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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’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’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
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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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