A preprocessing layer which randomly zooms images during training.
Inherits From: Layer, Module
tf.keras.layers.RandomZoom(
    height_factor,
    width_factor=None,
    fill_mode='reflect',
    interpolation='bilinear',
    seed=None,
    fill_value=0.0,
    **kwargs
)
This layer will randomly zoom in or out on each axis of an image
independently, filling empty space according to fill_mode.
Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]) and
of interger or floating point dtype. By default, the layer will output floats.
For an overview and full list of preprocessing layers, see the preprocessing
guide.
Args | 
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", "nearest"}).
- reflect: 
(d c b a | a b c d | d c b a) The input is extended by
reflecting about the edge of the last pixel. 
- constant: 
(k k k k | a b c d | k k k k) The input is extended by
filling all values beyond the edge with the same constant value k = 0. 
- wrap: 
(a b c d | a b c d | a b c d) The input is extended by
wrapping around to the opposite edge. 
- nearest: 
(a a a a | a b c d | d d d d) The input is extended by the
nearest pixel.
   | 
interpolation
 | 
Interpolation mode. Supported values: "nearest",
"bilinear".
 | 
seed
 | 
Integer. Used to create a random seed.
 | 
fill_value
 | 
a float represents the value to be filled outside the boundaries
when fill_mode="constant".
 | 
Example:
input_img = np.random.random((32, 224, 224, 3))
layer = tf.keras.layers.RandomZoom(.5, .2)
out_img = layer(input_img)
out_img.shape
TensorShape([32, 224, 224, 3])
 | 
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.
 | 
Output shape | 
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.
 |