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

Packages that use ListDataset

Package	Description
org.openimaj.audio.analysis.benchmarking
org.openimaj.data.dataset
org.openimaj.data.dataset.cache
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.dataset
org.openimaj.image.annotation.evaluation.datasets
org.openimaj.image.dataset
org.openimaj.image.model
org.openimaj.image.model.asm.datasets
org.openimaj.image.objectdetection.datasets
org.openimaj.image.processing.face.detection	The detection package contains implementations of face detectors.
org.openimaj.image.processing.face.detection.benchmarking
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.ml.annotation
org.openimaj.ml.annotation.linear

Uses of ListDataset in org.openimaj.audio.analysis.benchmarking

Methods in org.openimaj.audio.analysis.benchmarking with parameters of type ListDataset

Modifier and Type	Method and Description
static long	AudioDatasetHelper.calculateStreamLength(ListDataset<List<SampleBuffer>> samples) Calculate the length of the stream of samples that will come from the dataset.
static AudioStream	AudioDatasetHelper.getAudioStream(ListDataset<List<SampleBuffer>> samples) From a dataset that contains sample buffers, this method will return an AudioStream which will return each of the sample buffers in turn.

Uses of ListDataset in org.openimaj.data.dataset

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

Modifier and Type	Class and Description
class	ListBackedDataset<T> A ListBackedDataset is a Dataset backed by an ordered list of items.
class	ReadableListDataset<INSTANCE,SOURCE> Base class for ListDatasets in which each instance is read with an InputStreamObjectReader.
class	VFSListDataset<INSTANCE> A ListDataset backed by a directory of items (either locally or remotely), or items stored in a compressed archive.

Methods in org.openimaj.data.dataset that return ListDataset

Modifier and Type	Method and Description
ListDataset<IdentifiableObject<INSTANCE>>	ReadableListDataset.toIdentifiable() Create a view of this dataset in which the instances are wrapped up in IdentifiableObjects.

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

Methods in org.openimaj.data.dataset.cache that return types with arguments of type ListDataset

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

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

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

Modifier and Type	Method and Description
ListDataset<INSTANCE>	UniformRandomisedSampler.sample(ListDataset<INSTANCE> dataset)

Methods in org.openimaj.experiment.dataset.sampling that return types with arguments of type ListDataset

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 ListDataset

Modifier and Type	Method and Description
ListDataset<INSTANCE>	UniformRandomisedSampler.sample(ListDataset<INSTANCE> dataset)

Method parameters in org.openimaj.experiment.dataset.sampling with type arguments of type ListDataset

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 ListDataset in org.openimaj.experiment.dataset.split

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

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.
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getTestDataset()
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getTrainingDataset()
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	GroupedRandomSplitter.getValidationDataset()

Method parameters in org.openimaj.experiment.dataset.split with type arguments of type ListDataset

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.

Constructor parameters in org.openimaj.experiment.dataset.split with type arguments of type ListDataset

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 ListDataset in org.openimaj.experiment.dataset.util

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

Modifier and Type	Method and Description
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 that return types with arguments of type ListDataset

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.

Method parameters in org.openimaj.experiment.dataset.util with type arguments of type ListDataset

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.

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

Constructor parameters in org.openimaj.experiment.evaluation.classification with type arguments of type ListDataset

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 ListDataset in org.openimaj.experiment.gmm.retrieval

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

Modifier and Type	Class and Description
class	UKBenchListDataset<IMAGE>

Uses of ListDataset in org.openimaj.experiment.validation

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

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

Constructor parameters in org.openimaj.experiment.validation with type arguments of type ListDataset

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 ListDataset in org.openimaj.experiment.validation.cross

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

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)
CrossValidationIterable<ListDataset<INSTANCE>>	KFold.createIterable(ListDataset<INSTANCE> data)
CrossValidationIterable<ListDataset<INSTANCE>>	LeaveOneOut.createIterable(ListDataset<INSTANCE> data)

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

Modifier and Type	Method and Description
CrossValidationIterable<ListDataset<INSTANCE>>	KFold.createIterable(ListDataset<INSTANCE> data)
CrossValidationIterable<ListDataset<INSTANCE>>	LeaveOneOut.createIterable(ListDataset<INSTANCE> data)

Method parameters in org.openimaj.experiment.validation.cross with type arguments of type ListDataset

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 ListDataset in org.openimaj.feature

Methods in org.openimaj.feature that return ListDataset

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

Methods in org.openimaj.feature that return types with arguments of type ListDataset

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 ListDataset

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

Method parameters in org.openimaj.feature with type arguments of type ListDataset

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 ListDataset in org.openimaj.image.annotation.evaluation.dataset

Classes in org.openimaj.image.annotation.evaluation.dataset that implement ListDataset

Modifier and Type	Class and Description
class	Corel5kDataset

Methods in org.openimaj.image.annotation.evaluation.dataset that return ListDataset

Modifier and Type	Method and Description
ListDataset<CorelAnnotatedImage>	StandardCorel5kSplit.getTestDataset()
ListDataset<CorelAnnotatedImage>	StandardCorel5kSplit.getTrainingDataset()

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

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

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)

Method parameters in org.openimaj.image.annotation.evaluation.datasets with type arguments of type ListDataset

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 ListDataset in org.openimaj.image.dataset

Classes in org.openimaj.image.dataset that implement ListDataset

Modifier and Type	Class and Description
class	BingImageDataset<IMAGE extends Image<?,IMAGE>> Image datasets dynamically created from the Bing search API.
class	FlickrImageDataset<IMAGE extends Image<?,IMAGE>> Class to dynamically create image datasets from flickr through various api calls.

Uses of ListDataset in org.openimaj.image.model

Method parameters in org.openimaj.image.model with type arguments of type ListDataset

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

Uses of ListDataset in org.openimaj.image.model.asm.datasets

Subinterfaces of ListDataset in org.openimaj.image.model.asm.datasets

Modifier and Type	Interface and Description
interface	ShapeModelDataset<IMAGE extends Image<?,IMAGE>> Dataset representing pairs of images and fixed size sets of points, together with a set of connections between points which are valid across all instances.

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

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

Modifier and Type	Method and Description
static <IMAGE extends Image<?,IMAGE>> ListDataset<IMAGE>	INRIAPersonDataset.generateNegativeExamples(int numSamplesPerImage, int width, int height, long seed, InputStreamObjectReader<IMAGE> reader)
static <IMAGE extends Image<?,IMAGE>> ListDataset<IMAGE>	INRIAPersonDataset.getNegativeTrainingImages(InputStreamObjectReader<IMAGE> reader)
static <IMAGE extends Image<?,IMAGE>> ListDataset<IMAGE>	INRIAPersonDataset.getPositiveTrainingImages(InputStreamObjectReader<IMAGE> reader)

Methods in org.openimaj.image.objectdetection.datasets that return types with arguments of type ListDataset

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

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

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

Modifier and Type	Method and Description
static <IMAGE extends Image<?,IMAGE>,FACE extends DetectedFace> ListDataset<FACE>	DatasetFaceDetector.process(List<IMAGE> instances, 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 that return types with arguments of type ListDataset

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.

Method parameters in org.openimaj.image.processing.face.detection with type arguments of type ListDataset

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 ListDataset in org.openimaj.image.processing.face.detection.benchmarking

Classes in org.openimaj.image.processing.face.detection.benchmarking that implement ListDataset

Modifier and Type	Class and Description
class	FDDBDataset

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

Modifier and Type	Method and Description
List<Results>	FDDBEvaluation.performEvaluation(ListDataset<FDDBRecord> dataset, FDDBEvaluation.EvaluationDetector detector)

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

Method parameters in org.openimaj.image.processing.face.feature with type arguments of type ListDataset

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 ListDataset in org.openimaj.image.processing.face.recognition

Method parameters in org.openimaj.image.processing.face.recognition with type arguments of type ListDataset

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 ListDataset in org.openimaj.image.processing.face.recognition.benchmarking

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

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

Method parameters in org.openimaj.image.processing.face.recognition.benchmarking with type arguments of type ListDataset

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

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

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.
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 ListDataset in org.openimaj.ml.annotation

Method parameters in org.openimaj.ml.annotation with type arguments of type ListDataset

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 ListDataset in org.openimaj.ml.annotation.linear

Method parameters in org.openimaj.ml.annotation.linear with type arguments of type ListDataset

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