tf.keras.layers.CutMix

CutMix data augmentation technique.

Inherits From: Layer, Operation

tf.keras.layers.CutMix(
    factor=1.0, seed=None, data_format=None, **kwargs
)

CutMix is a data augmentation method where patches are cut and pasted
between two images in the dataset, while the labels are also mixed
proportionally to the area of the patches.

Note: This layer is safe to use inside a <a href="../../../tf/data"><code>tf.data</code></a> or `grain` pipeline
(independently of which backend you're using).

References:

   - [CutMix paper]( https://arxiv.org/abs/1905.04899).

Args:
    factor: A single float or a tuple of two floats between 0 and 1.
        If a tuple of numbers is passed, a `factor` is sampled
        between the two values.
        If a single float is passed, a value between 0 and the passed
        float is sampled. These values define the range from which the
        mixing weight is sampled. A higher factor increases the variability
        in patch sizes, leading to more diverse and larger mixed patches.
        Defaults to 1.
    seed: Integer. Used to create a random seed.

Example:

layer = keras.layers.CutMix(value_range=(0, 255))
images = np.random.randint(0, 255, (8, 224, 224, 3), dtype="uint8")

labels = keras.ops.one_hot(
    np.array([0, 1, 2, 0, 1, 2, 0, 1]),
    num_classes=3
)

segmentation_masks = np.random.randint(0, 3, (8, 224, 224, 1), dtype="uint8")

output = layer(
    {
        "images": images,
        "labels": labels,
        "segmentation_masks": segmentation_masks
    },
    training=True
)

input Retrieves the input tensor(s) of a symbolic operation.

Only returns the tensor(s) corresponding to the first time the operation was called.

output Retrieves the output tensor(s) of a layer.

Only returns the tensor(s) corresponding to the first time the operation was called.

Methods

convert_weight

View source

convert_weight(
    weight
)

Convert the weight if it is from the a different backend.

from_config

View source

@classmethod
from_config(
    config
)

Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

Args
config A Python dictionary, typically the output of get_config.

Returns
An operation instance.

get_random_transformation

View source

get_random_transformation(
    data, training=True, seed=None
)

transform_bounding_boxes

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transform_bounding_boxes(
    bounding_boxes, transformation, training=True
)

transform_images

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transform_images(
    images, transformation=None, training=True
)

transform_labels

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transform_labels(
    labels, transformation, training=True
)

transform_segmentation_masks

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transform_segmentation_masks(
    segmentation_masks, transformation, training=True
)

transform_single_bounding_box

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transform_single_bounding_box(
    bounding_box, transformation, training=True
)

transform_single_image

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transform_single_image(
    image, transformation, training=True
)

transform_single_label

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transform_single_label(
    label, transformation, training=True
)

transform_single_segmentation_mask

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transform_single_segmentation_mask(
    segmentation_mask, transformation, training=True
)