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DocumentScoreModifiers that
use RANSAC to fit a geometric model to matching pairs
of visual terms.AffineTransformModel to the matching visual term pairs.BitOut
It encodes the data with the right compression methods.
ApplicationSetup.WeightingModel that calculates an unweighted
cosine distance between query and target vectors.Location object.
PositionSpec.toString().
TermPayloadInvertedIndex.getPayloads(BitIndexPointer).
PositionSpec used for this index.
HomographyModel to the matching visual term pairs.WeightingModel that calculates the L1 distance
between IDF weighted query and target vectors.WeightingModel that calculates the L1 distance
between unweighted query and target vectors.PositionSpec into the term payloads of an inverted index.Collection of documents built from QuantisedLocalFeatures.Document implementation for documents
built up of a list of visual terms in the form of
QuantisedLocalFeatures.MultiTermQuery constructed from an instance of
a QLFDocument.Collection of
QLFDocuments stored on disk.Collection of
QLFDocuments held in memory.Collection of
QLFDocuments stored within a Hadoop SequenceFile.Cluster) which
can be used to quantise features into visual terms.DataInput object.
ExtensibleSinglePassIndexer.BasicIterablePosting that allows payload
data to be stored with each posting.DataOutput object.
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