tf.keras.layers.experimental.preprocessing.Resizing

Image resizing layer.

Inherits From: PreprocessingLayer, Layer, Module

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.experimental.preprocessing.Resizing

tf.keras.layers.experimental.preprocessing.Resizing(
    height, width, interpolation='bilinear', name=None, **kwargs
)

Resize the batched image input to target height and width. The input should be a 4-D tensor in the format of NHWC.

Arguments
height	Integer, the height of the output shape.
width	Integer, the width of the output shape.
interpolation	String, the interpolation method. Defaults to bilinear. Supports bilinear, nearest, bicubic, area, lanczos3, lanczos5, gaussian, mitchellcubic
name	A string, the name of the layer.

Methods

adapt

View source

adapt(
    data, reset_state=True
)

Fits the state of the preprocessing layer to the data being passed.

Arguments
data	The data to train on. It can be passed either as a tf.data Dataset, or as a numpy array.
reset_state	Optional argument specifying whether to clear the state of the layer at the start of the call to adapt, or whether to start from the existing state. This argument may not be relevant to all preprocessing layers: a subclass of PreprocessingLayer may choose to throw if 'reset_state' is set to False.