tf.keras.layers.RandomSaturation

Randomly adjusts the saturation on given images.

Inherits From: Layer, Operation

This layer will randomly increase/reduce the saturation for the input RGB images.

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).
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.
seed Integer. Used to create a random seed.

Example:

(images, labels), _ = keras.datasets.cifar10.load_data()
images = images.astype("float32")
random_saturation = keras.layers.RandomSaturation(factor=0.2)
augmented_images = random_saturation(images)

input Retrieves the input tensor(s) of a symbolic operation.

Only returns the tensor(s) corresponding to the first time the operation was called.

output Retrieves the output tensor(s) of a layer.

Only returns the tensor(s) corresponding to the first time the operation was called.

Methods

convert_weight

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Convert the weight if it is from the a different backend.

from_config

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Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

Args
config A Python dictionary, typically the output of get_config.

Returns
An operation instance.

get_random_transformation

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transform_bounding_boxes

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transform_images

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transform_labels

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transform_segmentation_masks

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transform_single_bounding_box

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transform_single_image

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transform_single_label

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transform_single_segmentation_mask

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