Randomly translate each image during training.
Inherits From: Layer
tf.keras.layers.experimental.preprocessing.RandomTranslation( height_factor, width_factor, 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 shifting vertically. A negative value means shifting image up, while a positive value means shifting image down. When represented as a single positive float, this value is used for both the upper and lower bound. For instance, height_factor=(-0.2, 0.3) results in an output shifted by a random amount in the range [-20%, +30%]. height_factor=0.2 results in an output height shifted by a random amount in the range [-20%, +20%]. |
width_factor | a float represented as fraction of value, or a tuple of size 2 representing lower and upper bound for shifting horizontally. A negative value means shifting image left, while a positive value means shifting image right. When represented as a single positive float, this value is used for both the upper and lower bound. For instance, width_factor=(-0.2, 0.3) results in an output shifted left by 20%, and shifted right by 30%. width_factor=0.2 results in an output height shifted left or right by 20%. |
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. |
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 either bound is not between [0, 1], or upper bound is less than lower bound. |
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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/RandomTranslation