Packages

c

com.intel.analytics.bigdl.transform.vision.image

RoiImageFeatureToBatchWithResize

class RoiImageFeatureToBatchWithResize extends MTImageFeatureToBatch

A transformer pipeline wrapper to create RoiMiniBatch in multiple threads. Image features may have different sizes, so firstly we need to calculate max size in one batch, then padding all features to one batch with max size.

Linear Supertypes
MTImageFeatureToBatch, Transformer[ImageFeature, MiniBatch[Float]], Serializable, Serializable, AnyRef, Any
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Inherited
  1. RoiImageFeatureToBatchWithResize
  2. MTImageFeatureToBatch
  3. Transformer
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
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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
    Definition Classes
    MTImageFeatureToBatch
  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. def createBatch(batchSize: Int): MiniBatch[Float]
    Attributes
    protected
    Definition Classes
    RoiImageFeatureToBatchWithResize → MTImageFeatureToBatch
  12. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  14. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  15. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  17. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  18. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  19. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. val parallelism: Int
    Attributes
    protected
    Definition Classes
    MTImageFeatureToBatch
  22. def processImageFeature(img: ImageFeature, position: Int): Unit
    Attributes
    protected
    Definition Classes
    RoiImageFeatureToBatchWithResize → MTImageFeatureToBatch
  23. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  24. def toString(): String
    Definition Classes
    AnyRef → Any
  25. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  26. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from MTImageFeatureToBatch

Inherited from Transformer[ImageFeature, MiniBatch[Float]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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