TIGER-AI-Lab/ImagenHub
A one-stop library to standardize the inference and evaluation of all the conditional image generation models. [ICLR 2024]
This library helps researchers and practitioners working with AI image generation models to reliably compare how well different models perform. You feed in a text prompt or an existing image, and it generates an image from various models. The output includes the generated images and scores that tell you how semantically consistent and perceptually high-quality those images are. It's for anyone involved in developing, evaluating, or selecting conditional image generation models.
178 stars.
Use this if you need to systematically benchmark and compare the performance of multiple conditional image generation models against standardized tasks and metrics.
Not ideal if you are looking for an application to simply generate a single image for creative use without needing to compare models or evaluate their performance.
Stars
178
Forks
19
Language
Python
License
MIT
Category
Last pushed
Dec 02, 2025
Commits (30d)
0
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