Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] . More...

Inheritance diagram for OpenCVForUnity.Features2dModule.SIFT:

Public Member Functions
override string	getDefaultName ()

void	setNFeatures (int maxFeatures)

int	getNFeatures ()

void	setNOctaveLayers (int nOctaveLayers)

int	getNOctaveLayers ()

void	setContrastThreshold (double contrastThreshold)

double	getContrastThreshold ()

void	setEdgeThreshold (double edgeThreshold)

double	getEdgeThreshold ()

void	setSigma (double sigma)

double	getSigma ()

Public Member Functions inherited from OpenCVForUnity.Features2dModule.Feature2D
void	detect (Mat image, MatOfKeyPoint keypoints, Mat mask)
	Detects keypoints in an image (first variant) or image set (second variant). More...

void	detect (Mat image, MatOfKeyPoint keypoints)
	Detects keypoints in an image (first variant) or image set (second variant). More...

void	detect (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > masks)

void	detect (List< Mat > images, List< MatOfKeyPoint > keypoints)

void	compute (Mat image, MatOfKeyPoint keypoints, Mat descriptors)
	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...

void	compute (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > descriptors)

void	detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors, bool useProvidedKeypoints)

void	detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors)

int	descriptorSize ()

int	descriptorType ()

int	defaultNorm ()

void	write (string fileName)

void	read (string fileName)

override bool	empty ()
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...

Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
IntPtr	getNativeObjAddr ()

virtual void	clear ()
	Clears the algorithm state. More...

void	save (string filename)

Public Member Functions inherited from OpenCVForUnity.DisposableObject
void	Dispose ()

void	ThrowIfDisposed ()

Static Public Member Functions
static new SIFT	__fromPtr__ (IntPtr addr)

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, bool enable_precise_upscale)

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma)

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold)

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold)

static SIFT	create (int nfeatures, int nOctaveLayers)

static SIFT	create (int nfeatures)

static SIFT	create ()

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, bool enable_precise_upscale)
	Create SIFT with specified descriptorType. More...

static SIFT	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
	Create SIFT with specified descriptorType. More...

Static Public Member Functions inherited from OpenCVForUnity.Features2dModule.Feature2D
static new Feature2D	__fromPtr__ (IntPtr addr)

Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm	__fromPtr__ (IntPtr addr)

Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr	ThrowIfNullIntPtr (IntPtr ptr)

Protected Member Functions
override void	Dispose (bool disposing)

Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()

	DisposableOpenCVObject (IntPtr ptr)

	DisposableOpenCVObject (bool isEnabledDispose)

	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)

Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()

	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed `[get, protected set]`

bool	IsEnabledDispose `[get, set]`

Detailed Description

Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] .

Member Function Documentation

◆ fromPtr()

static new SIFT OpenCVForUnity.Features2dModule.SIFT.__fromPtr__ ( IntPtr addr )

static

◆ create() [1/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold,
		double	edgeThreshold,
		double	sigma,
		bool	enable_precise_upscale
	)

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [2/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold,
		double	edgeThreshold,
		double	sigma
	)

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [3/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold,
		double	edgeThreshold
	)

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [4/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold
	)

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [5/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers
	)

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [6/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create ( int nfeatures )

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [7/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create ( )

static

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [8/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold,
		double	edgeThreshold,
		double	sigma,
		int	descriptorType,
		bool	enable_precise_upscale
	)

static

Create SIFT with specified descriptorType.

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
descriptorType	The type of descriptors. Only CV_32F and CV_8U are supported.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ create() [9/9]

static SIFT OpenCVForUnity.Features2dModule.SIFT.create	(	int	nfeatures,
		int	nOctaveLayers,
		double	contrastThreshold,
		double	edgeThreshold,
		double	sigma,
		int	descriptorType
	)

static

Create SIFT with specified descriptorType.

Parameters

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

Parameters

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
descriptorType	The type of descriptors. Only CV_32F and CV_8U are supported.
enable_precise_upscale	Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default.

◆ Dispose()

override void OpenCVForUnity.Features2dModule.SIFT.Dispose ( bool disposing )

protectedvirtual

Reimplemented from OpenCVForUnity.Features2dModule.Feature2D.

◆ getContrastThreshold()

double OpenCVForUnity.Features2dModule.SIFT.getContrastThreshold ( )

◆ getDefaultName()

override string OpenCVForUnity.Features2dModule.SIFT.getDefaultName ( )

virtual

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

Reimplemented from OpenCVForUnity.Features2dModule.Feature2D.

◆ getEdgeThreshold()

double OpenCVForUnity.Features2dModule.SIFT.getEdgeThreshold ( )

◆ getNFeatures()

int OpenCVForUnity.Features2dModule.SIFT.getNFeatures ( )

◆ getNOctaveLayers()

int OpenCVForUnity.Features2dModule.SIFT.getNOctaveLayers ( )

◆ getSigma()

double OpenCVForUnity.Features2dModule.SIFT.getSigma ( )

◆ setContrastThreshold()

void OpenCVForUnity.Features2dModule.SIFT.setContrastThreshold ( double contrastThreshold )

◆ setEdgeThreshold()

void OpenCVForUnity.Features2dModule.SIFT.setEdgeThreshold ( double edgeThreshold )

◆ setNFeatures()

void OpenCVForUnity.Features2dModule.SIFT.setNFeatures ( int maxFeatures )

◆ setNOctaveLayers()

void OpenCVForUnity.Features2dModule.SIFT.setNOctaveLayers ( int nOctaveLayers )

◆ setSigma()

void OpenCVForUnity.Features2dModule.SIFT.setSigma ( double sigma )

The documentation for this class was generated from the following file:

OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/features2d/SIFT.cs

Public Member Functions

Static Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ __fromPtr__()

◆ create() [1/9]

◆ create() [2/9]

◆ create() [3/9]

◆ create() [4/9]

◆ create() [5/9]

◆ create() [6/9]

◆ create() [7/9]

◆ create() [8/9]

◆ create() [9/9]

◆ Dispose()

◆ getContrastThreshold()

◆ getDefaultName()

◆ getEdgeThreshold()

◆ getNFeatures()

◆ getNOctaveLayers()

◆ getSigma()

◆ setContrastThreshold()

◆ setEdgeThreshold()

◆ setNFeatures()

◆ setNOctaveLayers()

◆ setSigma()

◆ fromPtr()