ยป Keras API reference / KerasCV / Layers / Preprocessing layers / RandomSharpness layer

RandomSharpness layer

[source]

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. 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).
  • 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 setup.