Packages

class ImageTransformer extends Transformer with HasInputCol with HasOutputCol with Wrappable with ComplexParamsWritable with BasicLogging

Image processing stage. Please refer to OpenCV for additional information

Linear Supertypes
BasicLogging, ComplexParamsWritable, MLWritable, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, HasOutputCol, HasInputCol, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ImageTransformer
  2. BasicLogging
  3. ComplexParamsWritable
  4. MLWritable
  5. Wrappable
  6. DotnetWrappable
  7. RWrappable
  8. PythonWrappable
  9. BaseWrappable
  10. HasOutputCol
  11. HasInputCol
  12. Transformer
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
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Instance Constructors

  1. new ImageTransformer()
  2. new ImageTransformer(uid: String)

    uid

    The id of the module

Value Members

  1. def blur(height: Double, width: Double): ImageTransformer.this.type
  2. def centerCrop(height: Int, width: Int): ImageTransformer.this.type
  3. final def clear(param: Param[_]): ImageTransformer.this.type
    Definition Classes
    Params
  4. def colorFormat(format: Int): ImageTransformer.this.type
  5. val colorScaleFactor: DoubleParam
  6. def copy(extra: ParamMap): Transformer
    Definition Classes
    ImageTransformer → Transformer → PipelineStage → Params
  7. def crop(x: Int, y: Int, height: Int, width: Int): ImageTransformer.this.type
  8. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  9. val emptyStages: Array[Map[String, Any]]
  10. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  11. def explainParams(): String
    Definition Classes
    Params
  12. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  13. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  14. def flip(flipCode: Int): ImageTransformer.this.type

    Flips the image

    Flips the image

    flipCode

    is a flag to specify how to flip the image: - 0 means flipping around the x-axis (i.e. up-down) - positive value (for example, 1) means flipping around y-axis (left-right) - negative value (for example, -1) means flipping around both axes (diagonally) See OpenCV documentation for details.

  15. def gaussianKernel(apertureSize: Int, sigma: Double): ImageTransformer.this.type
  16. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  17. def getColorScaleFactor: Double
  18. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  19. def getInputCol: String

    Definition Classes
    HasInputCol
  20. def getNormalizeMean: Array[Double]
  21. def getNormalizeStd: Array[Double]
  22. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  23. def getOutputCol: String

    Definition Classes
    HasOutputCol
  24. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  25. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  26. def getStages: Array[Map[String, Any]]
  27. def getTensorChannelOrder: String
  28. def getTensorElementType: DataType
  29. def getToTensor: Boolean
  30. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  31. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  32. val inputCol: Param[String]

    The name of the input column

    The name of the input column

    Definition Classes
    HasInputCol
  33. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  34. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  35. def logClass(): Unit
    Definition Classes
    BasicLogging
  36. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  37. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  38. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  39. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  40. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  41. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  42. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  43. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  44. def normalize(mean: List[Double], std: List[Double], colorScaleFactor: Double): ImageTransformer.this.type

    For py4j invocation.

  45. def normalize(mean: Array[Double], std: Array[Double], colorScaleFactor: Double): ImageTransformer.this.type
  46. val normalizeMean: DoubleArrayParam
  47. val normalizeStd: DoubleArrayParam
  48. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  49. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  50. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  51. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  52. def resize(size: Int, keepAspectRatio: Boolean): ImageTransformer.this.type

    If keep aspect ratio is set to true, the shorter side of the image will be resized to the specified size.

  53. def resize(height: Int, width: Int): ImageTransformer.this.type
  54. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  55. final def set[T](param: Param[T], value: T): ImageTransformer.this.type
    Definition Classes
    Params
  56. def setColorScaleFactor(value: Double): ImageTransformer.this.type
  57. def setInputCol(value: String): ImageTransformer.this.type

    Definition Classes
    HasInputCol
  58. def setNormalizeMean(value: Array[Double]): ImageTransformer.this.type
  59. def setNormalizeStd(value: Array[Double]): ImageTransformer.this.type
  60. def setOutputCol(value: String): ImageTransformer.this.type

    Definition Classes
    HasOutputCol
  61. def setStages(value: ArrayList[HashMap[String, Any]]): ImageTransformer.this.type
  62. def setStages(value: Array[Map[String, Any]]): ImageTransformer.this.type
  63. def setTensorChannelOrder(value: String): ImageTransformer.this.type
  64. def setTensorElementType(value: DataType): ImageTransformer.this.type
  65. def setToTensor(value: Boolean): ImageTransformer.this.type
  66. val stages: ArrayMapParam
  67. val tensorChannelOrder: Param[String]
  68. val tensorElementType: DataTypeParam
  69. def threshold(threshold: Double, maxVal: Double, thresholdType: Int): ImageTransformer.this.type
  70. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  71. val toTensor: BooleanParam
  72. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ImageTransformer → Transformer
  73. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  74. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  75. def transformSchema(schema: StructType): StructType
    Definition Classes
    ImageTransformer → PipelineStage
  76. val uid: String
    Definition Classes
    ImageTransformer → BasicLogging → Identifiable
  77. val ver: String
    Definition Classes
    BasicLogging
  78. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable