主題
	NPPST 核心

	NPPST 影像處理

	NPPST 訊號處理

詳細說明

名稱空間
名稱空間	NcvCTprep

類
類	cv::cuda::BackgroundSubtractorFGD
	該類透過構建和維護背景模型來區分前景和背景畫素。更多...

類	cv::cuda::BackgroundSubtractorGMG
	背景/前景分割演算法。更多...

類	cv::cuda::FastOpticalFlowBM

結構體	cv::cuda::FGDParams

結構體	HaarClassifierCascadeDescriptor

結構體	HaarClassifierNode128

結構體	HaarClassifierNodeDescriptor32

結構體	HaarFeature64

結構體	HaarFeatureDescriptor32

結構體	HaarStage64

類	cv::cuda::ImagePyramid

類	INCVMemAllocator

結構體	NCVBroxOpticalFlowDescriptor
	模型和求解器引數。更多...

類	NCVMatrix< T >

類	NCVMatrixAlloc< T >

類	NCVMatrixReuse< T >

類	NCVMemNativeAllocator

結構體	NCVMemPtr

結構體	NCVMemSegment

類	NCVMemStackAllocator

結構體	NcvPoint2D32s

結構體	NcvPoint2D32u

結構體	NcvRect32s

結構體	NcvRect32u

結構體	NcvRect8u

結構體	NcvSize32s

結構體	NcvSize32u

類	NCVVector< T >

類	NCVVectorAlloc< T >

類	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)
	連線宏。

#define	NCV_CT_PREP_PASTE_AUX(a, b)
	連線間接宏。

#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)

型別定義 (Typedefs)
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

列舉
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 }

函式
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())
	使用塊匹配演算法計算兩張影像的光流。

void	cv::cuda::connectivityMask (const GpuMat &image, GpuMat &mask, const cv::Scalar &lo, const cv::Scalar &hi, Stream &stream=Stream::Null())
	為廣義漫水填充演算法計算連通分量掩碼。

Ptr< cuda::BackgroundSubtractorFGD >	cv::cuda::createBackgroundSubtractorFGD (const FGDParams &params=FGDParams())
	建立 FGD 背景減除器。

Ptr< cuda::BackgroundSubtractorGMG >	cv::cuda::createBackgroundSubtractorGMG (int initializationFrames=120, double decisionThreshold=0.8)
	建立 GMG 背景減除器。

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())
	透過 2D 常規 4 連通圖的圖割（graph cuts）執行標記。

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())
	透過 2D 常規 8 連通圖的圖割執行標記。

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（位移場）插值幀（影像）。

void	cv::cuda::labelComponents (const GpuMat &mask, GpuMat &components, int flags=0, Stream &stream=Stream::Null())
	執行連通分量標記。

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)
	計算光流。

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)
	從 3D-2D 點對應關係中查詢物體姿態。

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

變數
const Ncv32u	K_LOG2_WARP_SIZE = 5

const Ncv32u	K_WARP_SIZE = 32

宏定義文件

◆ 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)

定義 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)

連線宏。

定義 NCV.hpp:83

NcvCTprep::CT_ASSERT_FAILURE

定義 NCV.hpp:72

NcvCTprep::assertTest

定義 NCV.hpp:78

在檔案作用域上執行編譯時斷言

◆ 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)

連線間接宏。

定義 NCV.hpp:82

連線宏。

◆ NCV_CT_PREP_PASTE_AUX

#define NCV_CT_PREP_PASTE_AUX	(		a,
			b )

#include <opencv2/cudalegacy/NCV.hpp>

值

a##b

連線間接宏。

◆ 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)

◆ 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)

◆ 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

定義 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;

型別定義文件 (Typedef Documentation)

◆ 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>

列舉型別文件 (Enumeration Type Documentation)

◆ 匿名列舉

匿名列舉

#include <opencv2/cudalegacy/NCV.hpp>

用於狀態通知、錯誤和警告的返回碼

列舉值 (Enumerator)
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 (與 NPP_NO_ERROR 相同)
NPPST_ERROR	未知錯誤。
NPPST_CUDA_KERNEL_EXECUTION_ERROR	CUDA 核心執行錯誤。
NPPST_NULL_POINTER_ERROR	空指標引數錯誤。
NPPST_TEXTURE_BIND_ERROR	CUDA 紋理繫結錯誤或返回非零偏移。
NPPST_MEMCPY_ERROR	CUDA 記憶體複製錯誤。
NPPST_MEM_ALLOC_ERR	CUDA 記憶體分配錯誤。
NPPST_MEMFREE_ERR	CUDA 記憶體釋放錯誤。
NPPST_INVALID_ROI	無效的感興趣區域引數。
NPPST_INVALID_STEP	無效的影像行步長引數（檢查符號、對齊方式、與影像寬度的關係）
NPPST_INVALID_SCALE	傳遞的比例引數無效。
NPPST_MEM_INSUFFICIENT_BUFFER	使用者分配的緩衝區不足。
NPPST_MEM_RESIDENCE_ERROR	檢測到記憶體駐留錯誤（檢查指標是裝置指標還是固定記憶體指標）
NPPST_MEM_INTERNAL_ERROR	內部記憶體管理錯誤。
NCV_LAST_STATUS	標記以在其他檔案中繼續錯誤編號。

◆ 匿名列舉

匿名列舉

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

列舉值 (Enumerator)
NCVPipeObjDet_Default
NCVPipeObjDet_UseFairImageScaling
NCVPipeObjDet_FindLargestObject
NCVPipeObjDet_VisualizeInPlace

◆ NCVMemoryType

enum NCVMemoryType

#include <opencv2/cudalegacy/NCV.hpp>

NCVMemoryType

列舉值 (Enumerator)
NCVMemoryTypeNone
NCVMemoryTypeHostPageable
NCVMemoryTypeHostPinned
NCVMemoryTypeDevice

函式文件 (Function Documentation)

◆ ~INCVMemAllocator()

INCVMemAllocator::~INCVMemAllocator ( )

inlinepure virtual

#include <opencv2/cudalegacy/NCV.hpp>

◆ alignUp()

Ncv32u alignUp	(	Ncv32u	what,
		Ncv32u	alignment )

#include <opencv2/cudalegacy/NCV.hpp>

計算對齊的上邊界值

◆ 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,
		流 (Stream) &	stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

使用塊匹配演算法計算兩張影像的光流。

◆ connectivityMask()

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

#include <opencv2/cudalegacy.hpp>

為廣義漫水填充演算法計算連通分量掩碼。

◆ createBackgroundSubtractorFGD()

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

#include <opencv2/cudalegacy.hpp>

建立 FGD 背景減除器。

引數

params Algorithm 的引數。請參見 [167] 以獲取解釋。

◆ createBackgroundSubtractorGMG()

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

#include <opencv2/cudalegacy.hpp>

建立 GMG 背景減除器。

引數

initializationFrames	用於初始化直方圖的影片幀數。
decisionThreshold	畫素被確定為前景的值。

◆ createImagePyramid()

Ptr< ImagePyramid > cv::cuda::createImagePyramid	(	InputArray	img,
		int	nLayers = -1,
		流 (Stream) &	stream = Stream::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 (上),
		GpuMat &	bottom (下),
		GpuMat &	labels,
		GpuMat &	buf,
		流 (Stream) &	stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

透過 2D 常規 4 連通圖的圖割（graph cuts）執行標記。

◆ graphcut() [2/2]

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

#include <opencv2/cudalegacy.hpp>

透過 2D 常規 8 連通圖的圖割執行標記。

◆ 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,
		流 (Stream) &	stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

使用提供的光流（位移場）插值幀（影像）。

引數

frame0	第一幀（32位浮點影像，單通道）。
frame1	第二幀。必須與 frame0 具有相同的型別和大小。
fu	向前水平位移。
fv	向前垂直位移。
bu	向後水平位移。
bv	向後垂直位移。
pos	新幀位置。
newFrame	輸出影像。
buf	臨時緩衝區，寬度 x 6*高度大小，CV_32FC1 型別，包含 6 個 GpuMat：第一幀的遮擋掩碼，第二幀的遮擋掩碼，插值前向水平流，插值前向垂直流，插值後向水平流，插值後向垂直流。
流	Stream 用於非同步版本。

◆ labelComponents()

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

#include <opencv2/cudalegacy.hpp>

執行連通分量標記。

◆ memSegCopyHelper()

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

#include <opencv2/cudalegacy/NCV.hpp>

複製排程程式

◆ 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	流 )

#include <opencv2/cudalegacy/NCVBroxOpticalFlow.hpp>

計算光流。

基於 Brox 等人 [2004] 的方法

引數

[in]	desc	模型和求解器引數
[in]	gpu_mem_allocator	GPU 記憶體分配器
[in]	frame0	源幀
[in]	frame1	要跟蹤的幀
[out]	u	流水平分量（沿 x 軸）
[out]	v	流垂直分量（沿 y 軸）
	流

返回: 計算狀態

◆ 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 (標誌),
		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 *	d_rects,
		Ncv32u	numRects,
		Ncv32u	color,
		cudaStream_t	cuStream )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_32u_host()

NCVStatus ncvDrawRects_32u_host	(	Ncv32u *	h_dst,
		Ncv32u	dstStride,
		Ncv32u	dstWidth,
		Ncv32u	dstHeight,
		NcvRect32u *	h_rects,
		Ncv32u	numRects,
		Ncv32u	color )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_device()

NCVStatus ncvDrawRects_8u_device	(	Ncv8u *	d_dst,
		Ncv32u	dstStride,
		Ncv32u	dstWidth,
		Ncv32u	dstHeight,
		NcvRect32u *	d_rects,
		Ncv32u	numRects,
		Ncv8u	color,
		cudaStream_t	cuStream )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvDrawRects_8u_host()

NCVStatus ncvDrawRects_8u_host	(	Ncv8u *	h_dst,
		Ncv32u	dstStride,
		Ncv32u	dstWidth,
		Ncv32u	dstHeight,
		NcvRect32u *	h_rects,
		Ncv32u	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 > &	hypotheses,
		Ncv32u &	numHypotheses,
		Ncv32u	minNeighbors,
		Ncv32f	intersectEps,
		NCVVector< Ncv32u > *	hypothesesWeights )

#include <opencv2/cudalegacy/NCV.hpp>

矩形操作

◆ ncvGrowDetectionsVector_device()

NCVStatus ncvGrowDetectionsVector_device	(	NCVVector< Ncv32u > &	pixelMask,
		Ncv32u	numPixelMaskDetections,
		NCVVector< NcvRect32u > &	hypotheses,
		Ncv32u &	totalDetections,
		Ncv32u	totalMaxDetections,
		Ncv32u	rectWidth,
		Ncv32u	rectHeight,
		Ncv32f	curScale,
		cudaStream_t	cuStream )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvGrowDetectionsVector_host()

NCVStatus ncvGrowDetectionsVector_host	(	NCVVector< Ncv32u > &	pixelMask,
		Ncv32u	numPixelMaskDetections,
		NCVVector< NcvRect32u > &	hypotheses,
		Ncv32u &	totalDetections,
		Ncv32u	totalMaxDetections,
		Ncv32u	rectWidth,
		Ncv32u	rectHeight,
		Ncv32f	curScale )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarGetClassifierSize()

NCVStatus ncvHaarGetClassifierSize	(	const cv::String &	filename,
		Ncv32u &	numStages,
		Ncv32u &	numNodes,
		Ncv32u &	numFeatures )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarLoadFromFile_host()

NCVStatus ncvHaarLoadFromFile_host	(	const cv::String &	filename,
		HaarClassifierCascadeDescriptor &	haar,
		NCVVector< HaarStage64 > &	h_HaarStages,
		NCVVector< HaarClassifierNode128 > &	h_HaarNodes,
		NCVVector< HaarFeature64 > &	h_HaarFeatures )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvHaarStoreNVBIN_host()

NCVStatus ncvHaarStoreNVBIN_host	(	const cv::String &	filename,
		HaarClassifierCascadeDescriptor	haar,
		NCVVector< HaarStage64 > &	h_HaarStages,
		NCVVector< HaarClassifierNode128 > &	h_HaarNodes,
		NCVVector< HaarFeature64 > &	h_HaarFeatures )

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

◆ ncvSetDebugOutputHandler()

void ncvSetDebugOutputHandler ( NCVDebugOutputHandler * func )

#include <opencv2/cudalegacy/NCV.hpp>

◆ ncvStartTimer()

NcvTimer 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,
		流 (Stream) &	stream = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

◆ solvePnPRansac()

void cv::cuda::solvePnPRansac	(	const Mat &	object,
		const Mat &	影像,
		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>

從 3D-2D 點對應關係中查詢物體姿態。

引數

object	物體點單行矩陣。
影像	影像點單行矩陣。
camera_mat	3x3 的相機內參矩陣。
dist_coef	畸變係數。詳情請參見 undistortPoints。
rvec	輸出 3D 旋轉向量。
tvec	輸出 3D 平移向量。
use_extrinsic_guess	標誌，指示函式必須使用 rvec 和 tvec 作為初始變換猜測。目前不支援此功能。
num_iters	RANSAC 最大迭代次數。
max_dist	歐幾里得距離閾值，用於檢測點是否為內點。
min_inlier_count	標誌，指示如果達到大於或等於內點數，函式必須停止。目前不支援此功能。
inliers	內點索引的輸出向量。

◆ transformPoints()

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

#include <opencv2/cudalegacy.hpp>

變數文件

◆ 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>

主題

詳細說明

名稱空間

類

宏

型別定義 (Typedefs)

列舉

函式

變數

宏定義文件

◆ CLAMP

◆ CLAMP_0_255

◆ CLAMP_BOTTOM

◆ CLAMP_TOP

◆ HAAR_STDDEV_BORDER

◆ NCV_CT_ASSERT

◆ NCV_CT_PREP_PASTE

◆ NCV_CT_PREP_PASTE_AUX

◆ NCV_RESET_SKIP_COND

◆ NCV_SET_SKIP_COND

◆ NCV_SKIP_COND_BEGIN

◆ NCV_SKIP_COND_END

◆ ncvAssertCUDALastErrorReturn

◆ ncvAssertCUDAReturn

◆ ncvAssertPrintCheck

◆ ncvAssertPrintReturn

◆ ncvAssertReturn

◆ ncvAssertReturnNcvStat

◆ ncvSafeMatAlloc

◆ OBJDET_MASK_ELEMENT_INVALID_32U

◆ RECT_SIMILARITY_PROPORTION

◆ SQR

◆ SUB_BEGIN

◆ SUB_CALL

◆ SUB_END

型別定義文件 (Typedef Documentation)

◆ Ncv16s

◆ Ncv16u

◆ Ncv32f

◆ Ncv32f_a

◆ Ncv32s

◆ Ncv32u

◆ Ncv32u_a

◆ Ncv64f

◆ Ncv64s

◆ Ncv64u

◆ Ncv8s

◆ Ncv8u

◆ NcvBool

◆ NCVDebugOutputHandler

◆ NCVStatus

◆ NcvTimer

列舉型別文件 (Enumeration Type Documentation)

◆ 匿名列舉

◆ 匿名列舉

◆ NCVMemoryType

函式文件 (Function Documentation)

◆ ~INCVMemAllocator()

◆ alignUp()

◆ calcOpticalFlowBM()

◆ connectivityMask()

◆ createBackgroundSubtractorFGD()

◆ createBackgroundSubtractorGMG()

◆ createImagePyramid()

◆ createOpticalFlowNeedleMap()

◆ graphcut() [1/2]

◆ graphcut() [2/2]

◆ interpolateFrames()

◆ labelComponents()

◆ memSegCopyHelper()

◆ memSegCopyHelper2D()

◆ NCV_CT_ASSERT() [1/5]

◆ NCV_CT_ASSERT() [2/5]

◆ NCV_CT_ASSERT() [3/5]

◆ NCV_CT_ASSERT() [4/5]

◆ NCV_CT_ASSERT() [5/5]

◆ ncvApplyHaarClassifierCascade_device()

◆ ncvApplyHaarClassifierCascade_host()

◆ NCVBroxOpticalFlow()

◆ ncvDebugOutput()