Randomly zoom each image during training.
Inherits From: Layer
tf.keras.layers.experimental.preprocessing.RandomZoom( height_factor, width_factor=None, fill_mode='reflect', interpolation='bilinear', seed=None, name=None, **kwargs )
Arguments  

height_factor  a float represented as fraction of value, or a tuple of size 2 representing lower and upper bound for zooming vertically. When represented as a single float, this value is used for both the upper and lower bound. A positive value means zooming out, while a negative value means zooming in. For instance, height_factor=(0.2, 0.3) result in an output zoomed out by a random amount in the range [+20%, +30%]. height_factor=(0.3, 0.2) result in an output zoomed in by a random amount in the range [+20%, +30%]. 
width_factor  a float represented as fraction of value, or a tuple of size 2 representing lower and upper bound for zooming horizontally. When represented as a single float, this value is used for both the upper and lower bound. For instance, width_factor=(0.2, 0.3) result in an output zooming out between 20% to 30%. width_factor=(0.3, 0.2) result in an output zooming in between 20% to 30%. Defaults to None , i.e., zooming vertical and horizontal directions by preserving the aspect ratio. 
fill_mode  Points outside the boundaries of the input are filled according to the given mode (one of {'constant', 'reflect', 'wrap'} ).

interpolation  Interpolation mode. Supported values: "nearest", "bilinear". 
seed  Integer. Used to create a random seed. 
name  A string, the name of the layer. 
input_img = np.random.random((32, 224, 224, 3)) layer = tf.keras.layers.experimental.preprocessing.RandomZoom(.5, .2) out_img = layer(input_img) out_img.shape TensorShape([32, 224, 224, 3])
4D tensor with shape: (samples, height, width, channels)
, data_format='channels_last'.
4D tensor with shape: (samples, height, width, channels)
, data_format='channels_last'.
Raise  

ValueError  if lower bound is not between [0, 1], or upper bound is negative. 
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/layers/experimental/preprocessing/RandomZoom