tf.keras.layers.RandomRotation

A preprocessing layer which randomly rotates images during training.

Inherits From: Layer, Module

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

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 interger or floating point dtype. By default, the layer will output floats.

For an overview and full list of preprocessing layers, see the preprocessing guide.

3D unbatched) or 4D (batched) tensor with shape

(..., height, width, channels), in "channels_last" format

3D unbatched) or 4D (batched) tensor with shape

(..., height, width, channels), in "channels_last" format

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".

auto_vectorize Control whether automatic vectorization occurs.

By default the call() method leverages the tf.vectorized_map() function. Auto-vectorization can be disabled by setting self.auto_vectorize = False in your __init__() method. When disabled, call() instead relies on tf.map_fn(). For example:

class SubclassLayer(BaseImageAugmentationLayer):
  def __init__(self):
    super().__init__()
    self.auto_vectorize = False