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Pytorch implementation of the paper: OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization

Python 100.00%

oogan-pytorch's Introduction

OOGAN-pytorch

Pytorch implementation of the paper: OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization

Model overview: Alt text

OOGAN based on vanilla GAN

  1. code to define the networks: oogan_models.py, oogan_modules.py
  2. to train the model on your data, first prepare your images inside a root folder with subfolders containing your images, then edit the "config.py" for all hyperparameter settings, templetes are provided inside, then run
    python train.py
    the training will print log on terminal, and save the generated models and images during training.
  3. to generate images from trained model, first edit the model path in "generate.py", then run:
    python generate.py

Train results

On celebA: Alt text

On 3D chair: drawing drawing

On MNIST: drawing

On dSprite: drawing

OOGAN based on styleGAN

This implementation is based on the stylegan implementation from here, please refer to that repo for updated code and usage.

  1. code: ./oogan_stylegan/oo_stylegan_train.py, ./oogan_stylegan/oo_stylegan_modules.py
  2. to train the model on your data
    python oo_stylegan_train.py /path/to/image_root
    the training will print log on terminal and save the generated models and images during training.

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oogan-pytorch's Issues

What is the dist module?

While running the code, I got the error for "from dist import Normal" .
The error is "ModuleNotFoundError: No module named 'dist'". I couldn't find the dist module in anaconda. Please help me to figure it out the dist package issues.

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