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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
| Date | Stars |
|---|---|
| 2026-07-24 | 5629 |
| 2026-07-25 | 5629 |
| 2026-07-28 | 5629 |
| 2026-07-30 | 5629 |
| 2026-08-06 | 5629 |
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## (CVPR2024) Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
> [[Paper](https://arxiv.org/abs/2401.13627)]   [[Project Page](http://supir.xpixel.group/)]   [[Online App]](https://supir.suppixel.ai/home) <br>
> Fanghua, Yu, [Jinjin Gu](https://www.jasongt.com/), Zheyuan Li, Jinfan Hu, Xiangtao Kong, [Xintao Wang](https://xinntao.github.io/), [Jingwen He](https://scholar.google.com.hk/citations?user=GUxrycUAAAAJ), [Yu Qiao](https://scholar.google.com.hk/citations?user=gFtI-8QAAAAJ), [Chao Dong](https://scholar.google.com.hk/citations?user=OSDCB0UAAAAJ) <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>
<p align="center">
<img src="assets/teaser.png">
</p>
---
#### 🚀 We're thrilled to announce the official launch of SupPixel AI! Experience the next level of image processing and upscaling with our cutting-edge AI technology based on SUPIR. Explore now at [suppixel.ai](https://supir.suppixel.ai/home).
---
## 🔧 Dependencies and Installation
1. Clone repo
```bash
git clone https://github.com/Fanghua-Yu/SUPIR.git
cd SUPIR
```
2. Install dependent packages
```bash
conda create -n SUPIR python=3.8 -y
conda activate SUPIR
pip install --upgrade pip
pip install -r requirements.txt
```
3. Download Checkpoints
For users who can connect to huggingface, please setting `LLAVA_CLIP_PATH, SDXL_CLIP1_PATH, SDXL_CLIP2_CKPT_PTH` in `CKPT_PTH.py` as `None`. These CLIPs will be downloaded automatically.
#### Dependent Models
* [SDXL CLIP Encoder-1](https://huggingface.co/openai/clip-vit-large-patch14)
* [SDXL CLIP Encoder-2](https://huggingface.co/laion/CLIP-ViT-bigG-14-laion2B-39B-b160k)
* [SDXL base 1.0_0.9vae](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0_0.9vae.safetensors)
* [LLaVA CLIP](https://huggingface.co/openai/clip-vit-large-patch14-336)
* [LLaVA v1.5 13B](https://huggingface.co/liuhaotian/llava-v1.5-13b)
* (optional) [Juggernaut-XL_v9_RunDiffusionPhoto_v2](https://huggingface.co/RunDiffusion/Juggernaut-XL-v9/blob/main/Juggernaut-XL_v9_RunDiffusionPhoto_v2.safetensors)
* Replacement of `SDXL base 1.0_0.9vae` for Photo Realistic
* (optional) [Juggernaut_RunDiffusionPhoto2_Lightning_4Steps](https://huggingface.co/RunDiffusion/Juggernaut-XL-Lightning/blob/main/Juggernaut_RunDiffusionPhoto2_Lightning_4Steps.safetensors)
* Distilling model used in `SUPIR_v0_Juggernautv9_lightning.yaml`
#### Models we provided:
* `SUPIR-v0Q`: [Baidu Netdisk](https://pan.baidu.com/s/1lnefCZhBTeDWijqbj1jIyw?pwd=pjq6), [Google Drive](https://drive.google.com/drive/folders/1yELzm5SvAi9e7kPcO_jPp2XkTs4vK6aR?usp=sharing)
Default training settings with paper. High generalization and high image quality in most cases.
* `SUPIR-v0F`: [Baidu Netdisk](https://pan.baidu.com/s/1AECN8NjiVuE3hvO8o-Ua6A?pwd=k2uz), [Google Drive](https://drive.google.com/drive/folders/1yELzm5SvAi9e7kPcO_jPp2XkTs4vK6aR?usp=sharing)
Training with light degradation settings. Stage1 encoder of `SUPIR-v0F` remains more details when facing light degradations.
4. Edit Custom Path for Checkpoints
```
* [CKPT_PTH.py] --> LLAVA_CLIP_PATH, LLAVA_MODEL_PATH, SDXL_CLIP1_PATH, SDXL_CLIP2_CACHE_DIR
* [options/SUPIR_v0.yaml] --> SDXL_CKPT, SUPIR_CKPT_Q, SUPIR_CKPT_F
```
---
## ⚡ Quick Inference
### Val Dataset
RealPhoto60: [Baidu Netdisk](https://pan.baidu.com/s/1CJKsPGtyfs8QEVCQ97voBA?pwd=aocg), [Google Drive](https://drive.google.com/drive/folders/1yELzm5SvAi9e7kPcO_jPp2XkTs4vK6aR?usp=sharing)
### Usage of SUPIR
```Shell
Usage:
-- python test.py [options]
-- python gradio_demo.py [interactive options]
--img_dir Input folder.
--save_dir Output folder.
--upscale Upsampling ratio of given inputs. Default: 1
--SUPIR_sign Excerpt of 9,843 characters
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Ikko Eltociear Ashimine · Japan
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:16aa19cf995aba3e, topic:stable-diffusion, topic:diffusion-models, topic:super-resolution
matched fp:16aa19cf995aba3e, topic:deep-learning, topic:pytorch