com.intel.analytics.zoo.models.image.common

ImageConfigure

case class ImageConfigure[T](preProcessor: Preprocessing[ImageFeature, ImageFeature] = null, postProcessor: Preprocessing[ImageFeature, ImageFeature] = null, batchPerPartition: Int = 4, labelMap: Map[Int, String] = null, featurePaddingParam: Option[PaddingParam[T]] = scala.None)(implicit evidence$1: ClassTag[T], ev: TensorNumeric[T]) extends Product with Serializable

predictor configure

preProcessor

preprocessor of ImageFrame before model inference

postProcessor

postprocessor of ImageFrame after model inference

batchPerPartition

batch size per partition

labelMap

label mapping

featurePaddingParam

featurePaddingParam if the inputs have variant size

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Instance Constructors

  1. new ImageConfigure(preProcessor: Preprocessing[ImageFeature, ImageFeature] = null, postProcessor: Preprocessing[ImageFeature, ImageFeature] = null, batchPerPartition: Int = 4, labelMap: Map[Int, String] = null, featurePaddingParam: Option[PaddingParam[T]] = scala.None)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    preProcessor

    preprocessor of ImageFrame before model inference

    postProcessor

    postprocessor of ImageFrame after model inference

    batchPerPartition

    batch size per partition

    labelMap

    label mapping

    featurePaddingParam

    featurePaddingParam if the inputs have variant size

Value Members

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. final def asInstanceOf[T0]: T0

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  7. val batchPerPartition: Int

    batch size per partition

  8. def clone(): AnyRef

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    @throws( ... )

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

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  10. val featurePaddingParam: Option[PaddingParam[T]]

    featurePaddingParam if the inputs have variant size

  11. def finalize(): Unit

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

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  13. final def isInstanceOf[T0]: Boolean

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  14. val labelMap: Map[Int, String]

    label mapping

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. val postProcessor: Preprocessing[ImageFeature, ImageFeature]

    postprocessor of ImageFrame after model inference

  19. val preProcessor: Preprocessing[ImageFeature, ImageFeature]

    preprocessor of ImageFrame before model inference

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

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  21. final def wait(): Unit

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

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

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