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Image resizing layer.
Inherits From: PreprocessingLayer, Layer, Module
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
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.
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