OpenCV 4.11.0
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CUDA 加速的计算机视觉

主题

 NPPST 核心
 
 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
 该类通过构建和维护背景模型来区分前景和背景像素。更多…
 
类 cv::cuda::BackgroundSubtractorGMG
 背景/前景分割算法。更多…
 
类 cv::cuda::FastOpticalFlowBM
 
结构体 cv::cuda::FGDParams
 
结构体 HaarClassifierCascadeDescriptor
 
结构体 HaarClassifierNode128
 
结构体 HaarClassifierNodeDescriptor32
 
结构体 HaarFeature64
 
结构体 HaarFeatureDescriptor32
 
结构体 HaarStage64
 
类 cv::cuda::ImagePyramid
 
类 INCVMemAllocator
 
结构体 NCVBroxOpticalFlowDescriptor
 模型和求解器参数。更多…
 
类 NCVMatrix< T >
 
类 NCVMatrixAlloc< T >
 
类 NCVMatrixReuse< T >
 
类 NCVMemNativeAllocator
 
结构体 NCVMemPtr
 
结构体 NCVMemSegment
 
类 NCVMemStackAllocator
 
结构体 NcvPoint2D32s
 
结构体 NcvPoint2D32u
 
结构体 NcvRect32s
 
结构体 NcvRect32u
 
结构体 NcvRect8u
 
结构体 NcvSize32s
 
结构体 NcvSize32u
 
类 NCVVector< T >
 
类 NCVVectorAlloc< T >
 
类 NCVVectorReuse< T >
 

宏

#define CLAMP(x, a, b)
 
#define CLAMP_0_255(x)
 
#define CLAMP_BOTTOM(x, a)
 
#define CLAMP_TOP(x, a)
 
#define HAAR_STDDEV_BORDER   1
 
#define NCV_CT_ASSERT(X)
 
#define NCV_CT_PREP_PASTE(a, b)
 连接宏。
 
#define NCV_CT_PREP_PASTE_AUX(a, b)
 连接间接宏。
 
#define NCV_RESET_SKIP_COND(x)
 
#define NCV_SET_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)
 
#define SUB_BEGIN(type, name)
 
#define SUB_CALL(name)
 
#define SUB_END(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_ALLOC_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

虚函数 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幅图像的光流*‍/。
 
void cv::cuda::connectivityMask (const GpuMat &image, GpuMat &mask, const cv::Scalar &lo, const cv::Scalar &hi, Stream &stream=Stream::Null())
 计算广义泛洪填充组件标记的掩码。
 
Ptr< cuda::BackgroundSubtractorFGD > cv::cuda::createBackgroundSubtractorFGD (const FGDParams &params=FGDParams())
 创建FGD背景减法器。
 
Ptr< cuda::BackgroundSubtractorGMG > cv::cuda::createBackgroundSubtractorGMG (int initializationFrames=120, double decisionThreshold=0.8)
 创建GMG背景减法器。
 
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 &stream=Stream::Null())
 执行二维规则4连通图的图割标记。
 
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())
 执行二维规则8连通图的图割标记。
 
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())
 执行连通组件标记。
 
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, Ncv32u 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)
 查找基于3D-2D点对应的物体姿态。
 
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 )

#include <opencv2/cudalegacy/NCV.hpp>

值
( (x) > (b) ? (b) : ( (x) < (a) ? (a) : (x) ) )

◆ CLAMP_0_255

#define CLAMP_0_255 ( x)

#include <opencv2/cudalegacy/NCV.hpp>

值
CLAMP(x,0,255)
CLAMP
#define CLAMP(x, a, b)
定义 NCV.hpp:1013

◆ CLAMP_BOTTOM

#define CLAMP_BOTTOM ( x,
a )

#include <opencv2/cudalegacy/NCV.hpp>

值
(((x) < (a)) ? (a) : (x))

◆ CLAMP_TOP

#define CLAMP_TOP ( x,
a )

#include <opencv2/cudalegacy/NCV.hpp>

值
(((x) > (a)) ? (a) : (x))

◆ 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

执行文件范围条件的编译时断言

◆ NCV_CT_PREP_PASTE

#define NCV_CT_PREP_PASTE ( a,
b )

#include <opencv2/cudalegacy/NCV.hpp>

值
NCV_CT_PREP_PASTE_AUX(a, b)
NCV_CT_PREP_PASTE_AUX
#define NCV_CT_PREP_PASTE_AUX(a, b)
连接间接宏。
定义 NCV.hpp:82

连接宏。

◆ NCV_CT_PREP_PASTE_AUX

#define NCV_CT_PREP_PASTE_AUX ( a,
b )

#include <opencv2/cudalegacy/NCV.hpp>

值
a##b

连接间接宏。

◆ NCV_RESET_SKIP_COND

#define NCV_RESET_SKIP_COND ( x)

#include <opencv2/cudalegacy/NCV.hpp>

值
__ncv_skip_cond = x

◆ NCV_SET_SKIP_COND

#define NCV_SET_SKIP_COND ( x)

#include <opencv2/cudalegacy/NCV.hpp>

值
bool __ncv_skip_cond = x

◆ NCV_SKIP_COND_BEGIN

#define NCV_SKIP_COND_BEGIN    if (!__ncv_skip_cond) {

#include <opencv2/cudalegacy/NCV.hpp>

◆ NCV_SKIP_COND_END

#define NCV_SKIP_COND_END    }

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvAssertCUDALastErrorReturn

#define 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); \
} while (0)
cv::String
std::string String
定义 cvstd.hpp:151
cv::format
String format(const char *fmt,...)
返回使用 printf-like 表达式格式化的文本字符串。

◆ ncvAssertCUDAReturn

#define 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); \
} while (0)

◆ ncvAssertPrintCheck

#define 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); \
} \
} while (0)

◆ ncvAssertPrintReturn

#define ncvAssertPrintReturn ( pred,
msg,
err )

#include <opencv2/cudalegacy/NCV.hpp>

值
do \
{ \
ncvAssertPrintCheck(pred, msg); \
if (!(pred)) return err; \
} while (0)

◆ ncvAssertReturn

#define 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); \
} while (0)

◆ ncvAssertReturnNcvStat

#define 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); \
} while (0)
NCVStatus
Ncv32u NCVStatus
定义 NCV.hpp:376
NCV_SUCCESS
@ NCV_SUCCESS
定义 NCV.hpp:316

◆ ncvSafeMatAlloc

#define 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

#define OBJDET_MASK_ELEMENT_INVALID_32U   0xFFFFFFFF

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ RECT_SIMILARITY_PROPORTION

#define RECT_SIMILARITY_PROPORTION   0.2f

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ SQR

#define SQR ( x)

#include <opencv2/cudalegacy/NCV.hpp>

值
((x)*(x))

◆ SUB_BEGIN

#define SUB_BEGIN ( type,
name )

#include <opencv2/cudalegacy/NCV.hpp>

值
struct { __inline type name

◆ SUB_CALL

#define SUB_CALL ( name)

#include <opencv2/cudalegacy/NCV.hpp>

值
name.name

◆ SUB_END

#define SUB_END ( name)

#include <opencv2/cudalegacy/NCV.hpp>

值
} name;

类型定义文档

◆ 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 内核执行错误。

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 

无效的感兴趣区域参数。

NPPST_INVALID_STEP 

无效的图像行步长参数（检查符号、对齐方式以及与图像宽度的关系）

NPPST_INVALID_SCALE 

传递的比例参数无效。

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（检查指针应为设备指针还是固定指针）

NPPST_MEM_INTERNAL_ERROR 

内部内存管理错误。

NCV_LAST_STATUS 

标记，用于在其他文件中继续错误编号。

◆ 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 ( )
inline纯虚函数

#include <opencv2/cudalegacy/NCV.hpp>

◆ alignUp()

Ncv32u alignUp ( Ncv32u 什么,
Ncv32u alignment )

#include <opencv2/cudalegacy/NCV.hpp>

计算对齐的上界值

◆ 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 = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

使用块匹配算法计算两幅图像的光流*‍/。

◆ connectivityMask()

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

#include <opencv2/cudalegacy.hpp>

计算广义泛洪填充组件标记的掩码。

◆ createBackgroundSubtractorFGD()

Ptr< cuda::BackgroundSubtractorFGD > cv::cuda::createBackgroundSubtractorFGD ( const FGDParams & params = FGDParams())

#include <opencv2/cudalegacy.hpp>

创建FGD背景减法器。

参数
paramsAlgorithm 的参数。有关说明，请参见 [161]。

◆ createBackgroundSubtractorGMG()

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

#include <opencv2/cudalegacy.hpp>

创建GMG背景减法器。

参数
initializationFrames用于初始化直方图的视频帧数。
decisionThreshold高于此值的像素将被确定为前景。

◆ createImagePyramid()

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

#include <opencv2/cudalegacy.hpp>

◆ createOpticalFlowNeedleMap()

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

#include <opencv2/cudalegacy.hpp>

◆ graphcut() [1/2]

void cv::cuda::graphcut ( GpuMat & 终端 (terminals),
GpuMat & 左转移 (leftTransp),
GpuMat & 右转移 (rightTransp),
GpuMat & 顶部 (top),
GpuMat & 底部 (bottom),
GpuMat & 标签 (labels),
GpuMat & buf,
Stream & stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

执行二维规则4连通图的图割标记。

◆ graphcut() [2/2]

void cv::cuda::graphcut ( GpuMat & 终端 (terminals),
GpuMat & 左转移 (leftTransp),
GpuMat & 右转移 (rightTransp),
GpuMat & 顶部 (top),
GpuMat & 左上角 (topLeft),
GpuMat & 右上角 (topRight),
GpuMat & 底部 (bottom),
GpuMat & 左下角 (bottomLeft),
GpuMat & 右下角 (bottomRight),
GpuMat & 标签 (labels),
GpuMat & buf,
Stream & stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

执行二维规则8连通图的图割标记。

◆ interpolateFrames()

void cv::cuda::interpolateFrames ( const GpuMat & 帧0 (frame0),
const GpuMat & 帧1 (frame1),
const GpuMat & 向前水平位移 (Forward horizontal displacement),
const GpuMat & 向前垂直位移 (Forward vertical displacement),
const GpuMat & 向后水平位移 (Backward horizontal displacement),
const GpuMat & 向后垂直位移 (Backward vertical displacement),
浮点数 (float) 位置 (pos),
GpuMat & 新帧 (newFrame),
GpuMat & buf,
Stream & stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

使用提供的光流（位移场）插值帧（图像）。

参数
帧0 (frame0)第一帧（32位浮点图像，单通道）。
帧1 (frame1)第二帧。必须与frame0具有相同的类型和大小。
向前水平位移 (Forward horizontal displacement)向前水平位移。
向前垂直位移 (Forward vertical displacement)向前垂直位移。
向后水平位移 (Backward horizontal displacement)向后水平位移。
向后垂直位移 (Backward vertical displacement)向后垂直位移。
位置 (pos)新帧位置。
新帧 (newFrame)输出图像。
buf临时缓冲区，宽度为width x 6*height，类型为CV_32FC1，包含6个GpuMat：第一帧的遮挡掩码、第二帧的遮挡掩码、插值向前水平流、插值向前垂直流、插值向后水平流、插值向后垂直流。
流 (stream)Stream 用于异步版本。

◆ labelComponents()

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

#include <opencv2/cudalegacy.hpp>

执行连通组件标记。

◆ memSegCopyHelper()

NCVStatus memSegCopyHelper ( void * 目标 (dst),
NCVMemoryType 目标类型 (dstType),
const void * 源 (src),
NCVMemoryType 源类型 (srcType),
size_t 大小 (sz),
cudaStream_t cuStream )

#include <opencv2/cudalegacy/NCV.hpp>

复制调度程序 (Copy dispatchers)

◆ memSegCopyHelper2D()

NCVStatus memSegCopyHelper2D ( void * 目标 (dst),
Ncv32u 目标步长 (dstPitch),
NCVMemoryType 目标类型 (dstType),
const void * 源 (src),
Ncv32u 源步长 (srcPitch),
NCVMemoryType 源类型 (srcType),
Ncv32u 宽度字节数 (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 > & 积分图像 (d_integralImage),
NCVMatrix< Ncv32f > & 权重 (d_weights),
NCVMatrixAlloc< Ncv32u > & 像素掩码 (d_pixelMask),
Ncv32u & 检测数 (numDetections),
HaarClassifierCascadeDescriptor & 哈尔特征 (haar),
NCVVector< HaarStage64 > & 哈尔级联 (h_HaarStages),
NCVVector< HaarStage64 > & d_HaarStages,
NCVVector< HaarClassifierNode128 > & d_HaarNodes,
NCVVector< HaarFeature64 > & d_HaarFeatures,
NcvBool 掩码元素 (bMaskElements),
NcvSize32u 锚点区域 (anchorsRoi),
Ncv32u 像素步长 (pixelStep),
Ncv32f 缩放区域 (scaleArea),
INCVMemAllocator & GPU内存分配器 (gpuAllocator),
INCVMemAllocator & CPU内存分配器 (cpuAllocator),
cudaDeviceProp & 设备属性 (devProp),
cudaStream_t cuStream )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvApplyHaarClassifierCascade_host()

NCVStatus ncvApplyHaarClassifierCascade_host ( NCVMatrix< Ncv32u > & 积分图像 (h_integralImage),
NCVMatrix< Ncv32f > & 权重 (h_weights),
NCVMatrixAlloc< Ncv32u > & 像素掩码 (h_pixelMask),
Ncv32u & 检测数 (numDetections),
HaarClassifierCascadeDescriptor & 哈尔特征 (haar),
NCVVector< HaarStage64 > & 哈尔级联 (h_HaarStages),
NCVVector< HaarClassifierNode128 > & h_HaarNodes,
NCVVector< HaarFeature64 > & h_HaarFeatures,
NcvBool 掩码元素 (bMaskElements),
NcvSize32u 锚点区域 (anchorsRoi),
Ncv32u 像素步长 (pixelStep),
Ncv32f scaleArea )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ NCVBroxOpticalFlow()

NCVStatus NCVBroxOpticalFlow ( const NCVBroxOpticalFlowDescriptor 描述符 (desc),
INCVMemAllocator & GPU内存分配器 (gpu_mem_allocator),
const NCVMatrix< Ncv32f > & 帧0 (frame0),
const NCVMatrix< Ncv32f > & 帧1 (frame1),
NCVMatrix< Ncv32f > & u,
NCVMatrix< Ncv32f > & v,
cudaStream_t stream )

#include <opencv2/cudalegacy/NCVBroxOpticalFlow.hpp>

计算光流。

基于Brox等人的方法[2004]

参数
[输入 (in)]描述符 (desc)模型和求解器参数
[输入 (in)]GPU内存分配器 (gpu_mem_allocator)GPU内存分配器
[输入 (in)]帧0 (frame0)源帧
[输入 (in)]帧1 (frame1)要跟踪的帧
[输出 (out)]u水平光流分量（沿x轴）
[输出 (out)]v垂直光流分量（沿y轴）
流 (stream)
返回值 (Returns)
计算状态

◆ ncvDebugOutput()

void ncvDebugOutput ( const cv::String & msg)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDetectObjectsMultiScale_device()

NCVStatus ncvDetectObjectsMultiScale_device ( NCVMatrix< Ncv8u > & 源图像 (d_srcImg),
NcvSize32u 源区域 (srcRoi),
NCVVector< NcvRect32u > & 目标矩形 (d_dstRects),
Ncv32u & 目标矩形数量 (dstNumRects),
HaarClassifierCascadeDescriptor & 哈尔特征 (haar),
NCVVector< HaarStage64 > & 哈尔级联 (h_HaarStages),
NCVVector< HaarStage64 > & d_HaarStages,
NCVVector< HaarClassifierNode128 > & d_HaarNodes,
NCVVector< HaarFeature64 > & d_HaarFeatures,
NcvSize32u 最小目标大小 (minObjSize),
Ncv32u 最小邻域 (minNeighbors),
Ncv32f 缩放步长 (scaleStep),
Ncv32u 像素步长 (pixelStep),
Ncv32u 标志 (flags),
INCVMemAllocator & GPU内存分配器 (gpuAllocator),
INCVMemAllocator & CPU内存分配器 (cpuAllocator),
cudaDeviceProp & 设备属性 (devProp),
cudaStream_t cuStream )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvDrawRects_32u_device()

NCVStatus ncvDrawRects_32u_device ( Ncv32u * 目标 (d_dst),
Ncv32u 目标步长 (dstStride),
Ncv32u 目标宽度 (dstWidth),
Ncv32u 目标高度 (dstHeight),
NcvRect32u * 矩形 (d_rects),
Ncv32u 矩形数量 (numRects),
Ncv32u 颜色 (color),
cudaStream_t cuStream )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_32u_host()

NCVStatus ncvDrawRects_32u_host ( Ncv32u * 目标 (h_dst),
Ncv32u 目标步长 (dstStride),
Ncv32u 目标宽度 (dstWidth),
Ncv32u 目标高度 (dstHeight),
NcvRect32u * 矩形 (h_rects),
Ncv32u 矩形数量 (numRects),
Ncv32u color )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_device()

NCVStatus ncvDrawRects_8u_device ( Ncv8u * 目标 (d_dst),
Ncv32u 目标步长 (dstStride),
Ncv32u 目标宽度 (dstWidth),
Ncv32u 目标高度 (dstHeight),
NcvRect32u * 矩形 (d_rects),
Ncv32u 矩形数量 (numRects),
Ncv8u 颜色 (color),
cudaStream_t cuStream )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_host()

NCVStatus ncvDrawRects_8u_host ( Ncv8u * 目标 (h_dst),
Ncv32u 目标步长 (dstStride),
Ncv32u 目标宽度 (dstWidth),
Ncv32u 目标高度 (dstHeight),
NcvRect32u * 矩形 (h_rects),
Ncv32u 矩形数量 (numRects),
Ncv8u color )

#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,
Ncv32u & 假设数量,
Ncv32u 最小邻域 (minNeighbors),
Ncv32f 相交阈值,
NCVVector< Ncv32u > * hypothesesWeights )

#include <opencv2/cudalegacy/NCV.hpp>

矩形运算

◆ ncvGrowDetectionsVector_device()

NCVStatus ncvGrowDetectionsVector_device ( NCVVector< Ncv32u > & 像素掩码,
Ncv32u 像素掩码检测数,
NCVVector< NcvRect32u > & 假设,
Ncv32u & 总检测数,
Ncv32u 最大总检测数,
Ncv32u 矩形宽度,
Ncv32u 矩形高度,
Ncv32f 当前比例,
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,
NCVVector< NcvRect32u > & 假设,
Ncv32u & 总检测数,
Ncv32u 最大总检测数,
Ncv32u 矩形宽度,
Ncv32u 矩形高度,
Ncv32f curScale )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarGetClassifierSize()

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

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarLoadFromFile_host()

NCVStatus ncvHaarLoadFromFile_host ( const cv::String & 文件名,
HaarClassifierCascadeDescriptor & 哈尔特征 (haar),
NCVVector< HaarStage64 > & 哈尔级联 (h_HaarStages),
NCVVector< HaarClassifierNode128 > & h_HaarNodes,
NCVVector< HaarFeature64 > & h_HaarFeatures )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarStoreNVBIN_host()

NCVStatus ncvHaarStoreNVBIN_host ( const cv::String & 文件名,
HaarClassifierCascadeDescriptor 哈尔特征 (haar),
NCVVector< HaarStage64 > & 哈尔级联 (h_HaarStages),
NCVVector< HaarClassifierNode128 > & h_HaarNodes,
NCVVector< HaarFeature64 > & h_HaarFeatures )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvSetDebugOutputHandler()

void ncvSetDebugOutputHandler ( NCVDebugOutputHandler * 函数)

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvStartTimer()

NcvTimer ncvStartTimer ( void )

#include <opencv2/cudalegacy/NCV.hpp>

◆ projectPoints()

void cv::cuda::projectPoints ( const GpuMat & 源 (src),
const Mat & 旋转向量,
const Mat & 平移向量,
const Mat & 相机内参矩阵,
const Mat & 畸变系数。详见undistortPoints。,
GpuMat & 目标 (dst),
Stream & stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

◆ solvePnPRansac()

void cv::cuda::solvePnPRansac ( const Mat & 目标点,
const Mat & image,
const Mat & 相机内参矩阵,
const Mat & 畸变系数。详见undistortPoints。,
Mat & 旋转向量,
Mat & 平移向量,
bool use_extrinsic_guess = false,
int num_iters = 100,
浮点数 (float) max_dist = 8.0,
int min_inlier_count = 100,
std::vector< int > * inliers = NULL )

#include <opencv2/cudalegacy.hpp>

查找基于3D-2D点对应的物体姿态。

参数
目标点目标点的单行矩阵。
image图像点的单行矩阵。
相机内参矩阵3x3相机内参矩阵。
畸变系数。详见undistortPoints。畸变系数。详见undistortPoints。
旋转向量输出的3D旋转向量。
平移向量输出的3D平移向量。
use_extrinsic_guess指示函数是否必须使用rvec和tvec作为初始变换猜测的标志。目前不支持。
num_iters最大RANSAC迭代次数。
max_dist用于检测点是否为内点的欧几里德距离阈值。
min_inlier_count指示如果达到大于或等于数量的内点则函数必须停止的标志。目前不支持。
inliers输出的内点索引向量。

◆ transformPoints()

void cv::cuda::transformPoints ( const GpuMat & 源 (src),
const Mat & 旋转向量,
const Mat & 平移向量,
GpuMat & 目标 (dst),
Stream & stream = Stream::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>

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