Pytorch was lacking code to calculate the Inception Score for GANs. This repository fills this gap.
Clone the repository and navigate to it:
$ git clone [email protected]:sbarratt/inception-score-pytorch.git
$ cd inception-score-pytorch
To generate random 64x64 images and calculate the inception score, do the following:
$ python inception_score.py
The only function is inception_score
. It takes a list of numpy images normalized to the range [0,1] and a set of arguments and then calculates the inception score. Please assure your images are 299x299x3 and if not (e.g. your GAN was trained on CIFAR), pass resize=True
to the function to have it automatically resize using bilinear interpolation before passing the images to the inception network.
def inception_score(imgs, cuda=True, batch_size=32, resize=False):
"""Computes the inception score of the generated images imgs
imgs -- list of (HxWx3) numpy images normalized in the range [0,1]
cuda -- whether or not to run on GPU
batch_size -- batch size to feed into inception
"""
You will need torch, torchvision, numpy/scipy.
This project is licensed under the MIT License - see the LICENSE.md file for details
- Inception Score from Improved Techniques for Training GANs