/COCO-GAN

PyTorch implementation of COCO-GAN (https://hubert0527.github.io/COCO-GAN/)

Primary LanguagePythonMIT LicenseMIT

COCO_GAN

Implementation of Paper 'COCO-GAN: Generation by Parts via Conditional Coordinating' This code is PyTorch converted version of author's TensorFlow code present here : https://github.com/hubert0527/COCO-GAN

(The structure of the code is kept very similar to the author's repository, refer https://hubert0527.github.io/COCO-GAN/ for detailed descriptions)

Prerequisite

Torch
TorchVision
Numpy
Matplotlib

Train the Network

To train the network, e.g. with coco-gan, you can execute the following command:

python main.py

Config file can be edited according to the need !

Dataset

"celeb_data" can be downloaded from this link : https://drive.google.com/open?id=1PceubRgNbDhTExEFSfHuB4fKsOibDKQy This contains only 1000 randomly sampled images

For "MNIST" data, code is already present in the 'main' file under 'load_dataset'

Reference

@inproceedings{lin2019cocogan, author = {Chieh Hubert Lin and Chia{-}Che Chang and Yu{-}Sheng Chen and Da{-}Cheng Juan and Wei Wei and Hwann{-}Tzong Chen}, title = {{COCO-GAN:} Generation by Parts via Conditional Coordinating}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2019}, }