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

RandomColorJitter layer

[source]

keras.layers.RandomColorJitter(
    value_range=(0, 255),
    brightness_factor=None,
    contrast_factor=None,
    saturation_factor=None,
    hue_factor=None,
    seed=None,
    data_format=None,
    **kwargs
)

RandomColorJitter class randomly apply brightness, contrast, saturation and hue image processing operation sequentially and randomly on the input.

Arguments

• value_range: the range of values the incoming images will have. Represented as a two number tuple written [low, high]. This is typically either [0, 1] or [0, 255] depending on how your preprocessing pipeline is set up.
• brightness_factor: Float or a list/tuple of 2 floats between -1.0 and 1.0. The factor is used to determine the lower bound and upper bound of the brightness adjustment. A float value will be chosen randomly between the limits. When -1.0 is chosen, the output image will be black, and when 1.0 is chosen, the image will be fully white. When only one float is provided, eg, 0.2, then -0.2 will be used for lower bound and 0.2 will be used for upper bound.
• contrast_factor: a positive float represented as fraction of value, or a tuple of size 2 representing lower and upper bound. When represented as a single float, lower = upper. The contrast factor will be randomly picked between [1.0 - lower, 1.0 + upper]. For any pixel x in the channel, the output will be (x - mean) * factor + mean where mean is the mean value of the channel.
• saturation_factor: A tuple of two floats or a single float. factor controls the extent to which the image saturation is impacted. factor=0.5 makes this layer perform a no-op operation. factor=0.0 makes the image fully grayscale. factor=1.0 makes the image fully saturated. Values should be between 0.0 and 1.0. If a tuple is used, a factor is sampled between the two values for every image augmented. If a single float is used, a value between 0.0 and the passed float is sampled. To ensure the value is always the same, pass a tuple with two identical floats: (0.5, 0.5).
• hue_factor: A single float or a tuple of two floats. factor controls the extent to which the image hue is impacted. factor=0.0 makes this layer perform a no-op operation, while a value of 1.0 performs the most aggressive contrast adjustment available. If a tuple is used, a factor is sampled between the two values for every image augmented. If a single float is used, a value between 0.0 and the passed float is sampled. In order to ensure the value is always the same, please pass a tuple with two identical floats: (0.5, 0.5).
• seed: Integer. Used to create a random seed.

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