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You are developing a text-to-image generative model and want to evaluate the quality and diversity of the generated images. Which metric is MOST appropriate for assessing the diversity of generated images, considering computational efficiency is also important?
Correct Answer: B
FID is a commonly used metric for evaluating the quality and diversity of generated images, and it's more robust than IS. While LPIPS and MS-SSIM are useful for measuring perceptual similarity between images, they don't directly quantify diversity across a large set of generated images. Simply counting unique images doesn't capture the semantic diversity of the generated content. FID calculates the distance between the feature representations of real and generated images, capturing both quality and diversity.