RandomShear classkeras.layers.RandomShear(
x_factor=0.0,
y_factor=0.0,
interpolation="bilinear",
fill_mode="reflect",
fill_value=0.0,
data_format=None,
seed=None,
**kwargs
)
A preprocessing layer that randomly applies shear transformations to images.
This layer shears the input images along the x-axis and/or y-axis by a
randomly selected factor within the specified range. The shear
transformation is applied to each image independently in a batch. Empty
regions created during the transformation are filled according to the
fill_mode and fill_value parameters.
Note: This layer is safe to use inside a tf.data or grain pipeline
(independently of which backend you're using).
Arguments
(0, x_factor). Values represent a
percentage of the image to shear over. For example, 0.3 shears
pixels up to 30% of the way across the image. All provided values
should be positive.(0, y_factor). Values represent a
percentage of the image to shear over. For example, 0.3 shears
pixels up to 30% of the way across the image. All provided values
should be positive."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".