tf.keras.layers.RandomContrast

A preprocessing layer which randomly adjusts contrast during training.

Inherits From: Layer, Module

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

This layer will randomly adjust the contrast of an image or images by a random factor. 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 pixel values can be of any range (e.g. [0., 1.) or [0, 255]) and of interger or floating point dtype. By default, the layer will output floats.

For an overview and full list of preprocessing layers, see the preprocessing guide.

3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format.

3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format.

seed optional integer, used to create RandomGenerator.
force_generator boolean, default to False, whether to force the RandomGenerator to use the code branch of tf.random.Generator.
**kwargs other keyword arguments that will be passed to the parent class

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.