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.
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
Args
factor
a float represented as fraction of 2 Pi, or a tuple of size 2
representing lower and upper bound for rotating clockwise and
counter-clockwise. A positive values means rotating
counter clock-wise,
while a negative value means clock-wise.
When represented as a single
float, this value is used for both the upper and lower bound.
For instance, 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].
fill_mode
Points outside the boundaries of the input are filled
according to the given mode
(one of {"constant", "reflect", "wrap", "nearest"}).
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 = 0.
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.
This method is the reverse of get_config,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights).
Args
config
A Python dictionary, typically the
output of get_config.