How do I interpret inception score IS for evaluating image generation models

Question

With the help of proper code and explanation, can you tell me how I interpret the inception score (IS) for evaluating image generation models?

Answer 1

The Inception Score (IS) evaluates the quality and diversity of images generated by a model. It uses a pre-trained Inception model to compute the following:

• Quality: Generated images should correspond to clear, high-confidence class predictions.
• Diversity: The overall distribution of generated images should cover multiple classes.

Here is the formula you can refer to:

Where:

• p(y∣x)p(y|x)p(y∣x): Predicted class distribution for an image xxx.
• p(y)p(y)p(y): Marginal class distribution across all generated images.

Here is the code snippet you can refer to:

In the above code, we are using the following:

• Higher IS: Indicates better quality and diversity of generated images.
• Low IS: Suggests low-quality or repetitive outputs.
• Comparisons: Use IS to compare models, but note it may not fully capture image realism (e.g., context or fidelity).

Hence, this code provides a streamlined process to compute and interpret IS for image generation models.