taki0112/GAN_Metrics-Tensorflow taki0112/GAN_Metrics-Tensorflow

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taki0112/GAN_Metrics-Tensorflow
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Simple Tensorflow implementation of metrics for GAN evaluation (Inception score, Frechet-Inception distance, Kernel-Inception distance)

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

β”œβ”€β”€ real_source 
    β”œβ”€β”€ aaa.png
    β”œβ”€β”€ bbb.jpg
β”œβ”€β”€ real_target 
    β”œβ”€β”€ ccc.png
    β”œβ”€β”€ ddd.jpg
β”œβ”€β”€ fake 
    β”œβ”€β”€ ccc_fake.png
    β”œβ”€β”€ ddd_fake.jpg
β”œβ”€β”€ main.py
β”œβ”€β”€ inception_score.py
└── frechet_kernel_Inception_distance.py

> python main.py

Reference

Author

Junho Kim

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