com.intel.analytics.bigdl.dataset.DataSet

ImageFolder

object ImageFolder

Generate a DataSet from a local image folder. The image folder should have two levels. The first level is class folders, and the second level 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.

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

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  13. def images(path: Path, sc: SparkContext, scaleTo: Int): DataSet[LabeledBGRImage]

    Extract all images under the given path into a Distributed DataSet.

    Extract all images under the given path into a Distributed DataSet. The images are all labeled.

    path
    sc
    scaleTo
    returns

  14. def images(path: Path, scaleTo: Int): DataSet[LabeledBGRImage]

    Extract all images under the given path into a Local DataSet.

    Extract all images under the given path into a Local DataSet. The images are all labeled.

    path
    scaleTo
    returns

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  18. final def notifyAll(): Unit

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  19. def paths(path: Path): LocalDataSet[LocalLabeledImagePath]

    Extract all image paths into a Local DataSet.

    Extract all image paths into a Local DataSet. The paths are all labeled. When the image files are too large(e.g. ImageNet2012 data set), you'd better readd all paths instead of image files themselves.

    path
    returns

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