tf.keras.layers.experimental.preprocessing.RandomContrast

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Adjust the contrast of an image or images by a random factor.

Inherits From: Layer

tf.keras.layers.experimental.preprocessing.RandomContrast(
    factor, seed=None, name=None, **kwargs
)

Contrast is adjusted independently for each channel of each image during training.

For each channel, this layer computes the mean of the image pixels in the channel and then adjusts each component x of each pixel to (x - mean) * contrast_factor + mean.

Input shape:

4D tensor with shape: (samples, height, width, channels), data_format='channels_last'.

Output shape:

4D tensor with shape: (samples, height, width, channels), data_format='channels_last'.

Attributes:

  • 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].
  • seed: Integer. Used to create a random seed.
  • name: A string, the name of the layer.

Raise:

  • ValueError: if lower bound is not between [0, 1], or upper bound is negative.