OpenCV  4.10.0
开源计算机视觉
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模块 | 命名空间 | 类 | 宏 | 类型定义 | 枚举 | 函数 | 变量
历史支持
CUDA加速计算机视觉

模块

 NPPST 核心库
 
 NPPST 图像处理
 
 NPPST 信号处理
 

详细描述

命名空间

命名空间  NcvCTprep
 

类

类  cv::cuda::BackgroundSubtractorFGD
 该类通过建立和维护背景模型来判别前景和背景像素。 更多...
 
类  cv::cuda::BackgroundSubtractorGMG
 背景/前景分割 算法。 更多...
 
类  cv::cuda::FastOpticalFlowBM
 
结构  cv::cuda::FGDParams
 
结构  HaarClassifierCascadeDescriptor
 
结构  HaarClassifierNode128
 
结构  HaarClassifierNodeDescriptor32
 
结构  HaarFeature64
 
结构  HaarFeatureDescriptor32
 
结构  HaarStage64
 
类  cv::cuda::ImagePyramid
 
类  INCVMemAllocator
 
结构  NCVBroxOpticalFlowDescriptor
 模型和求解器参数。 更多...
 
类  NCVMatrix< T >
 
类  NCVMatrixAlloc< T >
 
类  NCVMatrixReuse< T >
 
类  NCVMemNativeAllocator
 
结构  NCVMemPtr
 
结构  NCVMemSegment
 
类  NCVMemStackAllocator
 
结构  NcvPoint2D32s
 
结构  NcvPoint2D32u
 
结构  NcvRect32s
 
结构  NcvRect32u
 
结构  NcvRect8u
 
结构  NcvSize32s
 
结构  NcvSize32u
 
类  NCVVector< T >
 
类  NCVVectorAlloc< T >
 
类  NCVVectorReuse< T >
 

宏

#define CLAMP(x, a, b)   ( (x) > (b) ? (b) : ( (x) < (a) ? (a) : (x) ) )
 
#define CLAMP_0_255(x)   CLAMP(x,0,255)
 
#define CLAMP_BOTTOM(x, a)   (((x) < (a)) ? (a) : (x))
 
#define CLAMP_TOP(x, a)   (((x) > (a)) ? (a) : (x))
 
#define HAAR_STDDEV_BORDER   1
 
#define NCV_CT_ASSERT(X)
 
#define NCV_CT_PREP_PASTE(a, b)   NCV_CT_PREP_PASTE_AUX(a, b)
 连接宏。
 
#define NCV_CT_PREP_PASTE_AUX(a, b)   a##b
 连接间接宏。
 
#define NCV_RESET_SKIP_COND(x)    __ncv_skip_cond = x
 
#define NCV_SET_SKIP_COND(x)    bool __ncv_skip_cond = x
 
#define NCV_SKIP_COND_BEGIN    if (!__ncv_skip_cond) {
 
#define NCV_SKIP_COND_END    }
 
#define ncvAssertCUDALastErrorReturn(errCode)
 
#define ncvAssertCUDAReturn(cudacall, errCode)
 
#define ncvAssertPrintCheck(pred, msg)
 
#define ncvAssertPrintReturn(pred, msg, err)
 
#define ncvAssertReturn(pred, err)
 
#define ncvAssertReturnNcvStat(ncvOp)
 
#define ncvSafeMatAlloc(name, type, alloc, width, height, err)
 
#define OBJDET_MASK_ELEMENT_INVALID_32U   0xFFFFFFFF
 
#define RECT_SIMILARITY_PROPORTION   0.2f
 
#define SQR(x)   ((x)*(x))
 
#define SUB_BEGIN(type, name)   struct { __inline type name
 
#define SUB_CALL(name)   name.name
 
#define SUB_END(name)   } name;
 

类型定义

typedef short Ncv16s
 
typedef unsigned short Ncv16u
 
typedef float Ncv32f
 
typedef Ncv32f Ncv32f_a
 
typedef int Ncv32s
 
typedef unsigned int Ncv32u
 
typedef Ncv32u Ncv32u_a
 
typedef double Ncv64f
 
typedef long long Ncv64s
 
typedef uint64 Ncv64u
 
typedef signed char Ncv8s
 
typedef unsigned char Ncv8u
 
typedef bool NcvBool
 
typedef void NCVDebugOutputHandler(const cv::String &msg)
 
typedef Ncv32u NCVStatus
 
typedef struct _NcvTimer * NcvTimer
 

枚举

enum  {
  NCV_SUCCESS ,
  NCV_UNKNOWN_ERROR ,
  NCV_CUDA_ERROR ,
  NCV_NPP_ERROR ,
  NCV_FILE_ERROR ,
  NCV_NULL_PTR ,
  NCV_INCONSISTENT_INPUT ,
  NCV_TEXTURE_BIND_ERROR ,
  NCV_DIMENSIONS_INVALID ,
  NCV_INVALID_ROI ,
  NCV_INVALID_STEP ,
  NCV_INVALID_SCALE ,
  NCV_ALLOCATOR_NOT_INITIALIZED ,
  NCV_ALLOCATOR_BAD_ALLOC ,
  NCV_ALLOCATOR_BAD_DEALLOC ,
  NCV_ALLOCATOR_INSUFFICIENT_CAPACITY ,
  NCV_ALLOCATOR_DEALLOC_ORDER ,
  NCV_ALLOCATOR_BAD_REUSE ,
  NCV_MEM_COPY_ERROR ,
  NCV_MEM_RESIDENCE_ERROR ,
  NCV_MEM_INSUFFICIENT_CAPACITY ,
  NCV_HAAR_INVALID_PIXEL_STEP ,
  NCV_HAAR_TOO_MANY_FEATURES_IN_CLASSIFIER ,
  NCV_HAAR_TOO_MANY_FEATURES_IN_CASCADE ,
  NCV_HAAR_TOO_LARGE_FEATURES ,
  NCV_HAAR_XML_LOADING_EXCEPTION ,
  NCV_NOIMPL_HAAR_TILTED_FEATURES ,
  NCV_NOT_IMPLEMENTED ,
  NCV_WARNING_HAAR_DETECTIONS_VECTOR_OVERFLOW ,
  NPPST_SUCCESS = NCV_SUCCESS ,
  NPPST_ERROR ,
  NPPST_CUDA_KERNEL Execution Error ,
  NPPST_NULL_POINTER_ERROR ,
  NPPST_TEXTURE_BIND_ERROR ,
  NPPST_MEMCPY_ERROR ,
  NPPST_MEM_ALLOCATION_ERR ,
  NPPST_MEMFREE_ERR ,
  NPPST_INVALID_ROI ,
  NPPST_INVALID_STEP ,
  NPPST_INVALID_SCALE ,
  NPPST_MEM_INSUFFICIENT_BUFFER ,
  NPPST_MEM_RESIDENCE_ERROR ,
  NPPST_MEM_INTERNAL_ERROR ,
  NCV_LAST_STATUS
}
 
enum  {
  NCVPipeObjDet_Default = 0x000 ,
  NCVPipeObjDet_UseFairImageScaling = 0x001 ,
  NCVPipeObjDet_FindLargestObject = 0x002 ,
  NCVPipeObjDet_VisualizeInPlace = 0x004
}
 
enum  NCVMemoryType {
  NCVMemoryTypeNone ,
  NCVMemoryTypeHostPageable ,
  NCVMemoryTypeHostPinned ,
  NCVMemoryTypeDevice
}
 

函数

virtual INCVMemAllocator::~INCVMemAllocator ()=0
 
Ncv32u alignUp (Ncv32u what, Ncv32u alignment)
 
void cv::cuda::calcOpticalFlowBM (const GpuMat &prev, const GpuMat &curr, Size block_size, Size shift_size, Size max_range, bool use_previous, GpuMat &velx, GpuMat &vely, GpuMat &buf, Stream &stream=Stream::Null())
 使用块匹配算法计算两张图像的光学流动。
 
void cv::cuda::connectivityMask (const GpuMat &image, GpuMat &mask, const cv::Scalar &lo, const cv::Scalar &hi, Stream &stream=Stream::Null())
 计算泛化洪水填充组件标记的掩码。
 
Ptr< cuda::BackgroundSubtractorFGD >cv::cuda::createBackgroundSubtractorFGD (const FGDParams &params=FGDParams())
 创建FGD背景分割器。
 
Ptr< cuda::BackgroundSubtractorGMG >cv::cuda::createBackgroundSubtractorGMG (int initializationFrames=120, double decisionThreshold=0.8)
 创建GMG背景分割器。
 
Ptr< ImagePyramid >cv::cuda::createImagePyramid (InputArray img, int nLayers=-1, Stream &stream=Stream::Null())
 
void cv::cuda::createOpticalFlowNeedleMap (const GpuMat &u, const GpuMat &v, GpuMat &vertex, GpuMat &colors)
 
void cv::cuda::graphcut (GpuMat &terminals, GpuMat &leftTransp, GpuMat &rightTransp, GpuMat &top, GpuMat &bottom, GpuMat &labels, GpuMat &buf, Stream::Null())
 通过二维规则四连接图进行图切割标记。
 
void cv::cuda::graphcut (GpuMat &terminals, GpuMat &leftTransp, GpuMat &rightTransp, GpuMat &top, GpuMat &topLeft, GpuMat &topRight, GpuMat &bottom, GpuMat &bottomLeft, GpuMat &bottomRight, GpuMat &labels, GpuMat &buf, Stream &stream=Stream::Null())
 通过二维正则八连通图的图割进行标记。
 
void cv::cuda::interpolateFrames (const GpuMat &frame0, const GpuMat &frame1, const GpuMat &fu, const GpuMat &fv, const GpuMat &bu, const GpuMat &bv, float pos, GpuMat &newFrame, GpuMat &buf, Stream &stream=Stream::Null())
 使用提供的光流（位移场）插值帧（图像）。
 
void cv::cuda::labelComponents (const GpuMat &mask, GpuMat &components, int flags=0, Stream &stream=Stream::Null())
 执行连通分量标记。
 
NCVStatus memSegCopyHelper (void *dst, NCVMemoryType dstType, const void *src, NCVMemoryType srcType, size_t sz, cudaStream_t cuStream)
 
NCVStatus memSegCopyHelper2D (void *dst, Ncv32u dstPitch, NCVMemoryType dstType, const void *src, Ncv32u srcPitch, NCVMemoryType srcType, Ncv32u widthbytes, Ncv32u height, cudaStream_t cuStream)
 
 NCV_CT_ASSERT (sizeof(HaarClassifierNode128)==16)
 
 NCV_CT_ASSERT (sizeof(HaarClassifierNodeDescriptor32)==4)
 
 NCV_CT_ASSERT (sizeof(HaarFeature64)==8)
 
 NCV_CT_ASSERT (sizeof(HaarFeatureDescriptor32)==4)
 
 NCV_CT_ASSERT (sizeof(HaarStage64)==8)
 
NCVStatus ncvApplyHaarClassifierCascade_device (NCVMatrix<Ncv32u> &d_integralImage, NCVMatrix<Ncv32f> &d_weights, NCVMatrixAlloc<Ncv32u> &d_pixelMask, Ncv32u &numDetections, HaarClassifierCascadeDescriptor &haar, NCVVector<HaarStage64> &h_HaarStages, NCVVector<HaarStage64> &d_HaarStages, NCVVector<HaarClassifierNode128> &d_HaarNodes, NCVVector<HaarFeature64> &d_HaarFeatures, NcvBool bMaskElements, NcvSize32u anchorsRoi, Ncv32u pixelStep, Ncv32f scaleArea, INCVMemAllocator &gpuAllocator, INCVMemAllocator &cpuAllocator, cudaDeviceProp &devProp, cudaStream_t cuStream)
 
NCVStatus ncvApplyHaarClassifierCascade_host (NCVMatrix<Ncv32u> &h_integralImage, NCVMatrix<Ncv32f> &h_weights, NCVMatrixAlloc<Ncv32u> &h_pixelMask, Ncv32u &numDetections, HaarClassifierCascadeDescriptor &haar, NCVVector<HaarStage64> &h_HaarStages, NCVVector<HaarClassifierNode128> &h_HaarNodes, NCVVector<HaarFeature64> &h_HaarFeatures, NcvBool bMaskElements, NcvSize32u anchorsRoi, Ncv32u pixelStep, Ncv32f scaleArea)
 
NCVStatus NCVBroxOpticalFlow (const NCVBroxOpticalFlowDescriptor desc, INCVMemAllocator &gpu_mem_allocator, const NCVMatrix<Ncv32f> &frame0, const NCVMatrix<Ncv32f> &frame1, NCVMatrix<Ncv32f> &u, NCVMatrix<Ncv32f> &v, cudaStream_t stream)
 计算光流。
 
void ncvDebugOutput (const cv::String &msg)
 
NCVStatus ncvDetectObjectsMultiScale_device (NCVMatrix< Ncv8u > &d_srcImg, NcvSize32u srcRoi, NCVVector< NcvRect32u > &d_dstRects, Ncv32u &dstNumRects, HaarClassifierCascadeDescriptor &haar, NCVVector< HaarStage64 > &h_HaarStages, NCVVector< HaarStage64 > &d_HaarStages, NCVVector< HaarClassifierNode128 > &d_HaarNodes, NCVVector< HaarFeature64 > &d_HaarFeatures, NcvSize32u minObjSize, Ncv32u minNeighbors, Ncv32f scaleStep, Ncv32u pixelStep, Ncv32u flags, INCVMemAllocator &gpuAllocator, INCVMemAllocator &cpuAllocator, cudaDeviceProp &devProp, cudaStream_t cuStream)
 
NCVStatus ncvDrawRects_32u_device (Ncv32u *d_dst, Ncv32u dstStride, Ncv32u dstWidth, Ncv32u dstHeight, NcvRect32u *d_rects, Ncv32u numRects, Ncv32u color, cudaStream_t cuStream)
 
NCVStatus ncvDrawRects_32u_host (Ncv32u *h_dst, Ncv32u dstStride, Ncv32u dstWidth, Ncv32u dstHeight, NcvRect32u *h_rects, Ncv32u numRects, Ncv32u color)
 
NCVStatus ncvDrawRects_8u_device (Ncv8u *d_dst, Ncv32u dstStride, Ncv32u dstWidth, Ncv8u dstHeight, NcvRect32u *d_rects, Ncv32u numRects, Ncv8u color, cudaStream_t cuStream)
 
NCVStatus ncvDrawRects_8u_host (Ncv8u *h_dst, Ncv32u dstStride, Ncv32u dstWidth, Ncv32u dstHeight, NcvRect32u *h_rects, Ncv32u numRects, Ncv8u color)
 
double ncvEndQueryTimerMs (NcvTimer t)
 
double ncvEndQueryTimerUs (NcvTimer t)
 
NCVStatus ncvGroupRectangles_host (NCVVector< NcvRect32u > &hypotheses, Ncv32u &numHypotheses, Ncv32u minNeighbors, Ncv32f intersectEps, NCVVector< Ncv32u > *hypothesesWeights)
 
NCVStatus ncvGrowDetectionsVector_device (NCVVector< Ncv32u > &pixelMask, Ncv32u numPixelMaskDetections, NCVVector< NcvRect32u > &hypotheses, Ncv32u &totalDetections, Ncv32u totalMaxDetections, Ncv32u rectWidth, Ncv32u rectHeight, Ncv32f curScale, cudaStream_t cuStream)
 
NCVStatus ncvGrowDetectionsVector_host (NCVVector< Ncv32u > &pixelMask, Ncv32u numPixelMaskDetections, NCVVector< NcvRect32u > &hypotheses, Ncv32u &totalDetections, Ncv32u totalMaxDetections, Ncv32u rectWidth, Ncv32u rectHeight, Ncv32f curScale)
 
NCVStatus ncvHaarGetClassifierSize (const cv::String &filename, Ncv32u &numStages, Ncv32u &numNodes, Ncv32u &numFeatures)
 
NCVStatus ncvHaarLoadFromFile_host (const cv::String &filename, HaarClassifierCascadeDescriptor &haar, NCVVector< HaarStage64 > &h_HaarStages, NCVVector< HaarClassifierNode128 > &h_HaarNodes, NCVVector< HaarFeature64 > &h_HaarFeatures)
 
NCVStatus ncvHaarStoreNVBIN_host (const cv::String &filename, HaarClassifierCascadeDescriptor haar, NCVVector< HaarStage64 > &h_HaarStages, NCVVector< HaarClassifierNode128 > &h_HaarNodes, NCVVector< HaarFeature64 > &h_HaarFeatures)
 
void ncvSetDebugOutputHandler (NCVDebugOutputHandler *func)
 
NcvTimer ncvStartTimer (void)
 
void cv::cuda::projectPoints (const GpuMat &src, const Mat &rvec, const Mat &tvec, const Mat &camera_mat, const Mat &dist_coef, GpuMat &dst, Stream &stream=Stream::Null())
 
void cv::cuda::solvePnPRansac (const Mat &object, const Mat &image, const Mat &camera_mat, const Mat &dist_coef, Mat &rvec, Mat &tvec, bool use_extrinsic_guess=false, int num_iters=100, float max_dist=8.0, int min_inlier_count=100, std::vector< int > *inliers=NULL)
 从3D-2D点对应关系中找到物体的姿态。
 
void cv::cuda::transformPoints (const GpuMat &src, const Mat &rvec, const Mat &tvec, GpuMat &dst, Stream &stream=Stream::Null())
 

变量

const Ncv32u K_LOG2_WARP_SIZE = 5
 
const Ncv32u K_WARP_SIZE = 32
 

宏定义文档

◆ CLAMP

#define CLAMP (   x,
  a,
  b 
)    ( (x) > (b) ? (b) : ( (x) < (a) ? (a) : (x) ) )

#include <opencv2/cudalegacy/NCV.hpp>

◆ CLAMP_0_255

#define CLAMP_0_255 (   x)    CLAMP(x,0,255)

#include <opencv2/cudalegacy/NCV.hpp>

◆ CLAMP_BOTTOM

#define CLAMP_BOTTOM (   x,
  a 
)    (((x) < (a)) ? (a) : (x))

#include <opencv2/cudalegacy/NCV.hpp>

◆ CLAMP_TOP

#define CLAMP_TOP (   x,
  a 
)    (((x) > (a)) ? (a) : (x))

#include <opencv2/cudalegacy/NCV.hpp>

◆ HAAR_STDDEV_BORDER

#define HAAR_STDDEV_BORDER   1

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCV_CT_ASSERT

#define NCV_CT_ASSERT (   X)

#include <opencv2/cudalegacy/NCV.hpp>

值
typedef NcvCTprep::assertTest<sizeof(NcvCTprep::CT_ASSERT_FAILURE< (bool)(X) >)> \
NCV_CT_PREP_PASTE(__ct_assert_typedef_, __LINE__)
NCV_CT_PREP_PASTE
#define NCV_CT_PREP_PASTE(a, b)
连接宏。
定义 NCV.hpp:83
NcvCTprep::CT_ASSERT_FAILURE
定义 NCV.hpp:72
NcvCTprep::assertTest
定义 NCV.hpp:78

在文件范围内执行编译时条件断言

◆ NCV_CT_PREP_PASTE

#define NCV_CT_PREP_PASTE (   a,
  b 
)    NCV_CT_PREP_PASTE_AUX(a, b)

#include <opencv2/cudalegacy/NCV.hpp>

连接宏。

◆ NCV_CT_PREP_PASTE_AUX

#define NCV_CT_PREP_PASTE_AUX (   a,
  b 
)    a##b

#include <opencv2/cudalegacy/NCV.hpp>

连接间接宏。

◆ NCV_RESET_SKIP_COND

#define NCV_RESET_SKIP_COND (   x)     __ncv_skip_cond = x

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCV_SET_SKIP_COND

#define NCV_SET_SKIP_COND (   x)     bool __ncv_skip_cond = x

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCV_SKIP_COND_BEGIN

定义 NCV_SKIP_COND_BEGIN    如果 (!__ncv_skip_cond) {

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCV_SKIP_COND_END

定义 NCV_SKIP_COND_END    }

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvAssertCUDALastErrorReturn

定义 ncvAssertCUDALastErrorReturn (   errCode)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
cudaError_t res = cudaGetLastError(); \
cv::String msg = cv::format("cudaError_t=%d", (int)res); \
ncvAssertPrintReturn(cudaSuccess==res, msg.c_str(), errCode); \
}
cv::String
std::string String
定义 cvstd.hpp:151
cv::format
String format(const char *fmt,...)
返回一个使用 printf 类似表达式格式化的文本字符串。

◆ ncvAssertCUDAReturn

定义 ncvAssertCUDAReturn (   cudacall,
  errCode 
)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
cudaError_t res = cudacall; \
cv::String msg = cv::format("cudaError_t=%d", (int)res); \
ncvAssertPrintReturn(cudaSuccess==res, msg.c_str(), errCode); \
}

◆ ncvAssertPrintCheck

定义 ncvAssertPrintCheck (   pred,
  msg 
)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
if (!(pred)) \
{ \
cv::String str = cv::format("NCV Assertion Failed: %s, file=%s, line=%d", msg, __FILE__, __LINE__); \
ncvDebugOutput(str); \
} \
}

◆ ncvAssertPrintReturn

定义 ncvAssertPrintReturn (   pred,
  msg,
  err 
)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
ncvAssertPrintCheck(pred, msg); \
if (!(pred)) return err; \
}

◆ ncvAssertReturn

定义 ncvAssertReturn (   pred,
  err 
)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
cv::String msg = cv::format("retcode=%d", (int)err); \
ncvAssertPrintReturn(pred, msg.c_str(), err); \
}

◆ ncvAssertReturnNcvStat

定义 ncvAssertReturnNcvStat (   ncvOp)

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
NCVStatus _ncvStat = ncvOp; \
cv::String msg = cv::format("NcvStat=%d", (int)_ncvStat); \
ncvAssertPrintReturn(NCV_SUCCESS==_ncvStat, msg.c_str(), _ncvStat); \
}
NCVStatus
Ncv32u NCVStatus
定义 NCV.hpp:376
NCV_SUCCESS
@ NCV_SUCCESS
定义 NCV.hpp:316

◆ ncvSafeMatAlloc

定义 ncvSafeMatAlloc (   name,
  type,
  alloc,
  width,
  height,
  err 
)

#include <opencv2/cudalegacy/NCV.hpp>

值
NCVMatrixAlloc<type> name(alloc, width, height); \
ncvAssertReturn(name.isMemAllocated(), err);
NCVMatrixAlloc
定义 NCV.hpp:845

◆ OBJDET_MASK_ELEMENT_INVALID_32U

定义 OBJDET_MASK_ELEMENT_INVALID_32U    0xFFFFFFFF

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ RECT_SIMILARITY_PROPORTION

定义 RECT_SIMILARITY_PROPORTION    0.2f

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ SQR

定义 SQR (   x)    ((x)*(x))

#include <opencv2/cudalegacy/NCV.hpp>

◆ SUB_BEGIN

定义 SUB_BEGIN (   type,
  name 
)    struct { __inline type name

#include <opencv2/cudalegacy/NCV.hpp>

◆ SUB_CALL

定义 SUB_CALL (   name)    name.name

#include <opencv2/cudalegacy/NCV.hpp>

◆ SUB_END

定义 SUB_END (   name)    } name;

#include <opencv2/cudalegacy/NCV.hpp>

typedef 说明

◆ Ncv16s

typedef short Ncv16s

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv16u

typedef unsigned short Ncv16u

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv32f

typedef float Ncv32f

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv32f_a

typedef Ncv32f Ncv32f_a

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ Ncv32s

typedef int Ncv32s

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv32u

typedef unsigned int Ncv32u

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv32u_a

typedef Ncv32u Ncv32u_a

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ Ncv64f

typedef double Ncv64f

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv64s

typedef long long Ncv64s

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv64u

typedef uint64 Ncv64u

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv8s

typedef signed char Ncv8s

#include <opencv2/cudalegacy/NCV.hpp>

◆ Ncv8u

typedef unsigned char Ncv8u

#include <opencv2/cudalegacy/NCV.hpp>

◆ NcvBool

typedef bool NcvBool

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCVDebugOutputHandler

typedef void NCVDebugOutputHandler(const cv::String &msg)

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCVStatus

typedef Ncv32u NCVStatus

#include <opencv2/cudalegacy/NCV.hpp>

◆ NcvTimer

typedef struct _NcvTimer* NcvTimer

#include <opencv2/cudalegacy/NCV.hpp>

枚举类型文档

◆ 匿名枚举

匿名枚举

#include <opencv2/cudalegacy/NCV.hpp>

状态通知、错误和警告的返回代码

枚举器
NCV_SUCCESS 
NCV_UNKNOWN_ERROR 
NCV_CUDA_ERROR 
NCV_NPP_ERROR 
NCV_FILE_ERROR 
NCV_NULL_PTR 
NCV_INCONSISTENT_INPUT 
NCV_TEXTURE_BIND_ERROR 
NCV_DIMENSIONS_INVALID 
NCV_INVALID_ROI 
NCV_INVALID_STEP 
NCV_INVALID_SCALE 
NCV_ALLOCATOR_NOT_INITIALIZED 
NCV_ALLOCATOR_BAD_ALLOC 
NCV_ALLOCATOR_BAD_DEALLOC 
NCV_ALLOCATOR_INSUFFICIENT_CAPACITY 
NCV_ALLOCATOR_DEALLOC_ORDER 
NCV_ALLOCATOR_BAD_REUSE 
NCV_MEM_COPY_ERROR 
NCV_MEM_RESIDENCE_ERROR 
NCV_MEM_INSUFFICIENT_CAPACITY 
NCV_HAAR_INVALID_PIXEL_STEP 
NCV_HAAR_TOO_MANY_FEATURES_IN_CLASSIFIER 
NCV_HAAR_TOO_MANY_FEATURES_IN_CASCADE 
NCV_HAAR_TOO_LARGE_FEATURES 
NCV_HAAR_XML_LOADING_EXCEPTION 
NCV_NOIMPL_HAAR_TILTED_FEATURES 
NCV_NOT_IMPLEMENTED 
NCV_WARNING_HAAR_DETECTIONS_VECTOR_OVERFLOW 
NPPST_SUCCESS 

操作成功（与 NPP_NO_ERROR 相同）

NPPST_ERROR 

未知错误。

NPPST_CUDA_KERNEL_EXECUTION_ERROR 

CUDA核执行错误。

NPPST_NULL_POINTER_ERROR 

空指针参数错误。

NPPST_TEXTURE_BIND_ERROR 

CUDA纹理绑定错误或返回非零偏移量。

NPPST_MEMCPY_ERROR 

CUDA内存复制错误。

NPPST_MEM_ALLOC_ERR 

CUDA内存分配错误。

NPPST_MEMFREE_ERR 

CUDA内存释放错误。

NPPST_INVALID_ROI 

无效的兴趣区域参数。

NPPST_INVALID_STEP 

无效的图像行步长参数（检查符号、对齐、与图像宽度的关系）

NPPST_INVALID_SCALE 

无效的缩放参数传入。

NPPST_MEM_INSUFFICIENT_BUFFER 

用户分配的缓冲区不足。

NPPST_MEM_RESIDENCE_ERROR 

检测到内存驻留错误（检查是否指针应该是设备或固定）

NPPST_MEM_INTERNAL_ERROR 

内存管理内部错误。

NCV_LAST_STATUS 

用作在其它文件中继续错误编号的标记。

◆ 匿名枚举

匿名枚举

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

枚举器
NCVPipeObjDet_Default 
NCVPipeObjDet_UseFairImageScaling 
NCVPipeObjDet_FindLargestObject 
NCVPipeObjDet_VisualizeInPlace 

◆ NCVMemoryType

枚举 NCVMemoryType

#include <opencv2/cudalegacy/NCV.hpp>

NCVMemoryType

枚举器
NCVMemoryTypeNone 
NCVMemoryTypeHostPageable 
NCVMemoryTypeHostPinned 
NCVMemoryTypeDevice 

函数文档

◆ ~INCVMemAllocator()

INCVMemAllocator::~INCVMemAllocator ( )
inlinepure virtual

#include <opencv2/cudalegacy/NCV.hpp>

◆ alignUp()

Ncv32u alignUp ( Ncv32u  what,
Ncv32u  alignment 
)

#include <opencv2/cudalegacy/NCV.hpp>

计算对齐后的顶部界限值

◆ calcOpticalFlowBM()

void cv::cuda::calcOpticalFlowBM ( const GpuMat &  prev,
const GpuMat &  curr,
Size  block_size,
Size  shift_size,
Size  max_range,
bool  use_previous,
GpuMat &  velx,
GpuMat &  vely,
GpuMat &  buf,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

使用块匹配算法计算两张图像的光学流动。

◆ connectivityMask()

void cv::cuda::connectivityMask ( const GpuMat &  image,
GpuMat &  mask,
const Scalar &  lo,
const Scalar &  hi,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

计算泛化洪水填充组件标记的掩码。

◆ createBackgroundSubtractorFGD()

Ptr<婷之仕事の指導者に基づく理論 shepherd< cuda::BackgroundSubtractorFGD > cv::cuda::createBackgroundSubtractorFGD ( const FGDParams &  params = FGDParams())

#include <opencv2/cudalegacy.hpp

创建FGD背景分割器。

参数
paramsAlgorithm's parameters. See [161] for explanation.

◆ createBackgroundSubtractorGMG()

Ptr< cuda::BackgroundSubtractorGMG > cv::cuda::createBackgroundSubtractorGMG ( int  initializationFrames = 120,
double  decisionThreshold = 0.8 
)

#include <opencv2/cudalegacy.hpp

创建GMG背景分割器。

参数
initializationFrames用于初始化直方图的视频帧数。
decisionThreshold像素被判断为前景的阈值。

◆ createImagePyramid()

Ptr< ImagePyramid > cv::cuda::createImagePyramid ( InputArray  img,
int  nLayers = -1,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

◆ createOpticalFlowNeedleMap()

void cv::cuda::createOpticalFlowNeedleMap ( const GpuMat &  u,
const GpuMat &  v,
GpuMat &  vertex,
GpuMat &  colors 
)

#include <opencv2/cudalegacy.hpp

◆ graphcut() [1/2]

void cv::cuda::graphcut ( GpuMat &  terminals,
GpuMat &  leftTransp,
GpuMat &  rightTransp,
GpuMat &  top,
GpuMat &  bottom,
GpuMat &  labels,
GpuMat &  buf,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

通过二维规则四连接图进行图切割标记。

◆ graphcut() [2/2]

void cv::cuda::graphcut ( GpuMat &  terminals,
GpuMat &  leftTransp,
GpuMat &  rightTransp,
GpuMat &  top,
GpuMat &  topLeft,
GpuMat &  topRight,
GpuMat &  bottom,
GpuMat &  bottomLeft,
GpuMat &  bottomRight,
GpuMat &  labels,
GpuMat &  buf,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

通过二维正则八连通图的图割进行标记。

◆ interpolateFrames()

void cv::cuda::interpolateFrames ( const GpuMat &  frame0,
const GpuMat &  frame1,
const GpuMat &  fu,
const GpuMat &  fv,
const GpuMat &  bu,
const GpuMat &  bv,
float  pos,
GpuMat &  newFrame,
GpuMat &  buf,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

使用提供的光流（位移场）插值帧（图像）。

参数
frame0第一帧（32位浮点图像，单通道）。
frame1第二帧。必须与frame0具有相同的类型和大小。
fu正向水平位移。
fv正向垂直位移。
bu反向水平位移。
bv反向垂直位移。
pos新帧位置。
newFrame输出图像。
buf临时缓冲区，将具有宽度 x 6*高度大小，CV_32FC1类型，包含6 GpuMat：第一帧遮挡掩码、第二帧遮挡掩码、插值正向水平流、插值正向垂直流、插值反向水平流、插值反向垂直流。
streamStream for the asynchronous version。

◆ labelComponents()

void cv::cuda::labelComponents ( const GpuMat &  mask,
GpuMat &  components,
int  flags = 0,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

执行连通分量标记。

◆ memSegCopyHelper()

NCVStatus memSegCopyHelper ( void *  dst,
NCVMemoryType  dstType,
const void *  src,
NCVMemoryType  srcType,
size_t  sz,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCV.hpp>

复制的调度器

◆ memSegCopyHelper2D()

NCVStatus memSegCopyHelper2D ( void *  dst,
Ncv32u  dstPitch,
NCVMemoryType  dstType,
const void *  src,
Ncv32u  srcPitch,
NCVMemoryType  srcType,
Ncv32u  widthbytes,
Ncv32u  height,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCV_CT_ASSERT() [1/5]

NCV_CT_ASSERT ( sizeof(HaarClassifierNode128)  = =16)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCV_CT_ASSERT() [2/5]

NCV_CT_ASSERT ( sizeof(HaarClassifierNodeDescriptor32)  = =4)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCV_CT_ASSERT() [3/5]

NCV_CT_ASSERT ( sizeof(HaarFeature64)  = =8)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCV_CT_ASSERT() [4/5]

NCV_CT_ASSERT ( sizeof(HaarFeatureDescriptor32)  = =4)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCV_CT_ASSERT() [5/5]

NCV_CT_ASSERT ( sizeof(HaarStage64)  = =8)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvApplyHaarClassifierCascade_device()

NCVStatus ncvApplyHaarClassifierCascade_device ( NCVMatrix< Ncv32u > &  d_integralImage,
NCVMatrix< Ncv32f > &  d_weights,
NCVMatrixAlloc< Ncv32u > &  d_pixelMask,
Ncv32u &  numDetections,
HaarClassifierCascadeDescriptor &  haar,
NCVVector< HaarStage64 > &  h_HaarStages,
NCVVector< HaarStage64 > &  d_HaarStages,
NCVVector< HaarClassifierNode128 > &  d_HaarNodes,
NCVVector< HaarFeature64 > &  d_HaarFeatures,
NcvBool  bMaskElements,
NcvSize32u  anchorsRoi,
Ncv32u  pixelStep,
Ncv32f  scaleArea,
INCVMemAllocator &  gpuAllocator,
INCVMemAllocator &  cpuAllocator,
cudaDeviceProp &  devProp,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvApplyHaarClassifierCascade_host()

NCVStatus ncvApplyHaarClassifierCascade_host ( NCVMatrix< Ncv32u > &  h_integralImage,
NCVMatrix< Ncv32f > &  h_weights,
NCVMatrixAlloc< Ncv32u > &  h_pixelMask,
Ncv32u &  numDetections,
HaarClassifierCascadeDescriptor &  haar,
NCVVector< HaarStage64 > &  h_HaarStages,
NCVVector< HaarClassifierNode128 > &  h_HaarNodes,
NCVVector< HaarFeature64 > &  h_HaarFeatures,
NcvBool  bMaskElements,
NcvSize32u  anchorsRoi,
Ncv32u  pixelStep,
Ncv32f  scaleArea 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCVBroxOpticalFlow()

NCVStatus NCVBroxOpticalFlow ( const NCVBroxOpticalFlowDescriptor  desc,
INCVMemAllocator &  gpu_mem_allocator,
const NCVMatrix< Ncv32f > &  frame0,
const NCVMatrix< Ncv32f > &  frame1,
NCVMatrix< Ncv32f > &  u,
NCVMatrix< Ncv32f > &  v,
cudaStream_t  stream 
)

#include <opencv2/cudalegacy/NCVBroxOpticalFlow.hpp>

计算光流。

Based on method by Brox et al [2004]

参数
[in]descmodel and solver parameters
[in]gpu_mem_allocatorGPU memory allocator
[in]frame0source frame
[in]frame1frame to track
[out]uflow horizontal component (along x axis)
[out]vflow vertical component (along y axis)
stream
Returns
computation status

◆ ncvDebugOutput()

void ncvDebugOutput ( const cv::String &  msg)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDetectObjectsMultiScale_device()

NCVStatus ncvDetectObjectsMultiScale_device ( NCVMatrix< Ncv8u > &  d_srcImg,
NcvSize32u  srcRoi,
NCVVector< NcvRect32u > &  d_dstRects,
Ncv32u &  dstNumRects,
HaarClassifierCascadeDescriptor &  haar,
NCVVector< HaarStage64 > &  h_HaarStages,
NCVVector< HaarStage64 > &  d_HaarStages,
NCVVector< HaarClassifierNode128 > &  d_HaarNodes,
NCVVector< HaarFeature64 > &  d_HaarFeatures,
NcvSize32u  minObjSize,
Ncv32u  minNeighbors,
Ncv32f  scaleStep,
Ncv32u  pixelStep,
Ncv32u  flags,
INCVMemAllocator &  gpuAllocator,
INCVMemAllocator &  cpuAllocator,
cudaDeviceProp &  devProp,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvDrawRects_32u_device()

NCVStatus ncvDrawRects_32u_device ( Ncv32u *  d_dst,
Ncv32u  dstStride,
Ncv32u  dstWidth,
Ncv32u  dstHeight,
NcvRect32u *  矩形数组,
Ncv32u  矩形数量,
Ncv32u  颜色,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_32u_host()

NCVStatus ncvDrawRects_32u_host ( Ncv32u *  目标句柄,
Ncv32u  dstStride,
Ncv32u  dstWidth,
Ncv32u  dstHeight,
NcvRect32u *  矩形句柄,
Ncv32u  矩形数量,
Ncv32u  颜色 
)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_device()

NCVStatus ncvDrawRects_8u_device ( Ncv8u *  d_dst,
Ncv32u  dstStride,
Ncv32u  dstWidth,
Ncv32u  dstHeight,
NcvRect32u *  矩形数组,
Ncv32u  矩形数量,
Ncv8u  颜色,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_host()

NCVStatus ncvDrawRects_8u_host ( Ncv8u *  目标句柄,
Ncv32u  dstStride,
Ncv32u  dstWidth,
Ncv32u  dstHeight,
NcvRect32u *  矩形句柄,
Ncv32u  矩形数量,
Ncv8u  颜色 
)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvEndQueryTimerMs()

double ncvEndQueryTimerMs ( NcvTimer  t)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvEndQueryTimerUs()

double ncvEndQueryTimerUs ( NcvTimer  t)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvGroupRectangles_host()

NCVStatus ncvGroupRectangles_host ( NCVVector< NcvRect32u > &  假设集,
Ncv32u &  假设数量,
Ncv32u  minNeighbors,
Ncv32f  交点容差,
NCVVector< Ncv32u > *  假设权重 
)

#include <opencv2/cudalegacy/NCV.hpp>

矩形操作

◆ ncvGrowDetectionsVector_device()

NCVStatus ncvGrowDetectionsVector_device ( NCVVector< Ncv32u > &  像素掩码,
Ncv32u  像素掩码检测数量,
NCVVector< NcvRect32u > &  假设集,
Ncv32u &  总检测数,
Ncv32u  最大检测数,
Ncv32u  矩形宽度,
Ncv32u  矩形高度,
Ncv32f  当前缩放,
cudaStream_t  cuStream 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvGrowDetectionsVector_host()

NCVStatus ncvGrowDetectionsVector_host ( NCVVector< Ncv32u > &  像素掩码,
Ncv32u  像素掩码检测数量,
NCVVector< NcvRect32u > &  假设集,
Ncv32u &  总检测数,
Ncv32u  最大检测数,
Ncv32u  矩形宽度,
Ncv32u  矩形高度,
Ncv32f  当前缩放 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarGetClassifierSize()

NCVStatus ncvHaarGetClassifierSize ( const cv::String &  文件名,
Ncv32u &  阶段数量,
Ncv32u &  节点数量,
Ncv32u &  特征数量 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarLoadFromFile_host()

NCVStatus ncvHaarLoadFromFile_host ( const cv::String &  文件名,
HaarClassifierCascadeDescriptor &  haar,
NCVVector< HaarStage64 > &  h_HaarStages,
NCVVector< HaarClassifierNode128 > &  h_HaarNodes,
NCVVector< HaarFeature64 > &  Haar特征句柄 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarStoreNVBIN_host()

NCVStatus ncvHaarStoreNVBIN_host ( const cv::String &  文件名,
Haar分类器级联描述符  haar,
NCVVector< HaarStage64 > &  h_HaarStages,
NCVVector< HaarClassifierNode128 > &  h_HaarNodes,
NCVVector< HaarFeature64 > &  Haar特征句柄 
)

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvSetDebugOutputHandler()

void ncvSetDebugOutputHandler ( NCV调试输出处理器 *  函数)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvStartTimer()

Ncv计时器 ncvStartTimer ( void  )

#include <opencv2/cudalegacy/NCV.hpp>

◆ projectPoints()

void cv::cuda::projectPoints ( const GpuMat &  src,
const Mat &  rvec,
const Mat &  tvec,
const Mat &  camera_mat,
const Mat &  dist_coef,
GpuMat &  dst,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

◆ solvePnPRansac()

void cv::cuda::solvePnPRansac ( const Mat &  object,
const Mat &  image,
const Mat &  camera_mat,
const Mat &  dist_coef,
Mat &  rvec,
Mat &  tvec,
bool  use_extrinsic_guess = false,
int  num_iters = 100,
float  max_dist = 8.0,
int  min_inlier_count = 100,
std::vector< int > *  inliers = NULL 
)

#include <opencv2/cudalegacy.hpp

从3D-2D点对应关系中找到物体的姿态。

参数
object物体单行矩阵。
image图像点单行矩阵。
camera_mat相机内参3x3矩阵。
dist_coef畸变系数。详细信息请参阅undistortPoints。
rvec输出3D旋转向量。
tvec输出3D平移向量。
使用外部猜测用于指示功能必须使用 rvec 和 tvec 作为初始变换猜测的标志。目前不支持。
num_itersRANSAC 迭代的最大数量。
max_dist欧几里得距离阈值，用于检测点是否为内点。
min_inlier_count用于指示功能达到或超过一定数量的内点后必须停止的标志。目前不支持。
inliers输出内点索引的向量。

◆ transformPoints()

void cv::cuda::transformPoints ( const GpuMat &  src,
const Mat &  rvec,
const Mat &  tvec,
GpuMat &  dst,
Stream &  stream = Стрим::Null 
)

#include <opencv2/cudalegacy.hpp

变量文档

◆ K_LOG2_WARP_SIZE

const Ncv32u K_LOG2_WARP_SIZE = 5

#include <opencv2/cudalegacy/NCV.hpp>

◆ K_WARP_SIZE

const Ncv32u K_WARP_SIZE = 32

#include <opencv2/cudalegacy/NCV.hpp>

由 OpenCV 于 2024 年 6 月 2 日星期日 21:52:15 自动生成。 propelled by   doxygen 1.9.8