RandomContrast layer
RandomContrast class
keras.layers.RandomContrast(factor, seed=None, **kwargs)
A preprocessing layer which randomly adjusts contrast during training.
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
in integer or floating point dtype.
By default, the layer will output floats.
Note: This layer is safe to use inside a tf.data pipeline
(independently of which backend you're using).
Input shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.
Output shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.
Arguments
- 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 + meanwheremeanis the mean value of the channel. - seed: Integer. Used to create a random seed.