Object/Class

com.intel.analytics.zoo.feature.image

ImageSet

Related Docs: class ImageSet | package image

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object ImageSet

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def array(data: Array[Array[Byte]], resizeH: Int = 1, resizeW: Int = 1, imageCodec: Int = Imgcodecs.CV_LOAD_IMAGE_UNCHANGED, labelMap: Map[String, Int] = null): ImageSet

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    create LocalImageSet from array of bytes

    create LocalImageSet from array of bytes

    data

    nested array of bytes, expect inner array is a image

    resizeH

    height after resize, by default is -1 which will not resize the image

    resizeW

    width after resize, by default is -1 which will not resize the image

    imageCodec

    specifying the color type of a loaded image, same as in OpenCV.imread. By default is Imgcodecs.CV_LOAD_IMAGE_UNCHANGED

  5. def array(data: Array[ImageFeature], labelMap: Map[String, Int]): LocalImageSet

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    create LocalImageSet

    create LocalImageSet

    data

    array of ImageFeature

    labelMap

    the labelMap of this ImageSet, a mapping from class names to label

  6. def array(data: Array[ImageFeature]): LocalImageSet

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    create LocalImageSet

    create LocalImageSet

    data

    array of ImageFeature

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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  15. final def ne(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def rdd(data: RDD[ImageFeature], labelMap: Map[String, Int] = null): DistributedImageSet

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    create DistributedImageSet

    create DistributedImageSet

    data

    rdd of ImageFeature

  19. def rddBytes(data: RDD[Array[Byte]], resizeH: Int = 1, resizeW: Int = 1, imageCodec: Int = Imgcodecs.CV_LOAD_IMAGE_UNCHANGED, labelMap: Map[String, Int] = null): ImageSet

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    create DistributedImageSet for a RDD of array bytes

    create DistributedImageSet for a RDD of array bytes

    data

    rdd of array of bytes

    resizeH

    height after resize, by default is -1 which will not resize the image

    resizeW

    width after resize, by default is -1 which will not resize the image

    imageCodec

    specifying the color type of a loaded image, same as in OpenCV.imread. By default is Imgcodecs.CV_LOAD_IMAGE_UNCHANGED

  20. def read(path: String, sc: SparkContext = null, minPartitions: Int = 1, resizeH: Int = 1, resizeW: Int = 1, imageCodec: Int = Imgcodecs.CV_LOAD_IMAGE_UNCHANGED, withLabel: Boolean = false, oneBasedLabel: Boolean = true): ImageSet

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    Read images as Image Set if sc is defined, Read image as DistributedImageSet from local file system or HDFS if sc is null, Read image as LocalImageSet from local file system

    Read images as Image Set if sc is defined, Read image as DistributedImageSet from local file system or HDFS if sc is null, Read image as LocalImageSet from local file system

    path

    path to read images if sc is defined, path can be local or HDFS. Wildcard character are supported. if sc is null, path is local directory/image file/image file with wildcard character if withLabel is set to true, path should be a directory that have two levels. The first level is class folders, and the second is images. All images belong to a same class should be put into the same class folder. So each image in the path is labeled by the folder it belongs.

    sc

    SparkContext

    minPartitions

    A suggestion value of the minimal partition number

    resizeH

    height after resize, by default is -1 which will not resize the image

    resizeW

    width after resize, by default is -1 which will not resize the image

    imageCodec

    specifying the color type of a loaded image, same as in OpenCV.imread. By default is Imgcodecs.CV_LOAD_IMAGE_UNCHANGED

    withLabel

    whether to treat folders in the path as image classification labels and read the labels into ImageSet.

    returns

    ImageSet

  21. def readSequenceFiles(path: String, sc: SparkContext, minPartitions: Int = 1, classNum: Int = 1000): DistributedImageSet

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    Read images (with labels) from Hadoop SequenceFiles as ImageSet.

    Read images (with labels) from Hadoop SequenceFiles as ImageSet.

    path

    The folder path that contains sequence files. Local or distributed file system (such as HDFS) are supported.

    sc

    An instance of SparkContext.

    minPartitions

    Integer. A suggestion value of the minimal partition number for input texts. Default is 1.

    classNum

    Integer. The number of image categories. Default is 1000 for ImageNet.

    returns

    DistributedImageSet.

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

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  23. def toString(): String

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  24. final def wait(): Unit

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

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  26. final def wait(arg0: Long): Unit

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