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News

  • We re-implement CycleGAN by Tensorflow 2! The old versions are here: v1, v0.


CycleGAN - Tensorflow 2

Tensorflow 2 implementation of CycleGAN.

Paper: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Author: Jun-Yan Zhu et al.

Exemplar results

summer2winter

row 1: summer -> winter -> reconstructed summer, row 2: winter -> summer -> reconstructed winter

horse2zebra

row 1: horse -> zebra -> reconstructed horse, row 2: zebra -> horse -> reconstructed zebra

apple2orange

row 1: apple -> orange -> reconstructed apple, row 2: orange -> apple -> reconstructed orange

Usage

  • Environment

    • Python 3.6

    • TensorFlow 2.2, TensorFlow Addons 0.10.0

    • OpenCV, scikit-image, tqdm, oyaml

    • we recommend Anaconda or Miniconda, then you can create the TensorFlow 2.2 environment with commands below

      conda create -n tensorflow-2.2 python=3.6
      
      source activate tensorflow-2.2
      
      conda install scikit-image tqdm tensorflow-gpu=2.2
      
      conda install -c conda-forge oyaml
      
      pip install tensorflow-addons==0.10.0
    • NOTICE: if you create a new conda environment, remember to activate it before any other command

      source activate tensorflow-2.2
  • Dataset

    • download the summer2winter dataset

      sh ./download_dataset.sh summer2winter_yosemite
    • download the horse2zebra dataset

      sh ./download_dataset.sh horse2zebra
    • see download_dataset.sh for more datasets

  • Example of training

    CUDA_VISIBLE_DEVICES=0 python train.py --dataset summer2winter_yosemite
    • tensorboard for loss visualization

      tensorboard --logdir ./output/summer2winter_yosemite/summaries --port 6006
  • Example of testing

    CUDA_VISIBLE_DEVICES=0 python test.py --experiment_dir ./output/summer2winter_yosemite