tf.keras.layers.RandomRotation  |  TensorFlow v2.16.1 (original) (raw)

A preprocessing layer which randomly rotates images during training.

Inherits From: Layer, Operation

tf.keras.layers.RandomRotation(
    factor,
    fill_mode='reflect',
    interpolation='bilinear',
    seed=None,
    fill_value=0.0,
    value_range=(0, 255),
    data_format=None,
    **kwargs
)

Used in the notebooks

Used in the guide Used in the tutorials
Working with preprocessing layers Image classification Data augmentation Transfer learning and fine-tuning Retraining an Image Classifier

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.

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.
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".
Attributes
input Retrieves the input tensor(s) of a symbolic operation.Only returns the tensor(s) corresponding to the _first time_the operation was called.
output Retrieves the output tensor(s) of a layer.Only returns the tensor(s) corresponding to the _first time_the operation was called.

Methods

from_config

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@classmethod from_config( config )

Creates a layer from its config.

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.
Returns
A layer instance.

symbolic_call

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symbolic_call(
    *args, **kwargs
)