Uses of Interface
org.openimaj.data.dataset.GroupedDataset

Packages that use GroupedDataset

Package	Description
org.openimaj.audio.analysis.benchmarking.dataset
org.openimaj.data.dataset
org.openimaj.data.dataset.cache
org.openimaj.experiment.dataset.cluster
org.openimaj.experiment.dataset.sampling	The sampling package deals with sampling datasets to produce smaller datasets.
org.openimaj.experiment.dataset.split	Interfaces describing objects which can provide different splits of a dataset.
org.openimaj.experiment.dataset.util
org.openimaj.experiment.evaluation.classification
org.openimaj.experiment.gmm.retrieval
org.openimaj.experiment.validation
org.openimaj.experiment.validation.cross
org.openimaj.feature
org.openimaj.image.annotation.evaluation.datasets
org.openimaj.image.model
org.openimaj.image.objectdetection.datasets
org.openimaj.image.processing.face.detection	The detection package contains implementations of face detectors.
org.openimaj.image.processing.face.feature	The feature package contains implementations of features that can describe a face.
org.openimaj.image.processing.face.recognition
org.openimaj.image.processing.face.recognition.benchmarking
org.openimaj.image.processing.face.recognition.benchmarking.dataset
org.openimaj.ml.annotation
org.openimaj.ml.annotation.linear
org.openimaj.ml.dataset

Uses of GroupedDataset in org.openimaj.audio.analysis.benchmarking.dataset

Classes in org.openimaj.audio.analysis.benchmarking.dataset that implement GroupedDataset

Modifier and Type	Class and Description
class	MusicSpeechDataset OpenIMAJ Dataset for the MusicSpeech Database

Uses of GroupedDataset in org.openimaj.data.dataset

Classes in org.openimaj.data.dataset that implement GroupedDataset

Modifier and Type	Class and Description
class	MapBackedDataset<KEY,DATASET extends Dataset<INSTANCE>,INSTANCE> A MapBackedDataset is a concrete implementation of a GroupedDataset backed by a Map.
class	ReadableGroupDataset<KEY,DATASET extends Dataset<INSTANCE>,INSTANCE,SOURCE> Base class for GroupedDatasets in which each instance is read with an InputStreamObjectReader.
class	VFSGroupDataset<INSTANCE> A GroupedDataset of VFSListDatasets backed by directories of items (either locally or remotely), or items stored in a hierarchical structure within a compressed archive.

Uses of GroupedDataset in org.openimaj.data.dataset.cache

Methods in org.openimaj.data.dataset.cache that return GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<KEY,ListDataset<OBJECT>,OBJECT>	GroupedListCache.getDataset()
GroupedDataset<KEY,ListDataset<OBJECT>,OBJECT>	InMemoryGroupedListCache.getDataset()

Uses of GroupedDataset in org.openimaj.experiment.dataset.cluster

Classes in org.openimaj.experiment.dataset.cluster that implement GroupedDataset

Modifier and Type	Class and Description
class	ClusterEvalDataset Reads datasets of items and cluster labels from the clustereval tool: http://chris.de-vries.id.au/2013/06/clustereval-10-release.html The general format of clustereval is: item cluster_label*

Uses of GroupedDataset in org.openimaj.experiment.dataset.sampling

Methods in org.openimaj.experiment.dataset.sampling that return GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	NamedGroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	NamedGroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, Collection<KEY> keys) Sample a dataset by selecting only the given group keys.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, double percentage) Sample a dataset with the given percentage of instances to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, double percentage, boolean withReplacement) Sample a dataset with the given percentage of instances to select, using with with-replacement or without-replacement sampling.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int number) Sample a dataset with the given number of instances to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int numGroups, boolean random) Sample a dataset with the given number of groups to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int number, boolean withReplacement) Sample a dataset with the given number of instances to select, using with with-replacement or without-replacement sampling.
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	StratifiedGroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset)

Methods in org.openimaj.experiment.dataset.sampling with parameters of type GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	NamedGroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset)
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	NamedGroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, Collection<KEY> keys) Sample a dataset by selecting only the given group keys.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, double percentage) Sample a dataset with the given percentage of instances to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, double percentage, boolean withReplacement) Sample a dataset with the given percentage of instances to select, using with with-replacement or without-replacement sampling.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int number) Sample a dataset with the given number of instances to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int numGroups, boolean random) Sample a dataset with the given number of groups to select.
static <KEY,INSTANCE> GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int number, boolean withReplacement) Sample a dataset with the given number of instances to select, using with with-replacement or without-replacement sampling.
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	StratifiedGroupedUniformRandomisedSampler.sample(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset)

Uses of GroupedDataset in org.openimaj.experiment.dataset.split

Methods in org.openimaj.experiment.dataset.split that return GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getTestDataset()
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getTrainingDataset()
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getValidationDataset()

Methods in org.openimaj.experiment.dataset.split that return types with arguments of type GroupedDataset

Modifier and Type	Method and Description
static <KEY,INSTANCE> CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedRandomSplitter.createCrossValidationData(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int numTraining, int numValidation, int numIterations) Create a CrossValidationIterable from the dataset.

Methods in org.openimaj.experiment.dataset.split with parameters of type GroupedDataset

Modifier and Type	Method and Description
static <KEY,INSTANCE> CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedRandomSplitter.createCrossValidationData(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int numTraining, int numValidation, int numIterations) Create a CrossValidationIterable from the dataset.

Constructors in org.openimaj.experiment.dataset.split with parameters of type GroupedDataset

Constructor and Description
GroupedRandomSplitter(GroupedDataset<KEY,? extends ListDataset<INSTANCE>,INSTANCE> dataset, int numTraining, int numValidation, int numTesting) Construct the dataset splitter with the given target instance sizes for each group of the training, validation and testing data.

Uses of GroupedDataset in org.openimaj.experiment.dataset.util

Methods in org.openimaj.experiment.dataset.util that return GroupedDataset

Modifier and Type	Method and Description
static <ANN,INSTANCE> GroupedDataset<ANN,ListDataset<INSTANCE>,INSTANCE>	DatasetAdaptors.flattenListGroupedDataset(GroupedDataset<ANN,? extends ListDataset<List<INSTANCE>>,? extends List<INSTANCE>> dataset) if you have a grouped dataset where the groups contains lists of feature objects (i.e.
static <ANN,DATASET extends Dataset<INSTANCE>,INSTANCE> GroupedDataset<ANN,DATASET,INSTANCE>	DatasetAdaptors.getGroupedDatasetSubset(GroupedDataset<ANN,DATASET,INSTANCE> data, ANN... groups) Takes a grouped dataset and returns a new dataset that contains only those groups specified.
static <ANN,DATASET extends ListDataset<INSTANCE>,INSTANCE> GroupedDataset<ANN,ListBackedDataset<INSTANCE>,INSTANCE>	DatasetAdaptors.getRegroupedDataset(GroupedDataset<ANN,DATASET,INSTANCE> data, Map<ANN,ANN[]> regroupCriteria) Takes a grouped dataset and returns a new dataset with the groups re-shuffled as specified in the regrouping criteria.

Methods in org.openimaj.experiment.dataset.util with parameters of type GroupedDataset

Modifier and Type	Method and Description
static <ANN,INSTANCE> GroupedDataset<ANN,ListDataset<INSTANCE>,INSTANCE>	DatasetAdaptors.flattenListGroupedDataset(GroupedDataset<ANN,? extends ListDataset<List<INSTANCE>>,? extends List<INSTANCE>> dataset) if you have a grouped dataset where the groups contains lists of feature objects (i.e.
static <ANN,DATASET extends Dataset<INSTANCE>,INSTANCE> GroupedDataset<ANN,DATASET,INSTANCE>	DatasetAdaptors.getGroupedDatasetSubset(GroupedDataset<ANN,DATASET,INSTANCE> data, ANN... groups) Takes a grouped dataset and returns a new dataset that contains only those groups specified.
static <ANN,DATASET extends ListDataset<INSTANCE>,INSTANCE> GroupedDataset<ANN,ListBackedDataset<INSTANCE>,INSTANCE>	DatasetAdaptors.getRegroupedDataset(GroupedDataset<ANN,DATASET,INSTANCE> data, Map<ANN,ANN[]> regroupCriteria) Takes a grouped dataset and returns a new dataset with the groups re-shuffled as specified in the regrouping criteria.

Uses of GroupedDataset in org.openimaj.experiment.evaluation.classification

Constructors in org.openimaj.experiment.evaluation.classification with parameters of type GroupedDataset

Constructor and Description
ClassificationEvaluator(Classifier<CLASS,OBJECT> classifier, GroupedDataset<CLASS,? extends ListDataset<OBJECT>,OBJECT> actual, ClassificationAnalyser<RESULT,CLASS,OBJECT> analyser) Construct a new ClassificationEvaluator with the given classifier, ground truth ("actual") data and an ClassificationAnalyser.

Uses of GroupedDataset in org.openimaj.experiment.gmm.retrieval

Classes in org.openimaj.experiment.gmm.retrieval that implement GroupedDataset

Modifier and Type	Class and Description
class	UKBenchGroupDataset<IMAGE> A GroupedDataset of UKBenchListDatasets instances each of an item in the UKBench experiment.

Uses of GroupedDataset in org.openimaj.experiment.validation

Constructors in org.openimaj.experiment.validation with parameters of type GroupedDataset

Constructor and Description
GroupedRandomisedPercentageHoldOut(double percentageTraining, GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset) Construct with the given dataset and percentage of training data (0..1).
StratifiedGroupedRandomisedPercentageHoldOut(double percentageTraining, GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset) Construct with the given dataset and percentage of training data (0..1).

Uses of GroupedDataset in org.openimaj.experiment.validation.cross

Methods in org.openimaj.experiment.validation.cross that return types with arguments of type GroupedDataset

Modifier and Type	Method and Description
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedLeaveOneOut.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	StratifiedGroupedKFold.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedKFold.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)

Methods in org.openimaj.experiment.validation.cross with parameters of type GroupedDataset

Modifier and Type	Method and Description
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedLeaveOneOut.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	StratifiedGroupedKFold.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)
CrossValidationIterable<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>	GroupedKFold.createIterable(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> data)

Uses of GroupedDataset in org.openimaj.feature

Methods in org.openimaj.feature that return GroupedDataset

Modifier and Type	Method and Description
static <FEATURE,OBJECT,KEY> GroupedDataset<KEY,ListDataset<FEATURE>,FEATURE>	DatasetExtractors.createLazyFeatureDataset(GroupedDataset<KEY,? extends ListDataset<OBJECT>,OBJECT> input, FeatureExtractor<FEATURE,OBJECT> extractor) Create a GroupedDataset of keys to ListDataset of features from the given GroupedDataset of keys to ListDatasets of objects by extracting the features from the objects with the given feature extractor.

Methods in org.openimaj.feature with parameters of type GroupedDataset

Modifier and Type	Method and Description
static <FEATURE,OBJECT,KEY> GroupedDataset<KEY,ListDataset<FEATURE>,FEATURE>	DatasetExtractors.createLazyFeatureDataset(GroupedDataset<KEY,? extends ListDataset<OBJECT>,OBJECT> input, FeatureExtractor<FEATURE,OBJECT> extractor) Create a GroupedDataset of keys to ListDataset of features from the given GroupedDataset of keys to ListDatasets of objects by extracting the features from the objects with the given feature extractor.

Uses of GroupedDataset in org.openimaj.image.annotation.evaluation.datasets

Methods in org.openimaj.image.annotation.evaluation.datasets that return GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getExpertData() Returns the results from the expert turkers.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getGroundTruth() Returns the ground truth set.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getNonExpertData() Returns the results from the non-expert turkers.
static <IMAGE> GroupedDataset<String,ListDataset<IMAGE>,IMAGE>	CIFAR10Dataset.getTestImages(BinaryReader<IMAGE> reader) Load the test images using the given reader.
static <IMAGE> GroupedDataset<String,ListDataset<IMAGE>,IMAGE>	CIFAR100Dataset.getTestImages(BinaryReader<IMAGE> reader, boolean fineLabels) Load the test images using the given reader.
static <IMAGE> GroupedDataset<String,ListDataset<IMAGE>,IMAGE>	CIFAR10Dataset.getTrainingImages(BinaryReader<IMAGE> reader) Load the training images using the given reader.
static <IMAGE> GroupedDataset<String,ListDataset<IMAGE>,IMAGE>	CIFAR100Dataset.getTrainingImages(BinaryReader<IMAGE> reader, boolean fineLabels) Load the training images using the given reader.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.parseMetadata(File metadataFile)

Methods in org.openimaj.image.annotation.evaluation.datasets that return types with arguments of type GroupedDataset

Modifier and Type	Method and Description
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getExpertData() Returns the results from the expert turkers.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getGroundTruth() Returns the ground truth set.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.getNonExpertData() Returns the results from the non-expert turkers.
GroupedDataset<String,GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response>,MMSys2013.Response>	MMSys2013.parseMetadata(File metadataFile)

Methods in org.openimaj.image.annotation.evaluation.datasets with parameters of type GroupedDataset

Modifier and Type	Method and Description
static Map<String,List<ScoredAnnotation<MMSys2013.QuestionResponse>>>	MMSys2013.getAnnotationsQ1(GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response> data) For a given GroupedDataset that represents the results from a single category, returns a list of scored annotations for each group, for question 1 (contains depication of category).
static Map<String,List<ScoredAnnotation<MMSys2013.QuestionResponse>>>	MMSys2013.getAnnotationsQ2(GroupedDataset<String,ListDataset<MMSys2013.Response>,MMSys2013.Response> data) For a given GroupedDataset that represents the results from a single category, returns a list of scored annotations for each group, for question 2 (is in category).

Uses of GroupedDataset in org.openimaj.image.model

Methods in org.openimaj.image.model with parameters of type GroupedDataset

Modifier and Type	Method and Description
<KEY> void	FisherImages.train(GroupedDataset<KEY,? extends ListDataset<FImage>,FImage> data) Train on a grouped dataset.

Uses of GroupedDataset in org.openimaj.image.objectdetection.datasets

Methods in org.openimaj.image.objectdetection.datasets that return GroupedDataset

Modifier and Type	Method and Description
static GroupedDataset<Boolean,ListDataset<FImage>,FImage>	INRIAPersonDataset.getTrainingData()

Uses of GroupedDataset in org.openimaj.image.processing.face.detection

Methods in org.openimaj.image.processing.face.detection that return GroupedDataset

Modifier and Type	Method and Description
static <PERSON,IMAGE extends Image<?,IMAGE>,FACE extends DetectedFace> GroupedDataset<PERSON,ListDataset<FACE>,FACE>	DatasetFaceDetector.process(GroupedDataset<PERSON,? extends ListDataset<IMAGE>,IMAGE> input, FaceDetector<FACE,IMAGE> detector) Apply a face detector to all the images in the given dataset, choosing only the biggest face if multiple are found.

Methods in org.openimaj.image.processing.face.detection with parameters of type GroupedDataset

Modifier and Type	Method and Description
static <PERSON,IMAGE extends Image<?,IMAGE>,FACE extends DetectedFace> GroupedDataset<PERSON,ListDataset<FACE>,FACE>	DatasetFaceDetector.process(GroupedDataset<PERSON,? extends ListDataset<IMAGE>,IMAGE> input, FaceDetector<FACE,IMAGE> detector) Apply a face detector to all the images in the given dataset, choosing only the biggest face if multiple are found.

Uses of GroupedDataset in org.openimaj.image.processing.face.feature

Methods in org.openimaj.image.processing.face.feature with parameters of type GroupedDataset

Modifier and Type	Method and Description
<KEY> void	FisherFaceFeature.Extractor.train(GroupedDataset<KEY,? extends ListDataset<T>,T> data) Train on a grouped dataset.

Uses of GroupedDataset in org.openimaj.image.processing.face.recognition

Methods in org.openimaj.image.processing.face.recognition with parameters of type GroupedDataset

Modifier and Type	Method and Description
protected void	EigenFaceRecogniser.beforeBatchTrain(GroupedDataset<PERSON,ListDataset<FACE>,FACE> dataset)
protected void	FisherFaceRecogniser.beforeBatchTrain(GroupedDataset<PERSON,ListDataset<FACE>,FACE> dataset)
void	FaceRecognitionEngine.train(GroupedDataset<PERSON,ListDataset<FImage>,FImage> dataset) Train with a dataset

Uses of GroupedDataset in org.openimaj.image.processing.face.recognition.benchmarking

Fields in org.openimaj.image.processing.face.recognition.benchmarking declared as GroupedDataset

Modifier and Type	Field and Description
protected GroupedDataset<PERSON,? extends ListDataset<IMAGE>,IMAGE>	CrossValidationBenchmark.dataset

Fields in org.openimaj.image.processing.face.recognition.benchmarking with type parameters of type GroupedDataset

Modifier and Type	Field and Description
protected CrossValidator<GroupedDataset<PERSON,ListDataset<FACE>,FACE>>	CrossValidationBenchmark.crossValidator

Methods in org.openimaj.image.processing.face.recognition.benchmarking with parameters of type GroupedDataset

Modifier and Type	Method and Description
FaceRecogniser<FACE,PERSON>	FaceRecogniserProvider.create(GroupedDataset<PERSON,? extends ListDataset<FACE>,FACE> dataset) Create and train a new recogniser instance based on the given dataset

Constructors in org.openimaj.image.processing.face.recognition.benchmarking with parameters of type GroupedDataset

Constructor and Description
CrossValidationBenchmark(CrossValidator<GroupedDataset<PERSON,ListDataset<FACE>,FACE>> crossValidator, GroupedDataset<PERSON,? extends ListDataset<IMAGE>,IMAGE> dataset, FaceDetector<FACE,IMAGE> faceDetector, FaceRecogniserProvider<FACE,PERSON> engine) Construct the CrossValidationBenchmark experiment with the given dependent variables.

Constructor parameters in org.openimaj.image.processing.face.recognition.benchmarking with type arguments of type GroupedDataset

Constructor and Description
CrossValidationBenchmark(CrossValidator<GroupedDataset<PERSON,ListDataset<FACE>,FACE>> crossValidator, GroupedDataset<PERSON,? extends ListDataset<IMAGE>,IMAGE> dataset, FaceDetector<FACE,IMAGE> faceDetector, FaceRecogniserProvider<FACE,PERSON> engine) Construct the CrossValidationBenchmark experiment with the given dependent variables.

Uses of GroupedDataset in org.openimaj.image.processing.face.recognition.benchmarking.dataset

Classes in org.openimaj.image.processing.face.recognition.benchmarking.dataset that implement GroupedDataset

Modifier and Type	Class and Description
class	ATandTDataset A Dataset for Our Database of Faces/The ORL Face Database/The AT&T Face database.
class	TextFileDataset A simple dataset of people and their images, backed by a text file with the following format:

Uses of GroupedDataset in org.openimaj.ml.annotation

Methods in org.openimaj.ml.annotation with parameters of type GroupedDataset

Modifier and Type	Method and Description
static <OBJECT,ANNOTATION> List<AnnotatedObject<OBJECT,ANNOTATION>>	AnnotatedObject.createList(GroupedDataset<ANNOTATION,? extends ListDataset<OBJECT>,OBJECT> dataset) Convert a grouped dataset to a list of annotated objects.
void	IncrementalAnnotator.train(GroupedDataset<ANNOTATION,? extends ListDataset<OBJECT>,OBJECT> dataset) Train the annotator with the given grouped dataset.
void	BatchAnnotator.train(GroupedDataset<ANNOTATION,? extends ListDataset<OBJECT>,OBJECT> dataset) Train the annotator with the given grouped dataset.
void	IncrementalAnnotator.trainMultiClass(GroupedDataset<ANNOTATION,? extends ListDataset<OBJECT>,OBJECT> dataset) Train the annotator with the given grouped dataset.

Uses of GroupedDataset in org.openimaj.ml.annotation.linear

Methods in org.openimaj.ml.annotation.linear with parameters of type GroupedDataset

Modifier and Type	Method and Description
void	LiblinearAnnotator.train(GroupedDataset<ANNOTATION,? extends ListDataset<OBJECT>,OBJECT> dataset)

Uses of GroupedDataset in org.openimaj.ml.dataset

Classes in org.openimaj.ml.dataset that implement GroupedDataset

Modifier and Type	Class and Description
class	WineDataset A Dataset instance of the standard wine clustering experiment found here: