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, 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. RWrappable
  7. PythonWrappable
  8. BaseWrappable
  9. HasOutputCol
  10. HasInputCol
  11. Transformer
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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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. val emptyStages: Array[Map[String, Any]]
  9. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  10. def explainParams(): String
    Definition Classes
    Params
  11. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  12. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  13. 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.

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

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

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

    The name of the input column

    The name of the input column

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

    For py4j invocation.

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

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  46. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  47. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  48. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  49. 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.

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

    Definition Classes
    HasInputCol
  55. def setNormalizeMean(value: Array[Double]): ImageTransformer.this.type
  56. def setNormalizeStd(value: Array[Double]): ImageTransformer.this.type
  57. def setOutputCol(value: String): ImageTransformer.this.type

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