本文整理汇总了C++中GpuMat::locateROI方法的典型用法代码示例。如果您正苦于以下问题：C++ GpuMat::locateROI方法的具体用法？C++ GpuMat::locateROI怎么用？C++ GpuMat::locateROI使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类GpuMat的用法示例。
在下文中一共展示了GpuMat::locateROI方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: void
void cv::cuda::resize(InputArray _src, OutputArray _dst, Size dsize, double fx, double fy, int interpolation, Stream& stream)
{
GpuMat src = _src.getGpuMat();
typedef void (*func_t)(const PtrStepSzb& src, const PtrStepSzb& srcWhole, int yoff, int xoff, const PtrStepSzb& dst, float fy, float fx, int interpolation, cudaStream_t stream);
static const func_t funcs[6][4] =
{
{device::resize<uchar> , 0 /*device::resize<uchar2>*/ , device::resize<uchar3> , device::resize<uchar4> },
{0 /*device::resize<schar>*/, 0 /*device::resize<char2>*/ , 0 /*device::resize<char3>*/, 0 /*device::resize<char4>*/},
{device::resize<ushort> , 0 /*device::resize<ushort2>*/, device::resize<ushort3> , device::resize<ushort4> },
{device::resize<short> , 0 /*device::resize<short2>*/ , device::resize<short3> , device::resize<short4> },
{0 /*device::resize<int>*/ , 0 /*device::resize<int2>*/ , 0 /*device::resize<int3>*/ , 0 /*device::resize<int4>*/ },
{device::resize<float> , 0 /*device::resize<float2>*/ , device::resize<float3> , device::resize<float4> }
};
CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
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())
{
dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
}
else
{
fx = static_cast<double>(dsize.width) / src.cols;
fy = static_cast<double>(dsize.height) / src.rows;
}
_dst.create(dsize, src.type());
GpuMat dst = _dst.getGpuMat();
if (dsize == src.size())
{
src.copyTo(dst, stream);
return;
}
const func_t func = funcs[src.depth()][src.channels() - 1];
if (!func)
CV_Error(Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
PtrStepSzb wholeSrc(wholeSize.height, wholeSize.width, src.datastart, src.step);
func(src, wholeSrc, ofs.y, ofs.x, dst, static_cast<float>(1.0 / fy), static_cast<float>(1.0 / fx), interpolation, StreamAccessor::getStream(stream));
}示例2: void
void cv::gpu::remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap, int interpolation, int borderMode, Scalar borderValue, Stream& stream)
{
using namespace cv::gpu::device::imgproc;
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, PtrStepSzf xmap, PtrStepSzf ymap, PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, int cc);
static const func_t funcs[6][4] =
{
{remap_gpu<uchar> , 0 /*remap_gpu<uchar2>*/ , remap_gpu<uchar3> , remap_gpu<uchar4> },
{0 /*remap_gpu<schar>*/, 0 /*remap_gpu<char2>*/ , 0 /*remap_gpu<char3>*/, 0 /*remap_gpu<char4>*/},
{remap_gpu<ushort> , 0 /*remap_gpu<ushort2>*/, remap_gpu<ushort3> , remap_gpu<ushort4> },
{remap_gpu<short> , 0 /*remap_gpu<short2>*/ , remap_gpu<short3> , remap_gpu<short4> },
{0 /*remap_gpu<int>*/ , 0 /*remap_gpu<int2>*/ , 0 /*remap_gpu<int3>*/ , 0 /*remap_gpu<int4>*/ },
{remap_gpu<float> , 0 /*remap_gpu<float2>*/ , remap_gpu<float3> , remap_gpu<float4> }
};
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(xmap.type() == CV_32F && ymap.type() == CV_32F && xmap.size() == ymap.size());
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);
const func_t func = funcs[src.depth()][src.channels() - 1];
CV_Assert(func != 0);
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderMode, gpuBorderType));
dst.create(xmap.size(), src.type());
Scalar_<float> borderValueFloat;
borderValueFloat = borderValue;
DeviceInfo info;
int cc = info.majorVersion() * 10 + info.minorVersion();
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, xmap, ymap,
dst, interpolation, gpuBorderType, borderValueFloat.val, StreamAccessor::getStream(stream), cc);
}示例3: void
void cv::cuda::remap(InputArray _src, OutputArray _dst, InputArray _xmap, InputArray _ymap, int interpolation, int borderMode, Scalar borderValue, Stream& stream)
{
using namespace cv::cuda::device::imgproc;
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, PtrStepSzf xmap, PtrStepSzf ymap, PtrStepSzb dst, int interpolation,
int borderMode, const float* borderValue, cudaStream_t stream, bool cc20);
static const func_t funcs[6][4] =
{
{remap_gpu<uchar> , 0 /*remap_gpu<uchar2>*/ , remap_gpu<uchar3> , remap_gpu<uchar4> },
{0 /*remap_gpu<schar>*/, 0 /*remap_gpu<char2>*/ , 0 /*remap_gpu<char3>*/, 0 /*remap_gpu<char4>*/},
{remap_gpu<ushort> , 0 /*remap_gpu<ushort2>*/, remap_gpu<ushort3> , remap_gpu<ushort4> },
{remap_gpu<short> , 0 /*remap_gpu<short2>*/ , remap_gpu<short3> , remap_gpu<short4> },
{0 /*remap_gpu<int>*/ , 0 /*remap_gpu<int2>*/ , 0 /*remap_gpu<int3>*/ , 0 /*remap_gpu<int4>*/ },
{remap_gpu<float> , 0 /*remap_gpu<float2>*/ , remap_gpu<float3> , remap_gpu<float4> }
};
GpuMat src = _src.getGpuMat();
GpuMat xmap = _xmap.getGpuMat();
GpuMat ymap = _ymap.getGpuMat();
CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
CV_Assert( xmap.type() == CV_32F && ymap.type() == CV_32F && xmap.size() == ymap.size() );
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 );
const func_t func = funcs[src.depth()][src.channels() - 1];
if (!func)
CV_Error(Error::StsUnsupportedFormat, "Unsupported input type");
_dst.create(xmap.size(), src.type());
GpuMat dst = _dst.getGpuMat();
Scalar_<float> borderValueFloat;
borderValueFloat = borderValue;
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y, xmap, ymap,
dst, interpolation, borderMode, borderValueFloat.val, StreamAccessor::getStream(stream), deviceSupports(FEATURE_SET_COMPUTE_20));
}示例4: void
void cv::cuda::warpPerspective(InputArray _src, OutputArray _dst, InputArray _M, Size dsize, int flags, int borderMode, Scalar borderValue, Stream& stream)
{
GpuMat src = _src.getGpuMat();
Mat M = _M.getMat();
CV_Assert( M.rows == 3 && M.cols == 3 );
const 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());
GpuMat dst = _dst.getGpuMat();
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::cuda::GpuMat& src, cv::cuda::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, stream);
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(stream));
}
else
//.........这里部分代码省略.........
示例5: void
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);
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;
useNpp = useNpp && useNppTab[src.depth()][src.channels() - 1][interpolation];
#ifdef linux
// NPP bug on float data
useNpp = useNpp && src.depth() != CV_32F;
#endif
if (useNpp)
{
typedef void (*func_t)(const cv::gpu::GpuMat& src, cv::Size wholeSize, cv::Point ofs, cv::gpu::GpuMat& dst, double coeffs[][3], cv::Size dsize, 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}
}
};
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, wholeSize, ofs, dst, coeffs, dsize, interpolation, StreamAccessor::getStream(s));
}
else
{
using namespace cv::gpu::device::imgproc;
typedef void (*func_t)(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);
//.........这里部分代码省略.........
示例6: NppStatus
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 || interpolation == INTER_AREA);
CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));
if (dsize == Size())
dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
else
{
fx = static_cast<double>(dsize.width) / src.cols;
fy = static_cast<double>(dsize.height) / src.rows;
}
if (dsize != dst.size())
dst.create(dsize, src.type());
if (dsize == src.size())
{
if (s)
s.enqueueCopy(src, dst);
else
src.copyTo(dst);
return;
}
cudaStream_t stream = StreamAccessor::getStream(s);
Size wholeSize;
Point ofs;
src.locateROI(wholeSize, ofs);
bool useNpp = (src.type() == CV_8UC1 || src.type() == CV_8UC4);
useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || (src.type() == CV_8UC4 && interpolation != INTER_AREA));
if (useNpp)
{
typedef NppStatus (*func_t)(const Npp8u * pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u * pDst, int nDstStep, NppiSize dstROISize,
double xFactor, double yFactor, int eInterpolation);
const func_t funcs[4] = { nppiResize_8u_C1R, 0, 0, nppiResize_8u_C4R };
static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS};
NppiSize srcsz;
srcsz.width = wholeSize.width;
srcsz.height = wholeSize.height;
NppiRect srcrect;
srcrect.x = ofs.x;
srcrect.y = ofs.y;
srcrect.width = src.cols;
srcrect.height = src.rows;
NppiSize dstsz;
dstsz.width = dst.cols;
dstsz.height = dst.rows;
NppStreamHandler h(stream);
nppSafeCall( funcs[src.channels() - 1](src.datastart, srcsz, static_cast<int>(src.step), srcrect,
dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, fx, fy, npp_inter[interpolation]) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
else
{
using namespace ::cv::gpu::device::imgproc;
typedef void (*func_t)(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float fx, float fy, DevMem2Db dst, int interpolation, cudaStream_t stream);
static const func_t funcs[6][4] =
{
{resize_gpu<uchar> , 0 /*resize_gpu<uchar2>*/ , resize_gpu<uchar3> , resize_gpu<uchar4> },
{0 /*resize_gpu<schar>*/, 0 /*resize_gpu<char2>*/ , 0 /*resize_gpu<char3>*/, 0 /*resize_gpu<char4>*/},
{resize_gpu<ushort> , 0 /*resize_gpu<ushort2>*/, resize_gpu<ushort3> , resize_gpu<ushort4> },
{resize_gpu<short> , 0 /*resize_gpu<short2>*/ , resize_gpu<short3> , resize_gpu<short4> },
{0 /*resize_gpu<int>*/ , 0 /*resize_gpu<int2>*/ , 0 /*resize_gpu<int3>*/ , 0 /*resize_gpu<int4>*/ },
{resize_gpu<float> , 0 /*resize_gpu<float2>*/ , resize_gpu<float3> , resize_gpu<float4> }
};
const func_t func = funcs[src.depth()][src.channels() - 1];
CV_Assert(func != 0);
func(src, DevMem2Db(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y,
static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, stream);
}
}