tf.keras.layers.experimental.preprocessing.CenterCrop

Crop the central portion of the images to target height and width.

Inherits From: PreprocessingLayer, Layer, Module

View aliases

Compat aliases for migration

See Migration guide for more details.

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

tf.keras.layers.experimental.preprocessing.CenterCrop(
    height, width, name=None, **kwargs
)

Input shape:

4D tensor with shape: (samples, height, width, channels), data_format='channels_last'.

Output shape:

4D tensor with shape: (samples, target_height, target_width, channels).

If the input height/width is even and the target height/width is odd (or inversely), the input image is left-padded by 1 pixel.

Arguments
height	Integer, the height of the output shape.
width	Integer, the width of the output shape.
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.