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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

demo

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An empirical study on evaluation metrics of generative adversarial networks.

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