layer_random_zoom: A preprocessing layer which randomly zooms images during...
In keras: R Interface to 'Keras'

layer_random_zoom

R Documentation

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.

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()