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

Last update: Dec 30, 2022

Overview

MNIST-to-SVHN and SVHN-to-MNIST

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

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

2) SGAN

From SVHN to MNIST	From MNIST to SVHN

Owner

Yunjey Choi

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

Related tags

Overview

MNIST-to-SVHN and SVHN-to-MNIST

Prerequites

Usage

Clone the repository

Download the dataset

Train the model

1) CycleGAN

2) SGAN

Results

1) CycleGAN (should be re-uploaded)

2) SGAN

Owner

Yunjey Choi

Logistic Bandit experiments. Official code for the paper "Jointly Efficient and Optimal Algorithms for Logistic Bandits".

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