RandomRotation layer
- Original Link : https://keras.io/api/layers/preprocessing_layers/image_augmentation/random_rotation/
- Last Checked at : 2024-11-25
RandomRotation
class
keras.layers.RandomRotation(
factor,
fill_mode="reflect",
interpolation="bilinear",
seed=None,
fill_value=0.0,
data_format=None,
**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, pass training=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.
Note: This layer is safe to use inside a tf.data
pipeline (independently of which backend you’re using).
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: 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.
- reflect:
- interpolation: Interpolation mode. Supported values:
"nearest"
,"bilinear"
. - seed: Integer. Used to create a random seed.
- fill_value: a float represents the value to be filled outside the boundaries when
fill_mode="constant"
. - data_format: string, either
"channels_last"
or"channels_first"
. The ordering of the dimensions in the inputs."channels_last"
corresponds to inputs with shape(batch, height, width, channels)
while"channels_first"
corresponds to inputs with shape(batch, channels, height, width)
. It defaults to theimage_data_format
value found in your Keras config file at~/.keras/keras.json
. If you never set it, then it will be"channels_last"
.