tf.keras.layers.RandomContrast
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A preprocessing layer which randomly adjusts contrast during training.
Inherits From: Layer, Module
tf.keras.layers.RandomContrast(
factor, seed=None, **kwargs
)
This layer will randomly adjust the contrast of an image or images by a random
factor. Contrast is adjusted independently for each channel of each image
during training.
For each channel, this layer computes the mean of the image pixels in the
channel and then adjusts each component x of each pixel to
(x - mean) * contrast_factor + mean.
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.
|
|---|
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.
|
Args |
|---|
seed
|
optional integer, used to create RandomGenerator.
|
force_generator
|
boolean, default to False, whether to force the
RandomGenerator to use the code branch of tf.random.Generator.
|
**kwargs
|
other keyword arguments that will be passed to the parent class
|
Attributes |
|---|
factor
|
a positive float represented as fraction of value, or a tuple of
size 2 representing lower and upper bound. When represented as a single
float, lower = upper. The contrast factor will be randomly picked between
[1.0 - lower, 1.0 + upper].
|
seed
|
Integer. Used to create a random seed.
|
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Last updated 2022-09-07 UTC.
[null,null,["Last updated 2022-09-07 UTC."],[],[],null,["# tf.keras.layers.RandomContrast\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v2.8.0/keras/layers/preprocessing/image_preprocessing.py#L1121-L1201) |\n\nA preprocessing layer which randomly adjusts contrast during training.\n\nInherits From: [`Layer`](../../../tf/keras/layers/Layer), [`Module`](../../../tf/Module)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.layers.experimental.preprocessing.RandomContrast`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/RandomContrast)\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.RandomContrast\\`, \\`tf.compat.v1.keras.layers.experimental.preprocessing.RandomContrast\\`\n\n\u003cbr /\u003e\n\n tf.keras.layers.RandomContrast(\n factor, seed=None, **kwargs\n )\n\nThis layer will randomly adjust the contrast of an image or images by a random\nfactor. Contrast is adjusted independently for each channel of each image\nduring training.\n\nFor each channel, this layer computes the mean of the image pixels in the\nchannel and then adjusts each component `x` of each pixel to\n`(x - mean) * contrast_factor + mean`.\n\nInput pixel values can be of any range (e.g. `[0., 1.)` or `[0, 255]`) and\nof interger or floating point dtype. By default, the layer will output floats.\n\nFor an overview and full list of preprocessing layers, see the preprocessing\n[guide](https://www.tensorflow.org/guide/keras/preprocessing_layers).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Input shape ----------- ||\n|---|---|\n| 3D (unbatched) or 4D (batched) tensor with shape: `(..., height, width, channels)`, in `\"channels_last\"` format. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Output shape ------------ ||\n|---|---|\n| 3D (unbatched) or 4D (batched) tensor with shape: `(..., height, width, channels)`, in `\"channels_last\"` format. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------------|----------------------------------------------------------------------------------------------------------------|\n| `seed` | optional integer, used to create RandomGenerator. |\n| `force_generator` | boolean, default to False, whether to force the RandomGenerator to use the code branch of tf.random.Generator. |\n| `**kwargs` | other keyword arguments that will be passed to the parent class |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `factor` | a positive float represented as fraction of value, or a tuple of size 2 representing lower and upper bound. When represented as a single float, lower = upper. The contrast factor will be randomly picked between `[1.0 - lower, 1.0 + upper]`. |\n| `seed` | Integer. Used to create a random seed. |\n\n\u003cbr /\u003e"]]
View source on GitHub