RandomRotation
classtf_keras.layers.RandomRotation(
factor,
fill_mode="reflect",
interpolation="bilinear",
seed=None,
fill_value=0.0,
**kwargs
)
A preprocessing layer which randomly rotates images during training.
This layer will apply random rotations to each image, filling empty space
according to fill_mode
.
By default, random rotations are only applied during training.
At inference time, the layer does nothing. If you need to apply random
rotations at inference time, set training
to True when calling the layer.
Input pixel values can be of any range (e.g. [0., 1.)
or [0, 255]
) and
of integer or floating point dtype.
By default, the layer will output floats.
For an overview and full list of preprocessing layers, see the preprocessing guide.
Input shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format
Output shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels)
, in "channels_last"
format
Arguments
factor=(-0.2, 0.3)
results in an output rotation by a random
amount in the range [-20% * 2pi, 30% * 2pi]
.
factor=0.2
results in an
output rotating by a random amount
in the range [-20% * 2pi, 20% * 2pi]
.{"constant", "reflect", "wrap", "nearest"}
).(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.(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 = 0.(a b c d | a b c d | a b c d)
The input is extended by
wrapping around to the opposite edge.(a a a a | a b c d | d d d d)
The input is extended by the nearest pixel."nearest"
,
"bilinear"
.fill_mode="constant"
.