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Showing content from https://keras.io/api/layers/preprocessing_layers/image_preprocessing/resizing below:

Resizing layer

Resizing layer

[source]

Resizing class
keras.layers.Resizing(
    height,
    width,
    interpolation="bilinear",
    crop_to_aspect_ratio=False,
    pad_to_aspect_ratio=False,
    fill_mode="constant",
    fill_value=0.0,
    antialias=False,
    data_format=None,
    **kwargs
)

A preprocessing layer which resizes images.

This layer resizes an image input to a target height and width. The input should be a 4D (batched) or 3D (unbatched) tensor in "channels_last" format. Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]).

Input shape

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

Output shape

3D (unbatched) or 4D (batched) tensor with shape: (..., target_height, target_width, channels), or (..., channels, target_height, target_width), in "channels_first" format.

Note: This layer is safe to use inside a tf.data pipeline (independently of which backend you're using).

Arguments


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