keras_cv.layers.RandomHue(factor, value_range, seed=None, **kwargs)
Randomly adjusts the hue on given images.
This layer will randomly increase/reduce the hue for the input RGB
images. At inference time, the output will be identical to the input.
Call the layer with
training=True to adjust the brightness of the input.
The image hue is adjusted by converting the image(s) to HSV and rotating the hue channel (H) by delta. The image is then converted back to RGB.
factorcontrols the extent to which the image hue is impacted.
factor=0.0makes 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
factoris sampled between the two values for every image augmented. If a single float is used, a value between
0.0and the passed float is sampled. In order to ensure the value is always the same, please pass a tuple with two identical floats:
[0, 255]depending on how your preprocessing pipeline is setup.