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

RoiImageFeatureToBatch

class RoiImageFeatureToBatch extends MTImageFeatureToBatch

A transformer pipeline wrapper to create RoiMiniBatch in multiple threads The output "target" is a Table. The keys are from 1 to sizeof(batch). The values are the tables for each RoiLabel. Each Roi label table, contains fields of RoiLabel class. The sizes of the input images should be the same

Linear Supertypes
MTImageFeatureToBatch, Transformer[ImageFeature, MiniBatch[Float]], Serializable, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. RoiImageFeatureToBatch
  2. MTImageFeatureToBatch
  3. Transformer
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. def ->[C](other: Transformer[MiniBatch[Float], C]): Transformer[ImageFeature, C]

    Definition Classes
    Transformer
  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  7. def apply(prev: Iterator[ImageFeature]): Iterator[MiniBatch[Float]]

    Definition Classes
    MTImageFeatureToBatchTransformer
  8. def apply(dataset: RDD[ImageFeature])(implicit evidence: ClassTag[MiniBatch[Float]]): RDD[MiniBatch[Float]]

    Apply this transformer to rdd

    Apply this transformer to rdd

    dataset

    Definition Classes
    Transformer
  9. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  10. val batchSize: Int

    Attributes
    protected
    Definition Classes
    MTImageFeatureToBatch
  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  12. def cloneTransformer(): Transformer[ImageFeature, MiniBatch[Float]]

    Definition Classes
    Transformer
  13. def createBatch(curBatchSize: Int): MiniBatch[Float]

    Attributes
    protected
    Definition Classes
    RoiImageFeatureToBatchMTImageFeatureToBatch
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  16. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  18. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  19. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  20. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  21. final def notify(): Unit

    Definition Classes
    AnyRef
  22. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  23. val parallelism: Int

    Attributes
    protected
    Definition Classes
    MTImageFeatureToBatch
  24. def processImageFeature(img: ImageFeature, position: Int): Unit

    Attributes
    protected
    Definition Classes
    RoiImageFeatureToBatchMTImageFeatureToBatch
  25. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  26. def toString(): String

    Definition Classes
    AnyRef → Any
  27. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MTImageFeatureToBatch

Inherited from Transformer[ImageFeature, MiniBatch[Float]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped