layer_random_zoom {keras}

A preprocessing layer which randomly zooms images during training.

Description

This layer will randomly zoom in or out on each axis of an image independently, filling empty space according to fill_mode.

Usage

layer_random_zoom(
  object,
  height_factor,
  width_factor = NULL,
  fill_mode = "reflect",
  interpolation = "bilinear",
  seed = NULL,
  fill_value = 0,
  ...
)

Arguments

object

What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is:

• missing or NULL, the Layer instance is returned.

• a Sequential model, the model with an additional layer is returned.

• a Tensor, the output tensor from layer_instance(object) is returned.

height_factor

a float represented as fraction of value, or a list of size 2 representing lower and upper bound for zooming vertically. When represented as a single float, this value is used for both the upper and lower bound. A positive value means zooming out, while a negative value means zooming in. For instance, height_factor = c(0.2, 0.3) result in an output zoomed out by a random amount in the range ⁠[+20%, +30%]⁠. height_factor = c(-0.3, -0.2) result in an output zoomed in by a random amount in the range ⁠[+20%, +30%]⁠.

width_factor

a float represented as fraction of value, or a list of size 2 representing lower and upper bound for zooming horizontally. When represented as a single float, this value is used for both the upper and lower bound. For instance, width_factor = c(0.2, 0.3) result in an output zooming out between 20% to 30%. width_factor = c(-0.3, -0.2) result in an output zooming in between 20% to 30%. Defaults to NULL, i.e., zooming vertical and horizontal directions by preserving the aspect ratio.

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".

...

standard layer arguments.

See Also

• https://www.tensorflow.org/api_docs/python/tf/keras/layers/RandomZoom

• https://keras.io/api/layers/preprocessing_layers/

Other image augmentation layers: layer_random_brightness(), layer_random_contrast(), layer_random_crop(), layer_random_flip(), layer_random_height(), layer_random_rotation(), layer_random_translation(), layer_random_width()

Other preprocessing layers: layer_category_encoding(), layer_center_crop(), layer_discretization(), layer_hashing(), layer_integer_lookup(), layer_normalization(), layer_random_brightness(), layer_random_contrast(), layer_random_crop(), layer_random_flip(), layer_random_height(), layer_random_rotation(), layer_random_translation(), layer_random_width(), layer_rescaling(), layer_resizing(), layer_string_lookup(), layer_text_vectorization()