| 程序包 | 说明 |
|---|---|
| net.semanticmetadata.lire.aggregators | |
| net.semanticmetadata.lire.builders | |
| net.semanticmetadata.lire.classifiers | |
| net.semanticmetadata.lire.indexers.parallel |
| 限定符和类型 | 方法和说明 |
|---|---|
protected int |
AbstractAggregator.clusterForFeature(double[] f,
Cluster[] clustersArray)
Returns the index of the cluster with the min distance between a feature and a codebook.
|
void |
VLAD.createVectorRepresentation(java.util.List<? extends LocalFeature> listOfLocalFeatures,
Cluster[] clustersArray)
Given a list of features and a codebook,
VLAD.createVectorRepresentation(List, Cluster[]) aggregates
the features to create the vector representation according to the VLAD model. |
void |
ShapemeAggregator.createVectorRepresentation(java.util.List<? extends LocalFeature> list,
Cluster[] clusters) |
void |
BOVW.createVectorRepresentation(java.util.List<? extends LocalFeature> listOfLocalFeatures,
Cluster[] clustersArray)
Given a list of features and a codebook,
BOVW.createVectorRepresentation(List, Cluster[]) aggregates
the features to create the vector representation according to the BOVW model. |
void |
Aggregator.createVectorRepresentation(java.util.List<? extends LocalFeature> listOfLocalFeatures,
Cluster[] clustersArray)
This method is used to create the vector representation of an image using the list of Features and a codebook
|
void |
ShapemeAggregator.createVisualWords(java.util.List<? extends LocalFeature> list,
Cluster[] clusters) |
| 限定符和类型 | 方法和说明 |
|---|---|
void |
SimpleDocumentBuilder.addExtractor(java.lang.Class<? extends GlobalFeature> globalFeatureClass,
SimpleExtractor.KeypointDetector keypointDetector,
Cluster[] codebook)
Can be used to add a global extractor with a
SimpleExtractor.KeypointDetector. |
void |
LocalDocumentBuilder.addExtractor(java.lang.Class<? extends LocalFeatureExtractor> localFeatureExtractorClass,
Cluster[] codebook)
Can be used to add local extractors.
|
void |
SimpleDocumentBuilder.addExtractor(ExtractorItem extractorItem,
Cluster[] codebook)
Can be used to add a global extractor with a
SimpleExtractor.KeypointDetector. |
void |
LocalDocumentBuilder.addExtractor(ExtractorItem extractorItem,
Cluster[] codebook)
Can be used to add local extractors.
|
| 构造器和说明 |
|---|
LocalDocumentBuilder(java.lang.Class<? extends LocalFeatureExtractor> localFeatureExtractorClass,
Cluster[] codebook) |
LocalDocumentBuilder(java.lang.Class<? extends LocalFeatureExtractor> localFeatureExtractorClass,
Cluster[] codebook,
java.lang.Class<? extends AbstractAggregator> aggregatorClass) |
LocalDocumentBuilder(ExtractorItem extractorItem,
Cluster[] codebook) |
LocalDocumentBuilder(ExtractorItem extractorItem,
Cluster[] codebook,
java.lang.Class<? extends AbstractAggregator> aggregatorClass) |
SimpleDocumentBuilder(java.lang.Class<? extends GlobalFeature> globalFeatureClass,
SimpleExtractor.KeypointDetector keypointDetector,
Cluster[] codebook) |
SimpleDocumentBuilder(java.lang.Class<? extends GlobalFeature> globalFeatureClass,
SimpleExtractor.KeypointDetector keypointDetector,
Cluster[] codebook,
java.lang.Class<? extends AbstractAggregator> aggregatorClass) |
SimpleDocumentBuilder(ExtractorItem extractorItem,
Cluster[] codebook) |
SimpleDocumentBuilder(ExtractorItem extractorItem,
Cluster[] codebook,
java.lang.Class<? extends AbstractAggregator> aggregatorClass) |
| 限定符和类型 | 字段和说明 |
|---|---|
protected Cluster[] |
KMeans.clusters |
| 限定符和类型 | 方法和说明 |
|---|---|
Cluster[] |
KMeans.getClusters() |
static Cluster[] |
Cluster.readClusters(java.lang.String file) |
| 限定符和类型 | 方法和说明 |
|---|---|
static void |
Cluster.writeClusters(Cluster[] clusters,
java.lang.String path) |
| 限定符和类型 | 方法和说明 |
|---|---|
void |
ParallelIndexer.addExtractor(java.lang.Class<? extends GlobalFeature> globalFeatureClass,
SimpleExtractor.KeypointDetector detector,
Cluster[] codebook) |
void |
ParallelIndexer.addExtractor(java.lang.Class<? extends LocalFeatureExtractor> localFeatureExtractorClass,
Cluster[] codebook) |