Machine Learning

TensorFlow implementation of EigenGAN: Layer-Wise Eigen-Learning for GANs

EigenGAN

TensorFlow implementation of EigenGAN: Layer-Wise Eigen-Learning for GANs

EigenGAN

Usage

  • Environment

    • Python 3.6

    • TensorFlow 1.15

    • OpenCV, scikit-image, tqdm, oyaml

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

      conda create -n EigenGAN python=3.6

source activate EigenGAN

conda install opencv scikit-image tqdm tensorflow-gpu=1.15

conda install -c conda-forge oyaml

    • NOTICE: if you create a new conda environment, remember to activate it before any other command

      source activate EigenGAN
  • Data Preparation
    • CelebA-unaligned (10.2GB, higher quality than the aligned data)

      • download the dataset

      • unzip and process the data

        7z x ./data/img_celeba/img_celeba.7z/img_celeba.7z.001 -o./data/img_celeba/
        

        unzip ./data/img_celeba/annotations.zip -d ./data/img_celeba/
        

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