Keras 3 API documentation
Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Attention layers Reshaping layers Merging layers Activation layers Backend-specific layers Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization Utilities
Keras 2 API documentation
► Keras 3 API documentation / Layers API / Preprocessing layers / Image augmentation layers / CutMix layer

CutMix layer

[source]

CutMix class

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

CutMix data augmentation technique.

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.

Arguments

  • 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.

References

CutMix layer
CutMix class