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	NPPST コア

	NPPST画像処理

	NPPST 信号処理

詳細説明

名前空間
namespace	NcvCTprep

クラス
class	cv::cuda::BackgroundSubtractorFGD
	このクラスは、背景のモデルを構築・維持することで前景ピクセルと背景ピクセルを判別する。続きを読む...

class	cv::cuda::BackgroundSubtractorGMG
	背景/前景セグメンテーション (領域分割) Algorithm。続きを読む...

class	cv::cuda::FastOpticalFlowBM

struct	cv::cuda::FGDParams

struct	HaarClassifierCascadeDescriptor

struct	HaarClassifierNode128

struct	HaarClassifierNodeDescriptor32

struct	HaarFeature64

struct	HaarFeatureDescriptor32

struct	HaarStage64

class	cv::cuda::ImagePyramid

class	INCVMemAllocator

struct	NCVBroxOpticalFlowDescriptor
	モデルおよびソルバのパラメータ。さらに...

class	NCVMatrix< T >

class	NCVMatrixAlloc< T >

class	NCVMatrixReuse< T >

class	NCVMemNativeAllocator

struct	NCVMemPtr

struct	NCVMemSegment

class	NCVMemStackAllocator

struct	NcvPoint2D32s

struct	NcvPoint2D32u

struct	NcvRect32s

struct	NcvRect32u

struct	NcvRect8u

struct	NcvSize32s

struct	NcvSize32u

class	NCVVector< T >

class	NCVVectorAlloc< T >

class	NCVVectorReuse< T >

マクロ定義
#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)
	連結マクロ。

#define	NCV_CT_PREP_PASTE_AUX(a, b)
	連結間接参照マクロ。

#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)

型定義
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

列挙型
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 }

関数
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())
	ブロックマッチングアルゴリズムを用いて2枚の画像のオプティカルフローを計算する *‍/。

void	cv::cuda::connectivityMask (const GpuMat &image, GpuMat &mask, const cv::Scalar &lo, const cv::Scalar &hi, Stream &stream=Stream::Null())
	一般化フラッドフィル(Generalized Flood fill)による成分ラベリング用のマスクを計算する。

Ptr< cuda::BackgroundSubtractorFGD >	cv::cuda::createBackgroundSubtractorFGD (const FGDParams &params=FGDParams())
	FGD背景差分器を生成する。

Ptr< cuda::BackgroundSubtractorGMG >	cv::cuda::createBackgroundSubtractorGMG (int initializationFrames=120, double decisionThreshold=0.8)
	GMG背景差分器を生成する。

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())
	2D正則4近傍グラフのグラフカットによるラベリングを行う。

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())
	2D正則8近傍グラフのグラフカットによるラベリングを行う。

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())
	指定されたオプティカルフロー（変位場）を用いてフレーム（画像）を補間する。

void	cv::cuda::labelComponents (const GpuMat &mask, GpuMat &components, int flags=0, Stream &stream=Stream::Null())
	連結成分のラベリングを行う。

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)
	オプティカルフローを計算する。

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)
	3D-2D点対応からオブジェクトの姿勢を求める。

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

変数
const Ncv32u	K_LOG2_WARP_SIZE = 5

const Ncv32u	K_WARP_SIZE = 32

マクロ定義詳解

◆ CLAMP

#define CLAMP	(	x,
		a,
		b )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

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

◆ CLAMP_0_255

#define CLAMP_0_255 ( x )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

CLAMP(x,0,255)

CLAMP

#define CLAMP(x, a, b)

Definition NCV.hpp:1013

◆ CLAMP_BOTTOM

#define CLAMP_BOTTOM	(		x,
			a )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

(((x) < (a)) ? (a) : (x))

◆ CLAMP_TOP

#define CLAMP_TOP	(		x,
			a )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

(((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>

Value:

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)

Concatenation macro.

Definition NCV.hpp:83

NcvCTprep::CT_ASSERT_FAILURE

Definition NCV.hpp:72

NcvCTprep::assertTest

Definition NCV.hpp:78

ファイルスコープで条件のコンパイル時アサーションを実行する

◆ NCV_CT_PREP_PASTE

#define NCV_CT_PREP_PASTE	(		a,
			b )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

NCV_CT_PREP_PASTE_AUX(a, b)

NCV_CT_PREP_PASTE_AUX

#define NCV_CT_PREP_PASTE_AUX(a, b)

Concatenation indirection macro.

Definition NCV.hpp:82

連結マクロ。

◆ NCV_CT_PREP_PASTE_AUX

#define NCV_CT_PREP_PASTE_AUX	(		a,
			b )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

a##b

連結間接参照マクロ。

◆ NCV_RESET_SKIP_COND

#define NCV_RESET_SKIP_COND ( x )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

__ncv_skip_cond = x

◆ NCV_SET_SKIP_COND

#define NCV_SET_SKIP_COND ( x )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

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>

Value:

 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>

Value:

 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>

Value:

 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>

Value:

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

◆ ncvAssertReturn

#define ncvAssertReturn	(		pred,
			err )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

 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>

Value:

 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>

Value:

NCVMatrixAlloc<type> name(alloc, width, height); \

ncvAssertReturn(name.isMemAllocated(), err);

NCVMatrixAlloc

Definition 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>

Value:

((x)*(x))

◆ SUB_BEGIN

#define SUB_BEGIN	(		type,
			name )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

struct { __inline type name

◆ SUB_CALL

#define SUB_CALL ( name )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

name.name

◆ SUB_END

#define SUB_END ( name )

#include <opencv2/cudalegacy/NCV.hpp>

Value:

} name;

型定義詳解

◆ 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>

列挙型詳解

◆ anonymous enum

anonymous enum

#include <opencv2/cudalegacy/NCV.hpp>

状態通知、エラー、警告のための戻りコード

列挙値
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	処理に成功(NPP_NO_ERROR と同じ)。
NPPST_ERROR	不明なエラー。
NPPST_CUDA_KERNEL_EXECUTION_ERROR	CUDA カーネルの実行エラー。
NPPST_NULL_POINTER_ERROR	NULL ポインタ引数エラー。
NPPST_TEXTURE_BIND_ERROR	CUDA テクスチャバインディングエラー、またはゼロ以外のオフセットが返された。
NPPST_MEMCPY_ERROR	CUDA メモリコピーエラー。
NPPST_MEM_ALLOC_ERR	CUDA メモリ確保エラー。
NPPST_MEMFREE_ERR	CUDA メモリ解放エラー。
NPPST_INVALID_ROI	不正な注目領域引数。
NPPST_INVALID_STEP	不正な画像ラインステップ引数(符号、アライメント、画像幅との関係を確認すること)。
NPPST_INVALID_SCALE	不正なスケール引数が渡された。
NPPST_MEM_INSUFFICIENT_BUFFER	ユーザが確保したバッファが不足している。
NPPST_MEM_RESIDENCE_ERROR	メモリ常駐エラーを検出(ポインタがデバイスメモリまたはピン留めメモリであるべきか確認すること)。
NPPST_MEM_INTERNAL_ERROR	内部メモリ管理エラー。
NCV_LAST_STATUS	他のファイルでエラー番号付けを継続するためのマーカー。

◆ anonymous enum

anonymous enum

#include <opencv2/cudalegacy/NCVHaarObjectDetection.hpp>

列挙値
NCVPipeObjDet_Default
NCVPipeObjDet_UseFairImageScaling
NCVPipeObjDet_FindLargestObject
NCVPipeObjDet_VisualizeInPlace

◆ NCVMemoryType

enum NCVMemoryType

#include <opencv2/cudalegacy/NCV.hpp>

NCVMemoryType

列挙値
NCVMemoryTypeNone
NCVMemoryTypeHostPageable
NCVMemoryTypeHostPinned
NCVMemoryTypeDevice

関数詳解

◆ ~INCVMemAllocator()

INCVMemAllocator::~INCVMemAllocator ( )

inlinepure virtual

#include <opencv2/cudalegacy/NCV.hpp>

◆ alignUp()

Ncv32u alignUp	(	Ncv32u	what,
		Ncv32u	alignment )

#include <opencv2/cudalegacy/NCV.hpp>

アラインメントされた上限値を計算する

◆ 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>

ブロックマッチングアルゴリズムを用いて2枚の画像のオプティカルフローを計算する *‍/。

◆ 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>

一般化フラッドフィル成分のラベリングのためのマスクを計算する。

◆ createBackgroundSubtractorFGD()

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

#include <opencv2/cudalegacy.hpp>

FGD 背景差分器を生成する。

引数

params Algorithm の引数。説明については [167] を参照。

◆ createBackgroundSubtractorGMG()

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

#include <opencv2/cudalegacy.hpp>

GMG 背景差分器を生成する。

引数

initializationFrames	ヒストグラムの初期化に使用する動画のフレーム数。
decisionThreshold	ピクセルが前景 (FG) と判定されるしきい値。

◆ 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 &	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 = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

2次元の正則な4連結グラフのグラフカットによってラベリングを行う。

◆ 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 = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

2次元の正則な8連結グラフのグラフカットによってラベリングを行う。

◆ 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 = Stream::Null() )

#include <opencv2/cudalegacy.hpp>

与えられたオプティカルフロー(変位場)を用いてフレーム(画像)を補間する。

引数

frame0	最初のフレーム(32ビット浮動小数点画像、シングルチャンネル)。
frame1	2番目のフレーム。frame0 と同じ型およびサイズでなければならない。
fu	前方向の水平変位。
fv	前方向の垂直変位。
bu	後方向の水平変位。
bv	後方向の垂直変位。
pos	新しいフレーム位置。
newFrame	出力画像。
buf	一時バッファ。width x 6*height のサイズ、CV_32FC1 型を持ち、6つの GpuMat を含む。すなわち、最初のフレームのオクルージョンマスク、2番目のフレームのオクルージョンマスク、補間された前方向の水平フロー、補間された前方向の垂直フロー、補間された後方向の水平フロー、補間された後方向の垂直フロー。
stream	非同期版のための Stream。

◆ labelComponents()

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

#include <opencv2/cudalegacy.hpp>

連結成分のラベリングを行う。

◆ memSegCopyHelper()

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

#include <opencv2/cudalegacy/NCV.hpp>

コピーのディスパッチャ

◆ 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>

オプティカルフローを計算する。

Brox et al [2004] の手法に基づく

引数

[in]	desc	モデルおよびソルバの引数
[in]	gpu_mem_allocator	GPUメモリアロケータ
[in]	frame0	ソースフレーム
[in]	frame1	追跡対象のフレーム
[out]	u	フローの水平成分(x 軸に沿った成分)
[out]	v	フローの垂直成分(y 軸に沿った成分)
	stream

戻り値: 計算ステータス

◆ 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 *	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>

矩形に関する演算

◆ 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,
		Stream &	stream = Stream::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>

3D-2D点対応からオブジェクトの姿勢を求める。

引数

object	オブジェクト点の単一行の行列。
image	画像点の単一行の行列。
camera_mat	カメラの内部パラメータの3x3行列。
dist_coef	歪み係数。詳細は undistortPoints を参照。
rvec	出力される3次元回転ベクトル。
tvec	出力される3次元並進ベクトル。
use_extrinsic_guess	関数が rvec と tvec を初期変換の推定値として使用しなければならないことを示すフラグ。現時点ではサポートされていない。
num_iters	RANSAC の最大反復回数。
max_dist	点がインライアかどうかを判定するためのユークリッド距離のしきい値。
min_inlier_count	インライアの数が指定値以上に達した場合に関数を停止しなければならないことを示すフラグ。現時点ではサポートされていない。
inliers	インライアのインデックスを出力するベクトル。

◆ transformPoints()

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

#include <opencv2/cudalegacy.hpp>

変数詳解

◆ 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>

トピック

詳細説明

名前空間

クラス

マクロ定義

型定義

列挙型

関数

変数

マクロ定義詳解

◆ 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

型定義詳解

◆ Ncv16s

◆ Ncv16u

◆ Ncv32f

◆ Ncv32f_a

◆ Ncv32s

◆ Ncv32u

◆ Ncv32u_a

◆ Ncv64f

◆ Ncv64s

◆ Ncv64u

◆ Ncv8s

◆ Ncv8u

◆ NcvBool

◆ NCVDebugOutputHandler

◆ NCVStatus

◆ NcvTimer

列挙型詳解

◆ anonymous enum

◆ anonymous enum

◆ NCVMemoryType

関数詳解

◆ ~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()