows == 2 && M.cols == 3);
int interpolation = flags & INTER_MAX;
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
CV_Assert(borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP);
dst.create(dsize, src.type());
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
static const bool useNppTab[6][4][3] =
{
{
{false, false, true},
{false, false, false},
{false, true, true},
{false, false, false}
},
{
{false, false, false},
{false, false, false},
{false, false, false},
{false, false, false}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, false}
},
{
{false, false, false},
{false, false, false},
{false, false, false},
{false, false, false}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, true}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, true}
}
};
bool useNpp = borderMode == BORDER_CONSTANT && ofs.x == 0 && ofs.y == 0 && useNppTab[src.depth()][src.channels() - 1][interpolation];
// NPP bug on float data
useNpp = useNpp && src.depth() != CV_32F;
if (useNpp)
{
typedef void (*func_t)(const cv::gpu::GpuMat& src, cv::gpu::GpuMat& dst, double coeffs[][3], int flags, cudaStream_t stream);
static const func_t funcs[2][6][4] =
{
{
{NppWarp<CV_8U, nppiWarpAffine_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpAffine_8u_C3R>::call, NppWarp<CV_8U, nppiWarpAffine_8u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_16U, nppiWarpAffine_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpAffine_16u_C3R>::call, NppWarp<CV_16U, nppiWarpAffine_16u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_32S, nppiWarpAffine_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpAffine_32s_C3R>::call, NppWarp<CV_32S, nppiWarpAffine_32s_C4R>::call},
{NppWarp<CV_32F, nppiWarpAffine_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpAffine_32f_C3R>::call, NppWarp<CV_32F, nppiWarpAffine_32f_C4R>::call}
},
{
{NppWarp<CV_8U, nppiWarpAffineBack_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpAffineBack_8u_C3R>::call, NppWarp<CV_8U, nppiWarpAffineBack_8u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_16U, nppiWarpAffineBack_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpAffineBack_16u_C3R>::call, NppWarp<CV_16U, nppiWarpAffineBack_16u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_32S, nppiWarpAffineBack_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpAffineBack_32s_C3R>::call, NppWarp<CV_32S, nppiWarpAffineBack_32s_C4R>::call},
{NppWarp<CV_32F, nppiWarpAffineBack_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpAffineBack_32f_C3R>::call, NppWarp<CV_32F, nppiWarpAffineBack_32f_C4R>::call}
}
};
dst.setTo(borderValue);
double coeffs[2][3];
Mat coeffsMat(2, 3, CV_64F, (void*)coeffs);
M.convertTo(coeffsMat, coeffsMat.type());
const func_t func = funcs[(flags & WARP_INVERSE_MAP) != 0][src.depth()][src.channels() - 1];
CV_Assert(func != 0);
func(src, dst, coeffs, interpolation, StreamAccessor::getStream(s));
}
else
{
using namespace cv::gpu::device::imgproc;
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
static const func_t funcs[6][4] =
{
{warpAffine_gpu<uchar> , 0 /*warpAffine_gpu<uchar2>*/ , warpAffine_gpu<uchar3> , warpAffine_gpu<uchar4> },
{0 /*warpAffine_gpu<schar>*/, 0 /*warpAffine_gpu<char2>*/ , 0 /*warpAffine_gpu<char3>*/, 0 /*warpAffine_gpu<char4>*/},
{warpAffine_gpu<ushort> , 0 /*warpAffine_gpu<ushort2>*/, warpAffine_gpu<ushort3> , warpAffine_gpu<ushort4> },
{warpAffine_gpu<short> , 0 /*warpAffine_gpu<short2>*/ , warpAffine_gpu<short3> , warpAffine_gpu<short4> },
{0 /*warpAffine_gpu<int>*/ , 0 /*warpAffine_gpu<int2>*/ , 0 /*warpAffine_gpu<int3>*/ , 0 /*warpAffine_gpu<int4>*/ },
{warpAffine_gpu<float> , 0 /*warpAffine_gpu<float2>*/ , warpAffine_gpu<float3> , warpAffine_gpu<float4> }
};
const func_t func = funcs[src.depth()][src.channels() - 1];
CV_Assert(func != 0);
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));
float coeffs[2 * 3];
Mat coeffsMat(2, 3, CV_32F, (void*)coeffs);
if (flags & WARP_INVERSE_MAP)
M.convertTo(coeffsMat, coeffsMat.type());
else
{
cv::Mat iM;
invertAffineTransform(M, iM);
iM.convertTo(coeffsMat, coeffsMat.type());
}
Scalar_<float> borderValueFloat;
borderValueFloat = borderValue;
func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, coeffs,
dst, interpolation, gpuBorderType, borderValueFloat.val, StreamAccessor::getStream(s), deviceSupports(FEATURE_SET_COMPUTE_20));
}
}
void cv::gpu::warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& s)
{
CV_Assert(M.rows == 3 && M.cols == 3);
int interpolation = flags & INTER_MAX;
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
CV_Assert(borderMode == BORDER_REFLECT101 || borderMode == BORDER_REPLICATE || borderMode == BORDER_CONSTANT || borderMode == BORDER_REFLECT || borderMode == BORDER_WRAP);
dst.create(dsize, src.type());
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
static const bool useNppTab[6][4][3] =
{
{
{false, false, true},
{false, false, false},
{false, true, true},
{false, false, false}
},
{
{false, false, false},
{false, false, false},
{false, false, false},
{false, false, false}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, false}
},
{
{false, false, false},
{false, false, false},
{false, false, false},
{false, false, false}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, true}
},
{
{false, true, true},
{false, false, false},
{false, true, true},
{false, false, true}
}
};
bool useNpp = borderMode == BORDER_CONSTANT && ofs.x == 0 && ofs.y == 0 && useNppTab[src.depth()][src.channels() - 1][interpolation];
// NPP bug on float data
useNpp = useNpp && src.depth() != CV_32F;
if (useNpp)
{
typedef void (*func_t)(const cv::gpu::GpuMat& src, cv::gpu::GpuMat& dst, double coeffs[][3], int flags, cudaStream_t stream);
static const func_t funcs[2][6][4] =
{
{
{NppWarp<CV_8U, nppiWarpPerspective_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpPerspective_8u_C3R>::call, NppWarp<CV_8U, nppiWarpPerspective_8u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_16U, nppiWarpPerspective_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpPerspective_16u_C3R>::call, NppWarp<CV_16U, nppiWarpPerspective_16u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_32S, nppiWarpPerspective_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpPerspective_32s_C3R>::call, NppWarp<CV_32S, nppiWarpPerspective_32s_C4R>::call},
{NppWarp<CV_32F, nppiWarpPerspective_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpPerspective_32f_C3R>::call, NppWarp<CV_32F, nppiWarpPerspective_32f_C4R>::call}
},
{
{NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C1R>::call, 0, NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C3R>::call, NppWarp<CV_8U, nppiWarpPerspectiveBack_8u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C1R>::call, 0, NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C3R>::call, NppWarp<CV_16U, nppiWarpPerspectiveBack_16u_C4R>::call},
{0, 0, 0, 0},
{NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C1R>::call, 0, NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C3R>::call, NppWarp<CV_32S, nppiWarpPerspectiveBack_32s_C4R>::call},
{NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C1R>::call, 0, NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C3R>::call, NppWarp<CV_32F, nppiWarpPerspectiveBack_32f_C4R>::call}
}
};
dst.setTo(borderValue);
double coeffs[3][3];
Mat coeffsMat(3, 3, CV_64F, (void*)coeffs);
M.convertTo(coeffsMat, coeffsMat.type());
const func_t func = funcs[(flags & WARP_INVERSE_MAP) != 0][src.depth()][src.channels() - 1];
CV_Assert(func != 0);
func(src, dst, coeffs, interpolation, StreamAccessor::getStream(s));
}
else
{
using namespace cv::gpu::device::imgproc;
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float coeffs[2 * 3], PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
static const func_t funcs[6][4] =
{
{warpPerspective_gpu<uchar> , 0 /*warpPerspective_gpu<uchar2>*/ , warpPerspective_gpu<uchar3> , warpPerspective_gpu<uchar4> },
{0 /*warpPerspective_gpu<schar>*/, 0 /*warpPerspective_gpu<char2>*/ , 0 /*warpPerspective_gpu<char3>*/, 0 /*warpPerspective_gpu<char4>*/},
{warpPerspective_gpu<ushort> , 0 /*warpPerspective_gpu<ushort2>*/, warpPerspective_gpu<ushort3> , warpPerspective_gpu<ushort4> },
{warpPerspective_gpu<short> , 0 /*warpPerspective_gpu<short2>*/ , warpPerspective_gpu<short3> , warpPerspective_gpu<short4> },
{0 /*warpPerspective_gpu<int>*/ , 0 /*warpPerspective_gpu<int2>*/ , 0 /*warpPerspective_gpu<int3>*/ , 0 /*warpPerspective_gpu<int4>*/ },
{warpPerspective_gpu<float> , 0 /*warpPerspective_gpu<float2>*/ , warpPerspective_gpu<float3> , warpPerspective_gpu<float4> }
};
const func_t func = funcs[src.depth()][src.channels() - 1];
CV_Assert(func != 0);
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));
float coeffs[3 * 3];
Mat coeffsMat(3, 3, CV_32F, (void*)coeffs);
if (flags & WARP_INVERSE_MAP)
M.convertTo(coeffsMat, coeffsMat.type());
else
{
cv::Mat iM;
invert(M, iM);
iM.convertTo(coeffsMat, coeffsMat.type());
}
Scalar_<float> borderValueFloat;
borderValueFloat = borderValue;
func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, coeffs,
dst, interpolation, gpuBorderType, borderValueFloat.val, StreamAccessor::getStream(s), deviceSupports(FEATURE_SET_COMPUTE_20));
}
}
#endif // HAVE_CUDA