huggingface/diffusers

Add SUPIR Upscaler

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#7,219 创建于 2024年3月5日

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 (36 评论) (14 反应) (0 负责人)Python (22,190 star) (4,562 fork)batch import
New pipeline/modelcontributions-welcomehelp wanted

描述

Model/Pipeline/Scheduler description

SUPIR is a super-resolution model that looks like it produces excellent results

Github Repo: https://github.com/Fanghua-Yu/SUPIR

The model is quite memory intensive, so the optimisation features available in diffusers might be quite helpful in making this accessible to lower resource GPUs.

Open source status

  • The model implementation is available.
  • The model weights are available (Only relevant if addition is not a scheduler).

Provide useful links for the implementation

No response

贡献者指南

技术栈
pythonpytorch
领域
machine learningai
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
4
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
over 1 week
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
active
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
PyTorch knowledgediffusers codebase familiaritydiffusion model basics
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
25
研究方向
Start by examining existing diffusion pipelines in the `src/diffusers/pipelines` directory, particularly similar upscaling pipelines like `stable diffusion` or `controlnet`. Review the SUPIR model architecture in its GitHub repository to understand the components needed. The issue mentions memory constraints, so consider implementing with support for feature extraction offloading or using `torch.compile` for optimization.