Class

com.intel.analytics.bigdl.dlframes

DLImageTransformer

Related Doc: package dlframes

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class DLImageTransformer extends DLTransformerBase[Nothing] with HasInputCol with HasOutputCol

Provides DataFrame-based API for image pre-processing and feature transformation. DLImageTransformer follows the Spark Transformer API pattern and can be used as one stage in Spark ML pipeline.

The input column can be either DLImageSchema.byteSchema or DLImageSchema.floatSchema. If using DLImageReader, the default format is DLImageSchema.byteSchema The output column is always DLImageSchema.floatSchema.

Linear Supertypes
HasOutputCol, HasOutputCol, HasInputCol, HasInputCol, DLTransformerBase[Nothing], Model[Nothing], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DLImageTransformer
  2. HasOutputCol
  3. HasOutputCol
  4. HasInputCol
  5. HasInputCol
  6. DLTransformerBase
  7. Model
  8. Transformer
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DLImageTransformer(transformer: FeatureTransformer)

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  2. new DLImageTransformer(transformer: Transformer[ImageFeature, ImageFeature], uid: String)

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    transformer

    Single or a sequence of BigDL FeatureTransformers to be used. E.g. Resize(256, 256) -> CenterCrop(224, 224) -> ChannelNormalize(123, 117, 104, 1, 1, 1) -> MatToTensor()

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

  3. final def $[T](param: Param[T]): T

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    protected
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    Params

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

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    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

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    Any

  6. final def clear(param: Param[_]): DLImageTransformer.this.type

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    Definition Classes
    Params

  7. def clone(): AnyRef

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

  8. def copy(extra: ParamMap): Nothing

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    Definition Classes
    DLTransformerBase → Model → Transformer → PipelineStage → Params

  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
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    Params

  10. final def defaultCopy[T <: Params](extra: ParamMap): T

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    protected
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    Params

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

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. def explainParam(param: Param[_]): String

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    Definition Classes
    Params

  14. def explainParams(): String

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    Definition Classes
    Params

  15. final def extractParamMap(): ParamMap

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    Params

  16. final def extractParamMap(extra: ParamMap): ParamMap

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    Params

  17. def finalize(): Unit

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    protected[java.lang]
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    AnyRef
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    @throws( classOf[java.lang.Throwable] )

  18. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

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

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  20. final def getDefault[T](param: Param[T]): Option[T]

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    Params

  21. final def getInputCol: String

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    Definition Classes
    HasInputCol

  22. final def getOrDefault[T](param: Param[T]): T

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    Params

  23. final def getOutputCol: String

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    Definition Classes
    HasOutputCol

  24. def getParam(paramName: String): Param[Any]

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    Params

  25. final def hasDefault[T](param: Param[T]): Boolean

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    Params

  26. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  27. def hasParent: Boolean

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    Definition Classes
    Model

  28. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  29. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
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    Logging

  30. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging

  31. final val inputCol: Param[String]

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    Definition Classes
    HasInputCol

  32. def internalTransform(dataFrame: DataFrame): DataFrame

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    Attributes
    protected
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    DLImageTransformer → DLTransformerBase

  33. final def isDefined(param: Param[_]): Boolean

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    Params

  34. final def isInstanceOf[T0]: Boolean

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    Any

  35. final def isSet(param: Param[_]): Boolean

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    Params

  36. def isTraceEnabled(): Boolean

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    protected
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    Logging

  37. def log: Logger

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    Logging

  38. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  39. def logDebug(msg: ⇒ String): Unit

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    Logging

  40. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  41. def logError(msg: ⇒ String): Unit

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    Logging

  42. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  43. def logInfo(msg: ⇒ String): Unit

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    Logging

  44. def logName: String

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    Logging

  45. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  46. def logTrace(msg: ⇒ String): Unit

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    Logging

  47. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  48. def logWarning(msg: ⇒ String): Unit

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    Logging

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

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    AnyRef

  50. final def notify(): Unit

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    AnyRef

  51. final def notifyAll(): Unit

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    AnyRef

  52. final val outputCol: Param[String]

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    Definition Classes
    HasOutputCol

  53. lazy val params: Array[Param[_]]

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    Definition Classes
    Params

  54. var parent: Estimator[Nothing]

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    Definition Classes
    Model

  55. final def set(paramPair: ParamPair[_]): DLImageTransformer.this.type

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  56. final def set(param: String, value: Any): DLImageTransformer.this.type

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  57. final def set[T](param: Param[T], value: T): DLImageTransformer.this.type

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  58. final def setDefault(paramPairs: ParamPair[_]*): DLImageTransformer.this.type

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  59. final def setDefault[T](param: Param[T], value: T): DLImageTransformer.this.type

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  60. def setInputCol(value: String): DLImageTransformer.this.type

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  61. def setOutputCol(value: String): DLImageTransformer.this.type

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  62. def setParent(parent: Estimator[Nothing]): Nothing

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    Definition Classes
    Model

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

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    AnyRef

  64. def toString(): String

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    Identifiable → AnyRef → Any

  65. def transform(dataset: Dataset[_]): DataFrame

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    DLTransformerBase → Transformer

  66. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )

  67. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()

  68. def transformSchema(schema: StructType): StructType

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    Definition Classes
    DLImageTransformer → PipelineStage

  69. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
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    PipelineStage
    Annotations
    @DeveloperApi()

  70. val transformer: Transformer[ImageFeature, ImageFeature]

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    Single or a sequence of BigDL FeatureTransformers to be used.

    Single or a sequence of BigDL FeatureTransformers to be used. E.g. Resize(256, 256) -> CenterCrop(224, 224) -> ChannelNormalize(123, 117, 104, 1, 1, 1) -> MatToTensor()

  71. val uid: String

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    Definition Classes
    DLImageTransformer → Identifiable

  72. def validateInputType(inputType: DataType): Unit

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    Attributes
    protected

  73. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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    @throws( ... )

Inherited from HasOutputCol

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from HasInputCol

Inherited from DLTransformerBase[Nothing]

Inherited from Model[Nothing]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped