xuqiantong/GAN-Metrics
An empirical study on evaluation metrics of generative adversarial networks.
| repo name | xuqiantong/GAN-Metrics |
| repo link | https://github.com/xuqiantong/GAN-Metrics |
| homepage | https://arxiv.org/abs/1806.07755 |
| language | Jupyter Notebook |
| size (curr.) | 48528 kB |
| stars (curr.) | 264 |
| created | 2018-06-10 |
| license | |
GAN Metrics
This repository provides the code for An empirical study on evaluation metrics of generative adversarial networks.
Requirement
- Python 3.6.4
- torch 0.4.0
- torchvision 0.2.1
- pot 0.4.0
- tqdm 4.19.6
- numpy, scipy, math
Usage
- We create a demo for DCGAN training as well as computing all the metrics after each epoch.
In the demo, final metrics scores of all epoches will be scored in<outf>/score_tr_ep.npy - If you want to compute metrics of your own images, you have to modify the codes of function
compute_score_raw()inmetric.pyby yourself :)
python3 demo_dcgan.py \
--dataset cifar10 \
--cuda \
--dataroot <data_folder> \
--outf <output_folder> \
--sampleSize 2000
