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ImageAugmentationLayer[{h,w}]

represents a net layer that applies random image transformations to produce images of height h and width w.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Options  
"ReflectionProbabilities"  
Possible Issues  
See Also
Tech Notes
Related Guides
History
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ImageAugmentationLayer

ImageAugmentationLayer[{h,w}]

represents a net layer that applies random image transformations to produce images of height h and width w.

Details and Options

Examples

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Basic Examples  (2)

Create an ImageAugmentationLayer whose output dimensions are {n,80,80}:

Create an ImageAugmentationLayer that takes an image of size 128×128 and returns an image crop of size 80×80:

Apply the layer to an image, obtaining the center crop:

Apply the layer to an image, specifying that training behavior be used:

The layer threads across a batch of examples:

Options  (1)

"ReflectionProbabilities"  (1)

Create an ImageAugmentationLayer that randomly reflects an image about the vertical axis with probability 0.9 during training:

Apply the layer to an image, using training behavior:

The layer threads across a batch of examples:

Possible Issues  (1)

Currently, any randomness invoked by NetEvaluationMode->"Train" is not affected by SeedRandom and BlockRandom:

Compare with BlockRandom generating random reals:

Wolfram Research (2017), ImageAugmentationLayer, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html.

Text

Wolfram Research (2017), ImageAugmentationLayer, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html.

CMS

Wolfram Language. 2017. "ImageAugmentationLayer." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html.

APA

Wolfram Language. (2017). ImageAugmentationLayer. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html

BibTeX

@misc{reference.wolfram_2025_imageaugmentationlayer, author="Wolfram Research", title="{ImageAugmentationLayer}", year="2017", howpublished="\url{https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html}", note=[Accessed: 01-December-2025]}

BibLaTeX

@online{reference.wolfram_2025_imageaugmentationlayer, organization={Wolfram Research}, title={ImageAugmentationLayer}, year={2017}, url={https://reference.wolfram.com/language/ref/ImageAugmentationLayer.html}, note=[Accessed: 01-December-2025]}