RandomSharpness layer
RandomSharpness class
keras_cv.layers.RandomSharpness(factor, value_range, seed=None, **kwargs)
Randomly performs the sharpness operation on given images.
The sharpness operation first performs a blur operation, then blends between the original image and the blurred image. This operation makes the edges of an image less sharp than they were in the original image.
References
Arguments
- factor: A tuple of two floats, a single float or
keras_cv.FactorSampler.factorcontrols the extent to which the image sharpness is impacted.factor=0.0makes this layer perform a no-op operation, while a value of 1.0 uses the sharpened result entirely. Values between 0 and 1 result in linear interpolation between the original image and the sharpened image. Values should be between0.0and1.0. If a tuple is used, afactoris sampled between the two values for every image augmented. If a single float is used, a value between0.0and the passed float is sampled. In order to ensure the value is always the same, please pass a tuple with two identical floats:(0.5, 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.