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Showing content from https://keras.io/api/layers/preprocessing_layers/image_augmentation/rand_augment below:

RandAugment layer

[source]

keras.layers.RandAugment(
    value_range=(0, 255),
    num_ops=2,
    factor=0.5,
    interpolation="bilinear",
    seed=None,
    data_format=None,
    **kwargs
)

RandAugment performs the Rand Augment operation on input images.

This layer can be thought of as an all-in-one image augmentation layer. The policy implemented by this layer has been benchmarked extensively and is effective on a wide variety of datasets.

References

• RandAugment

Arguments

• value_range: The range of values the input image can take. Default is (0, 255). Typically, this would be (0, 1) for normalized images or (0, 255) for raw images.
• num_ops: The number of augmentation operations to apply sequentially to each image. Default is 2.
• factor: The strength of the augmentation as a normalized value between 0 and 1. Default is 0.5.
• interpolation: The interpolation method to use for resizing operations. Options include nearest, bilinear. Default is bilinear.
• seed: Integer. Used to create a random seed.

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