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docs/gan/cycle_gan.html

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<h1>Cycle GAN</h1>
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<p>This is an implementation of paper
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<a href="https://arxiv.org/abs/1703.10593">Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks</a>.</p>
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<p>I&rsquo;ve taken pieces of code from <a href="https://github.com/eriklindernoren/PyTorch-GAN">https://github.com/eriklindernoren/PyTorch-GAN</a>.
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<p>I&rsquo;ve taken pieces of code from <a href="https://github.com/eriklindernoren/PyTorch-GAN">eriklindernoren/PyTorch-GAN</a>.
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It is a very good resource if you want to checkout other GAN variations too.</p>
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<p>Cycle GAN does image-to-image translation.
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It trains a model to translate an image from given distribution to another, say images of class A and B

labml_nn/gan/cycle_gan.py

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This is an implementation of paper
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[Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593).
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I've taken pieces of code from [https://github.com/eriklindernoren/PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN).
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I've taken pieces of code from [eriklindernoren/PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN).
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It is a very good resource if you want to checkout other GAN variations too.
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Cycle GAN does image-to-image translation.

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