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CycleGAN implementation (apples to oranges)

09/05/2022

While working on unpaired style transfer:
Implementation of the Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks paper by Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros with the help of educational resources.

The model translates apple pictures to the corresponding orange pictures.
Made with Python and Keras.

Results on test data:

617746-a1b3ac4ecbb13127 Screen Shot 2022-09-05 at 10 48 31 AM

The model uses:

  • a cycle consistency, identity and reconstruction loss
  • Instance normalization instead of batch normalization
  • a PatchGAN discriminator, which only penalizes structure at the scale of image patches rather than the whole image.
  • a U-Net generator (encoder-decoder architecture with skip connections)

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