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A preprocessing layer which resizes images.
tf.keras.layers.Resizing(
height,
width,
interpolation='bilinear',
crop_to_aspect_ratio=False,
**kwargs
)
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]
) and of integer or floating point dtype.
By default, the layer will output floats.
This layer can be called on tf.RaggedTensor batches of input images of distinct sizes, and will resize the outputs to dense tensors of uniform size.
For an overview and full list of preprocessing layers, see the preprocessing guide.