PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)

Related tags

Deep Learning pytorch mnist svhn domain-transfer cycle-gan semi-supervised-gan
Overview

MNIST-to-SVHN and SVHN-to-MNIST

PyTorch Implementation of CycleGAN and Semi-Supervised GAN for Domain Transfer.

alt text

Prerequites


Usage

Clone the repository

$ git clone https://github.com/yunjey/mnist-svhn-transfer.git
$ cd mnist-svhn-transfer/

Download the dataset

$ chmod +x download.sh
$ ./download.sh

Train the model

1) CycleGAN
$ python main.py --use_labels=False --use_reconst_loss=True
2) SGAN
$ python main.py --use_labels=True --use_reconst_loss=False

Results

1) CycleGAN (should be re-uploaded)

From SVHN to MNIST From MNIST to SVHN
alt text alt text
alt text alt text

2) SGAN

From SVHN to MNIST From MNIST to SVHN
alt text alt text
alt text alt text
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Comments
  • implementation problems here

    implementation problems here

    I found two problems about the code. First, the reconstruction loss should be L1 loss instead of L2, according to cycleGAN's paper. Second, the generator and discriminator should update simutaneously, while in the code it firstly update discriminator and then use updated discriminator to update generator, which is wrong.

    opened by Ledzy 0
  • So is this code actually working?

    So is this code actually working?

    So is this code actually working? Readme says "(should be re-uploaded)", What does that mean? Some people here report that this code is just memorizing training examples but does not generalize. Is this true?

    Even worse than having no code is having code that is pretending to work but will just waste your time and then you have to implement it from scratch anyway...

    opened by mario98 9
  • the result is very pool

    the result is very pool

    when i run your code about cyclegan svhn to mnist，i find the result is very pool，maybe the sample example is good，but，the test examples is pool. for example ,it can translate 8 to 5, 2 to 0,the correct rate of the generate mnist is about 25%,when the correct rate about train mnist classify is 99%.

    opened by daishuolove 1
  • testing code

    testing code

    Hi, thanks for sharing the well-written code. Could you please also share the testing code? I have successfully trained the model, now I just want to test it on the validation set.

    opened by juntingzh 1
Owner
Yunjey Choi
Yunjey Choi
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