RandomElasticTransform classkeras.layers.RandomElasticTransform(
factor=1.0,
scale=1.0,
interpolation="bilinear",
fill_mode="reflect",
fill_value=0.0,
value_range=(0, 255),
seed=None,
data_format=None,
**kwargs
)
A preprocessing layer that applies random elastic transformations.
This layer distorts input images by applying elastic deformations,
simulating a physically realistic transformation. The magnitude of the
distortion is controlled by the scale parameter, while the factor
determines the probability of applying the transformation.
Note: This layer is safe to use inside a tf.data or grain pipeline
(independently of which backend you're using).
Arguments
factor controls the probability of applying the transformation.factor=0.0 ensures no erasing is applied.factor=1.0 means erasing is always applied.(min, max) is provided, a probability value
is sampled between min and max for each image.0.0 and the given float.
Default is 1.0.(min, max) is provided, a random scale value is
sampled within this range.0.0 and the given float.
Default is 1.0."nearest",
"bilinear"."constant",
"nearest", "wrap" and "reflect". Defaults to "constant"."reflect": (d c b a | a b c d | d c b a)
The input is extended by reflecting about the edge of the last
pixel."constant": (k k k k | a b c d | k k k k)
The input is extended by filling all values beyond
the edge with the same constant value k specified by
fill_value."wrap": (a b c d | a b c d | a b c d)
The input is extended by wrapping around to the opposite edge."nearest": (a a a a | a b c d | d d d d)
The input is extended by the nearest pixel.
Note that when using torch backend, "reflect" is redirected to
"mirror" (c d c b | a b c d | c b a b) because torch does not
support "reflect".
Note that torch backend does not support "wrap".fill_mode="constant".[low, high]. This is
typically either [0, 1] or [0, 255] depending on how your
preprocessing pipeline is set up.