[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution

Re-implement CycleGAN in Tensorlayer

Prerequisites:

  • Tensorlayer
  • TensorFlow
  • Python

Run:

CUDA_VISIBLE_DEVICES=0 python main.py 

(if datasets are collected by yourself, you can use dataset_clean.py or dataset_crop.py to pre-process images)

Theory:

The generator process:

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

The discriminator process:

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

Result Improvement

  • Data augmentation
  • Resize convolution[4]
  • Instance normalization[5]

data augmentation:

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

Instance normalization(comparision by original paper arxiv.org/abs/1607.08…:

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

Resize convolution (Remove Checkerboard Artifacts):

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

Final Results:

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

《[P] 图片到图片转换 Improved CycleGAN with Resize-Convolution》

Reference:

    原文作者:小蜜蜂
    原文地址: https://juejin.im/entry/59cb9c57f265da06470409b4
    本文转自网络文章,转载此文章仅为分享知识,如有侵权,请联系博主进行删除。
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