tf.keras.layers.RandomZoom

View source on GitHub

Randomly zoom each image during training.

Inherits From: Layer, Module

View aliases

Main aliases

tf.keras.layers.experimental.preprocessing.RandomZoom

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.RandomZoom, tf.compat.v1.keras.layers.experimental.preprocessing.RandomZoom

tf.keras.layers.RandomZoom(
    height_factor, width_factor=None, fill_mode='reflect',
    interpolation='bilinear', seed=None, fill_value=0.0, **kwargs
)

Args
`height_factor`	a float represented as fraction of value, or a tuple 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=(0.2, 0.3)` result in an output zoomed out by a random amount in the range `[+20%, +30%]`. `height_factor=(-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 tuple 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=(0.2, 0.3)` result in an output zooming out between 20% to 30%. `width_factor=(-0.3, -0.2)` result in an output zooming in between 20% to 30%. Defaults to `None`, 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"`.

Example:

input_img = np.random.random((32, 224, 224, 3))
layer = tf.keras.layers.RandomZoom(.5, .2)
out_img = layer(input_img)
out_img.shape
TensorShape([32, 224, 224, 3])

Input shape:

3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format.

Output shape: