| Package | Description |
|---|---|
| org.openimaj.image.processing.face.feature.ltp |
An implementation of the local texture features and comparison measure
defined by Xiaoyang Tan and Bill Triggs.
|
| Modifier and Type | Class and Description |
|---|---|
class |
CLM
Constrained Local Model
|
class |
Tracker
The initial ported version of the CLMTracker that can only track a single
face in an image.
|
| Modifier and Type | Class and Description |
|---|---|
class |
OpenIMAJ
Useful utility methods to get things such as the current OpenIMAJ version.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MusicSpeechDataset
OpenIMAJ Dataset for the MusicSpeech Database
|
| Modifier and Type | Method and Description |
|---|---|
static Set<Reference> |
ReferenceListener.getReferences()
Get a copy of the references collected by the listener
|
static Set<Reference> |
ReferenceListener.reset()
Reset the references held by the listener, returning the current set of
references.
|
| Modifier and Type | Method and Description |
|---|---|
static void |
ReferenceListener.addReference(Reference r)
Register the given
Reference |
| Modifier and Type | Method and Description |
|---|---|
static void |
ReferenceListener.addReferences(Collection<Reference> refs)
Register the given
References |
| Modifier and Type | Method and Description |
|---|---|
Reference |
MockReference.asReference() |
static Reference |
MockReference.makeReference(org.jbibtex.BibTeXEntry entry)
Make a
Reference from a BibTeXEntry. |
| Modifier and Type | Method and Description |
|---|---|
abstract String |
StandardFormatters.format(Reference ref) |
String |
ReferenceFormatter.format(Reference ref)
Format a single reference
|
| Modifier and Type | Method and Description |
|---|---|
String |
StandardFormatters.format(Collection<Reference> refs) |
String |
ReferenceFormatter.format(Collection<Reference> refs)
Format a multiples references
|
protected abstract String |
StandardFormatters.formatRefs(Iterable<Reference> refs) |
| Modifier and Type | Class and Description |
|---|---|
class |
BasicDuplicateImageDatabase<T>
An in-memory image duplicate database.
|
| Modifier and Type | Method and Description |
|---|---|
Set<Reference> |
ExperimentContext.getBibliography()
Get the bibliography for the experiment.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ByteEntropyFilter
Filter
LocalFeatures typed on ByteFV by rejecting those that
have a low feature entropy. |
| Modifier and Type | Class and Description |
|---|---|
class |
CIFAR100Dataset
CIFAR-100 Dataset.
|
class |
CIFAR10Dataset
CIFAR-10 Dataset.
|
class |
MMSys2013
A wrapper dataset for the MMSys2013 Fashion-Focussed Creative Commons social
dataset (Loni, et.al).
|
| Modifier and Type | Class and Description |
|---|---|
class |
CameraCalibrationZhang
Implementation of Zhengyou Zhang's camera calibration routine using a planar
calibration pattern.
|
| Modifier and Type | Class and Description |
|---|---|
class |
SuzukiContourProcessor
Given a binary image (1-connected and 0-connected regions) detect contours
and provide both the contours and a hierarchy of contour membership.
|
class |
SuzukiNeighborStrategy
The neighbourhood border/contour tracing algorithm described in Appendix 1 of
the Suzuki contour detection algorithm
|
| Modifier and Type | Class and Description |
|---|---|
class |
BasicLocalBinaryPattern
Implementation of the original 3x3 form of a local binary pattern.
|
class |
ExtendedLocalBinaryPattern
Implementation of an extended local binary pattern which has a
variable number of samples taken from a variable sized circle
about a point.
|
class |
LocalTernaryPattern
Implementation of a Local Ternary Pattern.
|
class |
LocalUniformBinaryPatternHistogram
Class for extracting histograms of Local Uniform Binary Patterns.
|
class |
UniformBinaryPattern
Class for determining whether specific binary patterns are "uniform".
|
| Modifier and Type | Class and Description |
|---|---|
class |
HOG
Implementation of an extractor for the Histogram of Oriented Gradients (HOG)
feature for object detection.
|
class |
PHOG
This class is an implementation of an extractor for the PHOG (Pyramid
Histograms of Orientation Gradients) feature described by Bosch et al.
|
| Modifier and Type | Class and Description |
|---|---|
class |
FixedHOGStrategy
Implementation of an
SpatialBinningStrategy that extracts normalised
HOG features in the style defined by Dalal and Triggs. |
| Modifier and Type | Class and Description |
|---|---|
class |
Colorfulness
Implementation of Hasler and Susstruck's Colorfulness metric
http://infoscience.epfl.ch/record/33994/files/HaslerS03.pdf?version=1
|
static class |
Colorfulness.ColorfulnessAttr
Classes of colourfulness
|
class |
ColourContrast
Implementation of a color contrast feature.
|
class |
Gist<IMAGE extends Image<?,IMAGE> & SinglebandImageProcessor.Processable<Float,FImage,IMAGE>>
Implementation of the "Gist" spatial envelope feature.
|
class |
LRIntensityBalance
Implementation of the intensity balance algorithm described by Yeh et al.
|
class |
LuoSimplicity
Estimate the simplicity of an image by looking at the colour distribution of
the background using the algorithm defined by Yiwen Luo and Xiaoou Tang.
|
class |
Naturalness
Implementation of the Naturalness index (CNI) defined by Huang, Qiao & Wu.
|
class |
RGBRMSContrast
Implementation of the RGB RMS contrast feature.
|
class |
RMSContrast
Implementation of the RMS contrast feature.
|
class |
ROIProportion
Implementation of the region of interest based image simplicity measure
described by Yeh et al.
|
class |
RuleOfThirds
Implementation of the rule-of-thirds algorithm described by Yeh et al.
|
class |
Saturation
Estimate the saturation of an image using the RGB approximation of
avg(max(R,G,B) - min(R,G,B)).
|
class |
SaturationVariation
Estimate the variation in saturation of an image using the RGB approximation
of avg(max(R,G,B) - min(R,G,B)).
|
class |
Sharpness
Sharpness measures the clarity and level of detail of an image.
|
class |
SharpnessVariation
Sharpness measures the clarity and level of detail of an image.
|
class |
WeberContrast
Implementation of the Weber contrast feature.
|
class |
YehBokehEstimator
Implementation of the Bokeh estimation feature described by Yeh et al.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AffineSimulationExtractor<Q extends List<T>,T extends ScaleSpacePoint,I extends Image<P,I> & SinglebandImageProcessor.Processable<Float,FImage,I>,P>
Base class for local feature detectors/extractors that use affine simulations
in order to increase detections and improve performance with respect to
affine change.
|
class |
ASIFT<I extends Image<P,I> & SinglebandImageProcessor.Processable<Float,FImage,I>,P>
Abstract base implementation of Affine-simulated SIFT (ASIFT).
|
| Modifier and Type | Class and Description |
|---|---|
class |
VLAD<T>
Implementation of VLAD, the "Vector of Locally Aggregated Descriptors"
algorithm.
|
| Modifier and Type | Class and Description |
|---|---|
class |
IrregularBinningSIFTFeatureProvider
Irregular binning SIFT descriptor based on this paper:
CuiHasThoSei09igSIFT.pdf
|
| Modifier and Type | Class and Description |
|---|---|
class |
MSERDetector
Takes a merge tree from the watershed algorithm and detects MSERs.
|
class |
MSERFeatureGenerator
Detector for MSER features.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MinMaxDoGSIFTEngine
A modified implementation of Lowe's difference-of-Gaussian detector and SIFT
feature extraction technique that also records whether features are detected
at local minima or maxima by looking at the sign of the difference of
Gaussian.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ASIFTEngine
An
Engine for ASIFT. |
| Modifier and Type | Class and Description |
|---|---|
class |
EigenImages
Implementation of EigenImages.
|
class |
FisherImages
Implementation of Fisher Images (aka "FisherFaces").
|
| Modifier and Type | Class and Description |
|---|---|
class |
IMMFaceDatabase
The IMM Face Database (a set of labelled faces with connected points).
|
| Modifier and Type | Class and Description |
|---|---|
class |
Detector
Basic, single-threaded multi-scale Haar cascade/tree object detector.
|
class |
HaarFeature
Class describing a Haar-like feature.
|
class |
HaarFeatureClassifier
A classifier based on a Haar-like feature.
|
class |
Stage
A classification stage.
|
class |
StageTreeClassifier
A tree of classifier stages.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AnisotropicDiffusion
Implementation of Perona & Malik's image filtering by anisotropic
diffusion.
|
class |
MaskedRobustContrastEqualisation
An image processor that performs contrast equalisation
in a robust manner with a mask.
|
| Modifier and Type | Class and Description |
|---|---|
class |
FFastGaussianConvolve
Fast approximate Gaussian smoothing using repeated fast box filtering.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LawsTexture
Implementation of Laws texture energy measures, based on the description in
Shapiro and Stockman Section 7.3.4.
|
class |
LawsTextureBase
Base
FilterBank that provides the 16 raw kernels used in Laws texture
classification approach. |
| Modifier and Type | Class and Description |
|---|---|
class |
StrokeWidthTransform
Implementation of the Stroke Width Transform.
|
class |
SUSANEdgeDetector
Implementations of the SUSAN edge detection algorithm.
|
| Modifier and Type | Class and Description |
|---|---|
class |
CLMDetectedFace
A constrained local model detected face.
|
class |
CLMFaceDetector
Face detector based on a constrained local model.
|
class |
HaarCascadeDetector
A face detector based on a Haar cascade.
|
class |
SandeepFaceDetector
Implementation of a face detector along the lines of "Human Face Detection in
Cluttered Color Images Using Skin Color and Edge Information" K.
|
| Modifier and Type | Class and Description |
|---|---|
class |
FacialKeypointExtractor
A class capable of finding likely facial keypoints using
a masked Haar cascade for each keypoint, and then picking
the best combination of points based on a model.
|
class |
FKEFaceDetector
F(rontal)K(eypoint)E(nriched)FaceDetector uses an underlying face detector to
detect frontal faces in an image, and then looks for facial keypoints within
the detections.
|
| Modifier and Type | Class and Description |
|---|---|
class |
EigenFaceFeature
A
FacialFeature for EigenFaces. |
class |
FisherFaceFeature
A
FacialFeature for FisherFaces. |
| Modifier and Type | Class and Description |
|---|---|
class |
DoGSIFTFeatureComparator
A
FacialFeatureComparator for comparing DoGSIFTFeatures. |
class |
LtpDtFeatureComparator
A comparator for Local Trinary Pattern Features using a
Euclidean distance transform.
|
class |
ReversedLtpDtFeatureComparator
A comparator for Local Trinary Pattern Features using a
Euclidean distance transform.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractLtpDtFeature
Base class for LTP based features using a
truncated Euclidean distance transform
to estimate the distances within each slice.
|
class |
GaussianWeighting
A Gaussian
LTPWeighting function. |
class |
LtpDtFeature
The LTP based feature using a truncated Euclidean distance transform
to estimate the distances within each slice.
|
interface |
LTPWeighting |
class |
TruncatedWeighting
A truncated weighting scheme which cuts-off distances
beyond a threshold.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ATandTDataset
A Dataset for Our Database of Faces/The ORL Face Database/The AT&T Face
database.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ResizeProcessor
Image processor and utility methods that can resize images.
|
| Modifier and Type | Class and Description |
|---|---|
class |
BlackmanFilter
Blackman window function interpolation filter for the resample function
|
class |
HammingFilter
Hamming window function interpolation filter for the resample function
|
class |
HanningFilter
Hanning window function interpolation filter for the resample function
|
| Modifier and Type | Class and Description |
|---|---|
class |
TeleaInpainting<IMAGE extends Image<?,IMAGE> & SinglebandImageProcessor.Processable<Float,FImage,IMAGE>>
Implementation of Alexandru Telea's FMM-based inpainting algorithm.
|
| Modifier and Type | Class and Description |
|---|---|
class |
OtsuThreshold
Otsu's adaptive thresholding algorithm.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AffineParams
Parameters defining an affine simulation, in terms of a tilt and rotation.
|
class |
AffineSimulation<I extends Image<P,I> & SinglebandImageProcessor.Processable<Float,FImage,I>,P>
Utility methods to simulate affine transformations defined by a rotation and
tilt, or series of rotations and tilts.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AchantaSaliency
Implementation of the saliency map algorithm described in:
R.
|
class |
DepthOfFieldEstimator
Construct a map that shows the "focus" of each pixel.
|
class |
LuoTangSubjectRegion
Extract the subject region of an image based on the
part that is least blurred (most in-focus).
|
class |
YehSaliency
Implementation of the region-based saliency algorithm described in:
Che-Hua Yeh, Yuan-Chen Ho, Brian A.
|
| Modifier and Type | Class and Description |
|---|---|
class |
FelzenszwalbHuttenlocherSegmenter<I extends Image<?,I> & SinglebandImageProcessor.Processable<Float,FImage,I>>
Implementation of the segmentation algorithm described in:
Efficient Graph-Based Image Segmentation
Pedro F.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LiuSamarabanduTextExtractorBasic
A processor that attempts to extract text from an image.
|
class |
LiuSamarabanduTextExtractorMultiscale
An implementation of the multiscale text extractor from
MULTISCALE EDGE-BASED TEXT EXTRACTION FROM COMPLEX IMAGES;
Xiaoqing Liu and Jagath Samarabandu
The University of Western Ontario
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4036951.
|
| Modifier and Type | Class and Description |
|---|---|
class |
SWTTextDetector
Implementation of the Stroke Width Transform text detection algorithm by
Epshtein et al.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ByteNearestNeighboursKDTree
Fast Nearest-Neighbours for byte data using an ensemble of Best-Bin-First KDTrees.
|
class |
DoubleNearestNeighboursKDTree
Fast Nearest-Neighbours for double data using an ensemble of Best-Bin-First KDTrees.
|
class |
FloatNearestNeighboursKDTree
Fast Nearest-Neighbours for float data using an ensemble of Best-Bin-First KDTrees.
|
class |
IntNearestNeighboursKDTree
Fast Nearest-Neighbours for int data using an ensemble of Best-Bin-First KDTrees.
|
class |
LongNearestNeighboursKDTree
Fast Nearest-Neighbours for long data using an ensemble of Best-Bin-First KDTrees.
|
class |
ShortNearestNeighboursKDTree
Fast Nearest-Neighbours for short data using an ensemble of Best-Bin-First KDTrees.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ByteADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
ByteProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of bytes.
|
class |
ByteSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
class |
DoubleADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
DoubleProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of doubles.
|
class |
DoubleSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
class |
FloatADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
FloatProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of floats.
|
class |
FloatSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
class |
IncrementalByteADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IncrementalDoubleADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IncrementalFloatADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IncrementalIntADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IncrementalLongADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IncrementalShortADCNearestNeighbours
Incremental Nearest-neighbours using Asymmetric Distance Computation (ADC)
on Product Quantised vectors.
|
class |
IntADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
IntProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of ints.
|
class |
IntSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
class |
LongADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
LongProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of longs.
|
class |
LongSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
class |
ShortADCNearestNeighbours
Nearest-neighbours using Asymmetric Distance Computation (ADC) on Product
Quantised vectors.
|
class |
ShortProductQuantiser
Implementation of a Product Quantiser for vectors/arrays of shorts.
|
class |
ShortSDCNearestNeighbours
Nearest-neighbours using Symmetric Distance Computation (SDC) on Product
Quantised vectors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ByteHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
ByteHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
ByteHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
BytePStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
class |
DoubleHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
DoubleHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
DoubleHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
DoublePStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
class |
FloatHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
FloatHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
FloatHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
FloatPStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
class |
IntHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
IntHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
IntHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
IntPStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
class |
LongHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
LongHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
LongHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
LongPStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
class |
ShortHammingFactory
A hash function factory for producing hash functions that approximate the
Hamming distance.
|
class |
ShortHyperplaneCosineFactory
A hash function factory that produces hash functions that approximate cosine
distance using hyperplanes.
|
class |
ShortHyperplaneL1Factory
A hash function factory that produces hash functions that approximate L1
(city-block) distance in closed spaces using random axis-aligned hyperplanes.
|
class |
ShortPStableFactory
Base class for hashing schemes based on P-Stable distributions.
|
| Modifier and Type | Method and Description |
|---|---|
double[] |
Polygon.calculateFirstMoment()
Treating the polygon as a continuous piecewise function, calculate
exactly the first moment.
|
double[] |
Polygon.calculateSecondMoment()
Treating the polygon as a continuous piecewise function, calculate
exactly the second moment.
|
double[] |
Polygon.calculateSecondMomentCentralised()
Treating the polygon as a continuous piecewise function, calculate
exactly the centralised second moment.
|
| Modifier and Type | Class and Description |
|---|---|
class |
HomographyRefinement
Refinement of homographies estimates using non-linear optimisation
(Levenberg-Marquardt) under different geometric distance/error assumptions.
|
| Modifier and Type | Method and Description |
|---|---|
static Jama.Matrix |
TransformUtilities.affineMatrixND(double[][] q,
double[][] p)
Find the affine transform between pairs of matching points in
n-dimensional space.
|
static Jama.Matrix |
TransformUtilities.affineMatrixND(List<? extends IndependentPair<? extends Coordinate,? extends Coordinate>> data)
Find the affine transform between pairs of matching points in
n-dimensional space.
|
static Jama.Matrix |
TransformUtilities.rigidMatrix(double[][] q,
double[][] p)
Compute the least-squares rigid alignment between two sets of matching
points in N-dimensional space.
|
static Jama.Matrix |
TransformUtilities.rigidMatrix(List<? extends IndependentPair<? extends Coordinate,? extends Coordinate>> data)
Compute the least-squares rigid alignment between two sets of matching
points in N-dimensional space.
|
| Modifier and Type | Class and Description |
|---|---|
class |
BucketingSampler2d
Implementation of the bucketing sampling strategy proposed by Zhang et al to
try and ensure a good spatial distribution of point-pairs for estimation of
geometric transforms and the fundamental matrix.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LinearDiscriminantAnalysis
Implementation of Multiclass Linear Discriminant Analysis.
|
| Modifier and Type | Class and Description |
|---|---|
class |
PCAWhitening
Whitening based on PCA.
|
class |
WhiteningTransform
Abstract base class for whitening transforms ("sphering").
|
class |
ZCAWhitening
The ZCA Whitening transform.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LMedS<I,D,M extends EstimatableModel<I,D>>
Least Median of Squares robust model fitting
|
| Modifier and Type | Class and Description |
|---|---|
class |
DenseLinearTransformAnnotator<OBJECT,ANNOTATION>
An annotator that determines a "transform" between feature vectors and
vectors of annotation counts.
|
class |
LiblinearAnnotator<OBJECT,ANNOTATION>
Annotator based on linear classifiers learned using Liblinear (see
Linear) or DenseLinear depending on the density of the
features. |
| Modifier and Type | Class and Description |
|---|---|
class |
ConstrainedFloatAssigner<DATATYPE>
An assigner that wraps another hard assigner and only produces valid
assignments if the closest cluster is within (or outside) of a given
threshold distance.
|
| Modifier and Type | Class and Description |
|---|---|
class |
HierarchicalByteKMeans
Hierarchical Byte K-Means clustering (
HierarchicalByteKMeans) is a simple
hierarchical version of ByteKMeans. |
class |
HierarchicalDoubleKMeans
Hierarchical Double K-Means clustering (
HierarchicalDoubleKMeans) is a simple
hierarchical version of DoubleKMeans. |
class |
HierarchicalFloatKMeans
Hierarchical Float K-Means clustering (
HierarchicalFloatKMeans) is a simple
hierarchical version of FloatKMeans. |
class |
HierarchicalIntKMeans
Hierarchical Integer K-Means clustering (
HierarchicalIntKMeans) is a simple
hierarchical version of IntKMeans. |
class |
HierarchicalLongKMeans
Hierarchical Long K-Means clustering (
HierarchicalLongKMeans) is a simple
hierarchical version of LongKMeans. |
class |
HierarchicalShortKMeans
Hierarchical Short K-Means clustering (
HierarchicalShortKMeans) is a simple
hierarchical version of ShortKMeans. |
| Modifier and Type | Class and Description |
|---|---|
class |
IntRAC
An implementation of the RAC algorithm proposed by Ramanan and Niranjan.
|
| Modifier and Type | Class and Description |
|---|---|
class |
IntRandomForest
An implementation of the RandomForest clustering algorithm proposed by Jurie et al.
|
| Modifier and Type | Class and Description |
|---|---|
class |
DoubleMultiviewSpectralClustering |
| Modifier and Type | Class and Description |
|---|---|
class |
BilinearUnmixedSparseOnlineLearner
An implementation of a stochastic gradient decent with proximal parameter
adjustment (for regularised parameters).
|
| Modifier and Type | Class and Description |
|---|---|
class |
LanguageDetector
Short text language detection ported from langid:
https://github.com/saffsd/langid.py
|
| Modifier and Type | Class and Description |
|---|---|
class |
MPQAToken
An implementation of the Prior-Polarity baseline sentiment classifier described by Wilson et.
|
class |
MPQATokenList
An implementation of the Prior-Polarity baseline sentiment classifier described by Wilson et.
|
| Modifier and Type | Class and Description |
|---|---|
class |
TFF
The TFF data format is the word clue format used by OpinionFinder.
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| Modifier and Type | Class and Description |
|---|---|
class |
LocalHistogramVideoShotDetector
A shot detector implementing the Steiner et al.
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| Modifier and Type | Class and Description |
|---|---|
class |
EfrosLeungInpainter<IMAGE extends Image<?,IMAGE> & SinglebandImageProcessor.Processable<Float,FImage,IMAGE>>
FIXME: Finish implementation (it works but is incredibly slow!)
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