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=0.2results 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_formatvalue found in your Keras config file at~/.keras/keras.json. If you never set it, then it will be"channels_last".