com.intel.analytics.bigdl.example.imageclassification

MlUtils

object MlUtils

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Type Members

  1. case class ByteImage(data: Array[Byte], imageName: String) extends Product with Serializable

    ByteImage is case class, which represents an object of image in byte format.

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

    It is used to store single data frame information

  3. sealed trait ModelType extends AnyRef

    This is a trait meaning the model type.

  4. case class PredictParams(folder: String = "./", batchSize: Int = 32, classNum: Int = 1000, isHdfs: Boolean = false, modelType: ModelType = MlUtils.this.BigDlModel, modelPath: String = "", showNum: Int = 100) extends Product with Serializable

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  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. object BigDlModel extends ModelType with Product with Serializable

  7. object TorchModel extends ModelType with Product with Serializable

  8. final def asInstanceOf[T0]: T0

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  9. def clone(): AnyRef

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

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  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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

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  14. def hashCode(): Int

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  15. val imageSize: Int

  16. def imagesLoad(paths: Array[LocalLabeledImagePath], scaleTo: Int): Array[ByteImage]

  17. def imagesLoadSeq(url: String, sc: SparkContext, classNum: Int): RDD[ByteImage]

  18. final def isInstanceOf[T0]: Boolean

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  19. def loadModel[T](param: PredictParams)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Module[T]

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

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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  23. val predictParser: OptionParser[PredictParams]

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

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  25. val testMean: (Double, Double, Double)

  26. val testStd: (Double, Double, Double)

  27. def toString(): String

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  28. def transformDF(data: DataFrame, f: Transformer[Row, DenseVector]): DataFrame

  29. final def wait(): Unit

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

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

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