Packages

abstract class MTImageFeatureToBatch extends Transformer[ImageFeature, MiniBatch[Float]]

An abstract class to convert ImageFeature iterator to MiniBatches. This transformer will be run on each image feature. "processImageFeature" will be called to buffer the image features. When there are enough buffered image features to form a batch, "createBatch" will be called. You should override processImageFeature to buffer each image feature, and createBatch to convert the buffered data into a mini-batch

Linear Supertypes
Transformer[ImageFeature, MiniBatch[Float]], Serializable, Serializable, AnyRef, Any
Known Subclasses
ClassificationMTImageFeatureToBatch, RoiImageFeatureToBatch, RoiImageFeatureToBatchWithResize
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Inherited
  1. MTImageFeatureToBatch
  2. Transformer
  3. Serializable
  4. Serializable
  5. AnyRef
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Visibility
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Abstract Value Members

  1. abstract def createBatch(batchSize: Int): MiniBatch[Float]
    Attributes
    protected
  2. abstract def processImageFeature(img: ImageFeature, position: Int): Unit
    Attributes
    protected

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. def ->[C](other: Transformer[MiniBatch[Float], C]): Transformer[ImageFeature, C]
    Definition Classes
    Transformer
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def apply(prev: Iterator[ImageFeature]): Iterator[MiniBatch[Float]]
    Definition Classes
    MTImageFeatureToBatch → Transformer
  6. def apply(dataset: RDD[ImageFeature])(implicit evidence: ClassTag[MiniBatch[Float]]): RDD[MiniBatch[Float]]

    Apply this transformer to rdd

    Apply this transformer to rdd

    Definition Classes
    Transformer
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. val batchSize: Int
    Attributes
    protected
  9. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  10. def cloneTransformer(): Transformer[ImageFeature, MiniBatch[Float]]
    Definition Classes
    Transformer
  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  13. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. val parallelism: Int
    Attributes
    protected
  21. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  22. def toString(): String
    Definition Classes
    AnyRef → Any
  23. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from Transformer[ImageFeature, MiniBatch[Float]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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