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Simple Tensorflow implementation of metrics for GAN evaluation (Inception score, Frechet-Inception distance, Kernel-Inception distance)
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README.md

GAN_Metrics-Tensorflow

Simple Tensorflow implementation of metrics for GAN evaluation

  • Inception score
  • Frechet-Inception distance
  • Kernel-Inception distance

Summary

Name Description Performance score
Inception score KL-Divergence between conditional and marginal label distributions over generated data. Higher is better.
Frechet-Inception distance Wasserstein-2 distance between multi-variate Gaussians fitted to data embedded into a feature space. Lower is better.
Kernel-Inception distance Measures the dissimilarity between two probability distributions Pr and Pg using samples drawn independently from each distribution. Lower is better.

Usage

├── real_source 
    ├── aaa.png
    ├── bbb.jpg
├── real_target 
    ├── ccc.png
    ├── ddd.jpg
├── fake 
    ├── ccc_fake.png
    ├── ddd_fake.jpg
├── main.py
├── inception_score.py
└── frechet_kernel_Inception_distance.py
> python main.py

Reference

Author

Junho Kim

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