Ideogram-4 结合 Modular Diffusers 实现高质量图像修复
原标题：IDEOGRAM-4 for inpainting with Modular Diffusers and Differential Diffusion
AI 摘要
Hugging Face 博客介绍了 Ideogram-4 模型在 Modular Diffusers 框架下的图像修复（inpainting）功能，通过自定义差分扩散模块实现精细控制。文章展示了如何使用 ModularPipeline 加载模型，并利用组卸载（group offloading）和 SDNQ 量化模型在 24GB 消费级 GPU 上运行。该集成支持文本到图像、图像到图像和修复任务，提升了图像编辑的质量和灵活性。
正文节选
As an example, let's take this image where I added 3 new objects and modified another one. For me, this is the best inpainting quality I have seen so far. You can unfold the original image to compare the results. Photo by roam in color on Unsplash What differentiates Ideogram-4 from other models, aside from the quality, is the fine-grained control we have over the inpainting process. For example, it is trivial to move objects or change their order when you have a UI to manipulate the bounding bo