@Namespace(value="cv") @NoOffset @Properties(inherit=opencv_features2d.class) public class BOWKMeansTrainer extends BOWTrainer
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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BOWKMeansTrainer(int clusterCount) |
BOWKMeansTrainer(int clusterCount,
TermCriteria termcrit,
int attempts,
int flags)
\brief The constructor.
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BOWKMeansTrainer(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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Mat |
cluster()
\overload
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Mat |
cluster(Mat descriptors)
\brief Clusters train descriptors.
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add, clear, descriptorsCount, getDescriptors
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public BOWKMeansTrainer(Pointer p)
Pointer(Pointer)
.public BOWKMeansTrainer(int clusterCount, @Const @ByRef(nullValue="cv::TermCriteria()") TermCriteria termcrit, int attempts, int flags)
cv::kmeans
public BOWKMeansTrainer(int clusterCount)
@ByVal public Mat cluster()
BOWTrainer
cluster
in class BOWTrainer
@ByVal public Mat cluster(@Const @ByRef Mat descriptors)
BOWTrainer
cluster
in class BOWTrainer
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.
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