layer_random_zoom
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
| Arguments | Description |
|---|---|
| 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()