tf.keras.layers.experimental.preprocessing.RandomTranslation
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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'}).
- 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.
|
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'.
Output shape:
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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Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.keras.layers.experimental.preprocessing.RandomTranslation\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.3.0/tensorflow/python/keras/layers/preprocessing/image_preprocessing.py#L429-L571) |\n\nRandomly translate each image during training.\n\nInherits From: [`Layer`](../../../../../tf/keras/layers/Layer)\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.layers.experimental.preprocessing.RandomTranslation`](/api_docs/python/tf/keras/layers/experimental/preprocessing/RandomTranslation)\n\n\u003cbr /\u003e\n\n tf.keras.layers.experimental.preprocessing.RandomTranslation(\n height_factor, width_factor, fill_mode='reflect', interpolation='bilinear',\n seed=None, name=None, **kwargs\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Arguments --------- ||\n|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `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%\\]. |\n| `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%. |\n| `fill_mode` | Points outside the boundaries of the input are filled according to the given mode (one of `{'constant', 'reflect', 'wrap'}`). \u003cbr /\u003e - *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. |\n| `interpolation` | Interpolation mode. Supported values: \"nearest\", \"bilinear\". |\n| `seed` | Integer. Used to create a random seed. |\n| `name` | A string, the name of the layer. |\n\n#### Input shape:\n\n4D tensor with shape: `(samples, height, width, channels)`,\ndata_format='channels_last'.\n\n#### Output shape:\n\n4D tensor with shape: `(samples, height, width, channels)`,\ndata_format='channels_last'.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raise ----- ||\n|--------------|-----------------------------------------------------------------------------------|\n| `ValueError` | if either bound is not between \\[0, 1\\], or upper bound is less than lower bound. |\n\n\u003cbr /\u003e"]]
View source on GitHub