RandomSharpness
classkeras_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
keras_cv.FactorSampler
. factor
controls the extent to which the
image sharpness is impacted. factor=0.0
makes 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
between 0.0
and 1.0
. If a tuple is used, a factor
is sampled
between the two values for every image augmented. If a single float
is used, a value between 0.0
and 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)
.[0, 1]
or [0, 255]
depending
on how your preprocessing pipeline is set up.