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All Projects → znxlwm → pytorch-CycleGAN

znxlwm / pytorch-CycleGAN

Licence: other
Pytorch implementation of CycleGAN.

Programming Languages

python
139335 projects - #7 most used programming language

Labels

pytorchgenerative-adversarial-networkgangenerative-modelimage-translationcyclegan

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pytorch-CycleGAN

Pytorch implementation of CycleGAN [1].

dataset

  • apple2orange
    • apple training images: 995, orange training images: 1,019, apple test images: 266, orange test images: 248
  • horse2zebra
    • horse training images: 1,067, zebra training images: 1,334, horse test images: 120, zebra test images: 140

Resutls

apple2orange (after 200 epochs)

  • apple2orange
Input Output Reconstruction
  • orange2apple
Input Output Reconstruction
  • Learning Time
    • apple2orange - Avg. per epoch: 299.38 sec; Total 200 epochs: 62,225.33 sec

horse2zebra (after 200 epochs)

  • horse2zebra
Input Output Reconstruction
  • zebra2horse
Input Output Reconstruction
  • Learning Time
    • horse2zebra - Avg. per epoch: 299.25 sec; Total 200 epochs: 61,221.27 sec

Development Environment

  • Ubuntu 14.04 LTS
  • NVIDIA GTX 1080 ti
  • cuda 8.0
  • Python 2.7.6
  • pytorch 0.1.12
  • matplotlib 1.3.1
  • scipy 0.19.1

Reference

[1] Zhu, Jun-Yan, et al. "Unpaired image-to-image translation using cycle-consistent adversarial networks." arXiv preprint arXiv:1703.10593 (2017).

(Full paper: https://arxiv.org/pdf/1703.10593.pdf)

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