Package org.opencv.features2d
Class BOWTrainer
java.lang.Object
org.opencv.features2d.BOWTrainer
- Direct Known Subclasses:
BOWKMeansTrainer
Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors.
For details, see, for example, *Visual Categorization with Bags of Keypoints* by Gabriella Csurka,
Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. :
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Field Summary
Fields -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionstatic BOWTrainer
__fromPtr__
(long addr) void
Adds descriptors to a training set.void
clear()
cluster()
Clusters train descriptors.int
Returns the count of all descriptors stored in the training set.protected void
finalize()
Returns a training set of descriptors.long
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Field Details
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nativeObj
protected final long nativeObj
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Constructor Details
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BOWTrainer
protected BOWTrainer(long addr)
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Method Details
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getNativeObjAddr
public long getNativeObjAddr() -
__fromPtr__
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add
Adds descriptors to a training set.- Parameters:
descriptors
- Descriptors to add to a training set. Each row of the descriptors matrix is a descriptor. The training set is clustered using clustermethod to construct the vocabulary.
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getDescriptors
Returns a training set of descriptors.- Returns:
- automatically generated
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descriptorsCount
public int descriptorsCount()Returns the count of all descriptors stored in the training set.- Returns:
- automatically generated
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clear
public void clear() -
cluster
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cluster
Clusters train descriptors.- Parameters:
descriptors
- Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set. The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object are clustered. In the second variant, input descriptors are clustered.- Returns:
- automatically generated
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finalize
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