Fanghua-Yu/SUPIR

• highreadme#1

  Reposition README's opening to clarify project type and audience

  原因：

  当前

  ## (CVPR2024) Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
  > [Paper] &emsp; [Project Page] &emsp; [[Online App]](https://supir.suppixel.ai/home) <br>
  > Fanghua, Yu, Jinjin Gu, Zheyuan Li, Jinfan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, Chao Dong <br>
  > Shenzhen Institute of Advanced Technology; Shanghai AI Laboratory; University of Sydney; The Hong Kong Polytechnic University; ARC Lab, Tencent PCG; The Chinese University of Hong Kong <br>

  复制粘贴的修复

  复制

  SUPIR is an open-source framework for **photo-realistic image restoration and super-resolution in the wild**, designed for researchers and developers. It provides practical algorithms leveraging diffusion models to achieve state-of-the-art results, powering applications like SupPixel AI.
  
  ## (CVPR2024) Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
  > [Paper] &emsp; [Project Page] &emsp; [[Online App]](https://supir.suppixel.ai/home) <br>
  > Fanghua, Yu, Jinjin Gu, Zheyuan Li, Jinfan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, Chao Dong <br>
  > Shenzhen Institute of Advanced Technology; Shanghai AI Laboratory; University of Sydney; The Hong Kong Polytechnic University; ARC Lab, Tencent PCG; The Chinese University of Hong Kong <br>

  待办完成忽略
• mediumtopics#2

  Add more specific topics to improve categorization

  原因：

  当前

  deep-learning, diffusion-models, llava, pytorch, pytorch-lightning, restoration, sdxl, stable-diffusion, super-resolution

  复制粘贴的修复

  复制

  deep-learning, diffusion-models, llava, pytorch, pytorch-lightning, restoration, sdxl, stable-diffusion, super-resolution, image-restoration-model, generative-ai-models, photo-restoration, real-world-image-restoration, computer-vision-models

  待办完成忽略
• lowlicense#3

  Clarify the existing license in the README

  原因：

  复制粘贴的修复

  复制

  ## License 
   This project is released under the terms specified in the [LICENSE](LICENSE) file. Please review the LICENSE file for specific conditions regarding use, modification, and distribution.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How can I achieve high-quality, photo-realistic image restoration for diverse real-world photos?

  你：未被推荐
  AI 推荐顺序：

  1. Adobe Photoshop
  2. Topaz Photo AI
  3. Luminar Neo
  4. Remini
  5. GFPGAN
  6. CodeFormer
  7. Stable Diffusion
  8. Midjourney

  AI 推荐了 8 个替代方案，却始终没点名 Fanghua-Yu/SUPIR。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the best deep learning models for super-resolution and image enhancement using diffusion?

  你：未被推荐
  AI 推荐顺序：

  1. Stable Diffusion
  2. ControlNet
  3. SwinIR
  4. SR3
  5. Palette
  6. DDPM
  7. Latent Diffusion Models

  AI 推荐了 7 个替代方案，却始终没点名 Fanghua-Yu/SUPIR。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of Fanghua-Yu/SUPIR?

  pass
  ✓AI 明确点名了 Fanghua-Yu/SUPIR

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts Fanghua-Yu/SUPIR in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 Fanghua-Yu/SUPIR

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo Fanghua-Yu/SUPIR solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 Fanghua-Yu/SUPIR

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？