Image domain conversion using CycleGAN

MATLAB example of deep learning for image domain conversion
Updated 11 Jun 2020

This example shows how to convert images from one domain into another using CycleGAN
CycleGAN is a GAN model that is generally used for the following purposes.
-Style transfer (images and paintings)
-Season conversion
-Day / night conversion
-Object transformation
The difference from Pix2Pix, which also perform image-image conversion, is that CycleGAN uses unsupervised learning, so there is no need for a paired image dataset. In this example, even with unsupervised learning, you can see the model convert the images by understanding whether the fruit was a whole one or a cut one.



Cite As

Takuji Fukumoto (2024). Image domain conversion using CycleGAN (, GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.