@Namespace(value="cv") @Properties(inherit=opencv_features2d.class) public class SIFT extends Feature2D
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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SIFT(Algorithm pointer)
Downcast constructor.
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SIFT(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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static SIFT |
create() |
static SIFT |
create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
boolean enable_precise_upscale) |
static SIFT |
create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
int descriptorType) |
static SIFT |
create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
int descriptorType,
boolean enable_precise_upscale)
\brief Create SIFT with specified descriptorType.
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double |
getContrastThreshold() |
BytePointer |
getDefaultName()
Returns the algorithm string identifier.
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double |
getEdgeThreshold() |
int |
getNFeatures() |
int |
getNOctaveLayers() |
double |
getSigma() |
void |
setContrastThreshold(double contrastThreshold) |
void |
setEdgeThreshold(double edgeThreshold) |
void |
setNFeatures(int maxFeatures) |
void |
setNOctaveLayers(int nOctaveLayers) |
void |
setSigma(double sigma) |
asAlgorithm, asAlgorithm, compute, compute, compute, compute, compute, compute, defaultNorm, descriptorSize, descriptorType, detect, detect, detect, detect, detect, detect, detect, detect, detect, detect, detect, detect, detectAndCompute, detectAndCompute, detectAndCompute, detectAndCompute, detectAndCompute, detectAndCompute, empty, getPointer, position, read, read, read, write, write, write, write, write
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public SIFT(Pointer p)
Pointer(Pointer)
.public SIFT(Algorithm pointer)
@opencv_core.Ptr public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, @Cast(value="bool") boolean enable_precise_upscale)
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.
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.@opencv_core.Ptr public static SIFT create()
@opencv_core.Ptr public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, @Cast(value="bool") boolean enable_precise_upscale)
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.
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.@opencv_core.Ptr public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
@opencv_core.Str public BytePointer getDefaultName()
Algorithm
getDefaultName
in class Feature2D
public void setNFeatures(int maxFeatures)
public int getNFeatures()
public void setNOctaveLayers(int nOctaveLayers)
public int getNOctaveLayers()
public void setContrastThreshold(double contrastThreshold)
public double getContrastThreshold()
public void setEdgeThreshold(double edgeThreshold)
public double getEdgeThreshold()
public void setSigma(double sigma)
public double getSigma()
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