Packages

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

Image processing stage. Please refer to OpenCV for additional information

Linear Supertypes
SynapseMLLogging, 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. SynapseMLLogging
  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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Instance Constructors

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

    uid

    The id of the module

Value Members

  1. val autoConvertToColor: BooleanParam
  2. def blur(height: Double, width: Double): ImageTransformer.this.type
  3. def centerCrop(height: Int, width: Int): ImageTransformer.this.type
  4. final def clear(param: Param[_]): ImageTransformer.this.type
    Definition Classes
    Params
  5. def colorFormat(format: Int): ImageTransformer.this.type
  6. val colorScaleFactor: DoubleParam
  7. def copy(extra: ParamMap): Transformer
    Definition Classes
    ImageTransformer → Transformer → PipelineStage → Params
  8. def crop(x: Int, y: Int, height: Int, width: Int): ImageTransformer.this.type
  9. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  10. val emptyStages: Array[Map[String, Any]]
  11. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  12. def explainParams(): String
    Definition Classes
    Params
  13. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  14. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  15. 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.

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

    Definition Classes
    HasInputCol
  23. def getNormalizeMean: Array[Double]
  24. def getNormalizeStd: Array[Double]
  25. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  26. def getOutputCol: String

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

    The name of the input column

    The name of the input column

    Definition Classes
    HasInputCol
  37. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  38. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  39. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  40. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  41. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  42. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  43. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  44. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  45. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  46. def normalize(mean: List[Double], std: List[Double], colorScaleFactor: Double): ImageTransformer.this.type

    For py4j invocation.

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

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  51. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  52. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  53. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  54. 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.

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

    Definition Classes
    HasInputCol
  62. def setNormalizeMean(value: Array[Double]): ImageTransformer.this.type
  63. def setNormalizeStd(value: Array[Double]): ImageTransformer.this.type
  64. def setOutputCol(value: String): ImageTransformer.this.type

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