ImageConfigure

predictor configure

preProcessor: preprocessor of ImageSet before model inference
postProcessor: postprocessor of ImageSet after model inference
batchPerPartition: batch size per partition
labelMap: label mapping
featurePaddingParam: featurePaddingParam if the inputs have variant size

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new ImageConfigure(preProcessor: Preprocessing[ImageFeature, ImageFeature] = null, postProcessor: Preprocessing[ImageFeature, ImageFeature] = null, batchPerPartition: Int = 4, labelMap: Map[Int, String] = null, featurePaddingParam: Option[PaddingParam[T]] = None)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

preProcessor
preprocessor of ImageSet before model inference
postProcessor
postprocessor of ImageSet after model inference
batchPerPartition
batch size per partition
labelMap
label mapping
featurePaddingParam
featurePaddingParam if the inputs have variant size

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
val batchPerPartition: Int

batch size per partition
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val featurePaddingParam: Option[PaddingParam[T]]

featurePaddingParam if the inputs have variant size
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val labelMap: Map[Int, String]

label mapping
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val postProcessor: Preprocessing[ImageFeature, ImageFeature]

postprocessor of ImageSet after model inference
val preProcessor: Preprocessing[ImageFeature, ImageFeature]

preprocessor of ImageSet before model inference
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object ImageConfigure | package common

Instance Constructors

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val batchPerPartition: Int

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

val featurePaddingParam: Option[PaddingParam[T]]

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val labelMap: Map[Int, String]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val postProcessor: Preprocessing[ImageFeature, ImageFeature]

val preProcessor: Preprocessing[ImageFeature, ImageFeature]

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

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped