Inception Score (compatible with Tensorflow 1.6+)

While the canonical OpenAI implementation of "Inception Score" for the evaluation of generative models is no longer compatible with new releases of Tensorflow, a new implementation of it is provided. Also, a bug raised in openai/improved-gan#29 is fixed.

Dependencies

• numpy and tensorflow-gpu

Features

• Fast, easy-to-use and memory-efficient, written in a way that is similar to the original implementation
• No prior knowledge about Tensorflow is necessary to use this code
• Makes use of TFGAN
• Downloads InceptionV1 automatically
• Compatible with both Python 2 and Python 3

Usage

• Call get_inception_score(images, splits=10), where images is a numpy array with values ranging from 0 to 255 and shape in the form [N, 3, HEIGHT, WIDTH] where N, HEIGHT and WIDTH can be arbitrary. dtype of the images is recommended to be np.uint8 to save CPU memory.
• A smaller BATCH_SIZE reduces GPU memory usage, but at the cost of a slight slowdown.
• If you want to compute a general "Classifier Score" with probabilities preds from another classifier, call preds2score(preds, splits=10). preds can be a numpy array of arbitrary shape [N, num_classes].

Links

• The Inception Score was proposed in the paper Improved Techniques for Training GANs
• Code for the Fréchet Inception Distance