tf.keras.layers.RandomZoom
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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 integer 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%. None means
i.e., zooming vertical and horizontal directions
by preserving the aspect ratio. Defaults to None .
|
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.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
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