Class

com.intel.analytics.bigdl.example.imageclassification.MlUtils

DfPoint

Related Doc: package MlUtils

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case class DfPoint(features: DenseVector, imageName: String) extends Product with Serializable

It is used to store single data frame information

features

extracted features after the transformers

imageName

image name

Linear Supertypes
Serializable, Serializable, Product, Equals, AnyRef, Any
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  1. DfPoint
  2. Serializable
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Instance Constructors

  1. new DfPoint(features: DenseVector, imageName: String)

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    features

    extracted features after the transformers

    imageName

    image name

Value Members

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

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    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
    Annotations
    @throws( ... )

  6. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  7. val features: DenseVector

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    extracted features after the transformers

  8. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  9. final def getClass(): Class[_]

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  10. val imageName: String

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    image name

  11. final def isInstanceOf[T0]: Boolean

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    Any

  12. final def ne(arg0: AnyRef): Boolean

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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  15. final def synchronized[T0](arg0: ⇒ T0): T0

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  16. final def wait(): Unit

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    @throws( ... )

  17. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )

  18. final def wait(arg0: Long): Unit

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Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

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