xuqiantong / GAN-Metrics

An empirical study on evaluation metrics of generative adversarial networks.

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() in metric.py by yourself :)

python3 demo_dcgan.py \
--dataset cifar10 \
--cuda \
--dataroot <data_folder> \
--outf <output_folder> \
--sampleSize 2000