ali-vilab/DiffDoctor
[ICCV 2025] DiffDoctor: Diagnosing Image Diffusion Models Before Treating
This project helps AI researchers and developers improve the quality of images generated by diffusion models. It takes an existing image diffusion model as input, identifies common flaws or 'artifacts' in its generated images, and then helps retrain the model to produce higher-quality, more realistic outputs. It's designed for machine learning engineers and researchers working on generative AI.
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Use this if you are developing or fine-tuning image diffusion models and want to systematically identify and fix common issues that lead to poor image quality or artifacts.
Not ideal if you are looking for a ready-to-use image generator or a tool to analyze images that were not created by a diffusion model.
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41
Forks
2
Language
Python
License
MIT
Category
Last pushed
Sep 09, 2025
Commits (30d)
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