Packages

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

The ImageFeaturizer relies on a ONNX model to do the featurization. One can set this model using the setOnnxModel parameter with a model you create yourself, or setModel to get a predefined named model from the ONNXHub.

The ImageFeaturizer takes an input column of images (the type returned by the ImageReader), and automatically resizes them to fit the ONNXModel's inputs. It then feeds them through a pre-trained ONNX model.

Linear Supertypes
SynapseMLLogging, ComplexParamsWritable, MLWritable, Wrappable, RWrappable, PythonWrappable, BaseWrappable, HasOutputCol, HasInputCol, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ImageFeaturizer
  2. SynapseMLLogging
  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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Visibility
  1. Public
  2. All

Instance Constructors

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

    uid

    the uid of the image transformer

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. val autoConvertToColor: BooleanParam
  7. val channelNormalizationMeans: DoubleArrayParam
  8. val channelNormalizationStds: DoubleArrayParam
  9. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  10. final def clear(param: Param[_]): ImageFeaturizer.this.type
    Definition Classes
    Params
  11. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  12. val colorScaleFactor: DoubleParam
  13. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  14. val convertFeaturesToVector: (Seq[Seq[Seq[Float]]]) ⇒ DenseVector
  15. val convertOutputToVector: (Seq[Float]) ⇒ DenseVector
  16. def copy(extra: ParamMap): Transformer
    Definition Classes
    ImageFeaturizer → Transformer → PipelineStage → Params
  17. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  18. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  19. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. val dropNa: BooleanParam
  21. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  23. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  24. def explainParams(): String
    Definition Classes
    Params
  25. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  26. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  27. val featureTensorName: Param[String]

    Name of the output node which represents features

  28. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  29. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  30. def getAutoConvertToColor: Boolean
  31. def getChannelNormalizationMeans: Array[Double]

  32. def getChannelNormalizationStds: Array[Double]

  33. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  34. def getColorScaleFactor: Double

  35. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  36. def getDropNa: Boolean

  37. def getFeatureTensorName: String

  38. def getHeadless: Boolean

  39. def getIgnoreDecodingErrors: Boolean

  40. def getImageHeight: Int

  41. def getImageTensorName: String

  42. def getImageWidth: Int

  43. def getInputCol: String

    Definition Classes
    HasInputCol
  44. def getMiniBatchSize: Int

  45. def getModel: Array[Byte]

  46. def getOnnxModel: ONNXModel

  47. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  48. def getOutputCol: String

    Definition Classes
    HasOutputCol
  49. def getOutputTensorName: String

  50. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  51. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  52. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  53. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  54. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  55. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  56. val headless: BooleanParam
  57. val ignoreDecodingErrors: BooleanParam
  58. val imageHeight: IntParam
  59. val imageTensorName: Param[String]

    Name of the input node for images

  60. val imageWidth: IntParam
  61. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  62. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. val inputCol: Param[String]

    The name of the input column

    The name of the input column

    Definition Classes
    HasInputCol
  64. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  65. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  66. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  67. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  68. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  69. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  70. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  71. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  72. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  77. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  78. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  81. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  84. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  85. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  88. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  89. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  90. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  91. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  92. val onnxModel: TransformerParam
  93. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  94. val outputTensorName: Param[String]

    Name of the output node which represents probabilities

  95. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  96. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  97. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  98. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  99. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  100. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  101. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  102. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  103. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    ImageFeaturizer → PythonWrappable
  104. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  105. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  106. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  107. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  108. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  109. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  110. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  111. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  112. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  113. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  114. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  115. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  116. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  117. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  118. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  119. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  120. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  121. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  122. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  123. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  124. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  125. final def set(paramPair: ParamPair[_]): ImageFeaturizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  126. final def set(param: String, value: Any): ImageFeaturizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  127. final def set[T](param: Param[T], value: T): ImageFeaturizer.this.type
    Definition Classes
    Params
  128. def setAutoConvertToColor(value: Boolean): ImageFeaturizer.this.type
  129. def setChannelNormalizationMeans(value: Array[Double]): ImageFeaturizer.this.type

  130. def setChannelNormalizationStds(value: Array[Double]): ImageFeaturizer.this.type

  131. def setColorScaleFactor(value: Double): ImageFeaturizer.this.type

  132. final def setDefault(paramPairs: ParamPair[_]*): ImageFeaturizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  133. final def setDefault[T](param: Param[T], value: T): ImageFeaturizer.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  134. def setDropNa(value: Boolean): ImageFeaturizer.this.type

  135. def setFeatureTensorName(value: String): ImageFeaturizer.this.type

  136. def setHeadless(value: Boolean): ImageFeaturizer.this.type

  137. def setIgnoreDecodingErrors(value: Boolean): ImageFeaturizer.this.type

  138. def setImageHeight(value: Int): ImageFeaturizer.this.type

  139. def setImageTensorName(value: String): ImageFeaturizer.this.type

  140. def setImageWidth(value: Int): ImageFeaturizer.this.type

  141. def setInputCol(value: String): ImageFeaturizer.this.type

    Definition Classes
    HasInputCol
  142. def setMiniBatchSize(value: Int): ImageFeaturizer.this.type

  143. def setModel(bytes: Array[Byte]): ImageFeaturizer.this.type

  144. def setModel(name: String): ImageFeaturizer.this.type
  145. def setModelInfo(info: ONNXModelInfo): ImageFeaturizer.this.type
  146. def setModelLocation(path: String): ImageFeaturizer.this.type
  147. def setOnnxModel(value: ONNXModel): ImageFeaturizer.this.type

  148. def setOutputCol(value: String): ImageFeaturizer.this.type

    Definition Classes
    HasOutputCol
  149. def setOutputTensorName(value: String): ImageFeaturizer.this.type

  150. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  151. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  152. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  153. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ImageFeaturizer → Transformer
  154. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  155. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  156. def transformSchema(schema: StructType): StructType

    Add the features column to the schema

    Add the features column to the schema

    schema

    Schema to transform

    returns

    schema with features column

    Definition Classes
    ImageFeaturizer → PipelineStage
  157. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  158. val uid: String
    Definition Classes
    ImageFeaturizer → SynapseMLLogging → Identifiable
  159. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  160. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  161. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  162. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from HasOutputCol

Inherited from HasInputCol

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

getParam

param

setParam

Ungrouped