| # StableSR for Stable Diffusion WebUI | |
| Licensed under S-Lab License 1.0 | |
| [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa] | |
| English｜[中文](README_CN.md) | |
| - StableSR is a competitive super-resolution method originally proposed by Jianyi Wang et al. | |
| - This repository is a migration of the StableSR project to the Automatic1111 WebUI. | |
| Relevant Links | |
| > Click to view high-quality official examples! | |
| - [Project Page](https://iceclear.github.io/projects/stablesr/) | |
| - [Official Repository](https://github.com/IceClear/StableSR) | |
| - [Paper on arXiv](https://arxiv.org/abs/2305.07015) | |
| > If you find this project useful, please give me & Jianyi Wang a star! ⭐ | |
| *** | |
| ## Features | |
| 1. **High-fidelity detailed image upscaling**: | |
| - Being very detailed while keeping the face identity of your characters. | |
| - Suitable for most images (Realistic or Anime, Photography or AIGC, SD 1.5 or Midjourney images...) [Official Examples](https://iceclear.github.io/projects/stablesr/) | |
| 2. **Less VRAM consumption** | |
| - I remove the VRAM-expensive modules in the official implementation. | |
| - The remaining model is much smaller than ControlNet Tile model and requires less VRAM. | |
| - When combined with Tiled Diffusion & VAE, you can do 4k image super-resolution with limited VRAM (e.g., < 12 GB). | |
| > Please be aware that sdp may lead to OOM for some unknown reasons. You may use xformers instead. | |
| 3. **Wavelet Color Fix** | |
| - The official StableSR will significantly change the color of the generated image. The problem will be even more prominent when upscaling in tiles. | |
| - I implement a powerful post-processing technique that effectively matches the color of the upscaled image to the original. See [Wavelet Color Fix Example](https://imgsli.com/MTgwNDg2/). | |
| *** | |
| ## Usage | |
| ### 1. Installation | |
| ⚪ Method 1: Official Market | |
| - Open Automatic1111 WebUI -> Click Tab "Extensions" -> Click Tab "Available" -> Find "StableSR" -> Click "Install" | |
| ⚪ Method 2: URL Install | |
| - Open Automatic1111 WebUI -> Click Tab "Extensions" -> Click Tab "Install from URL" -> type in https://github.com/pkuliyi2015/sd-webui-stablesr.git -> Click "Install" | |
|  | |
| ### 2. Download the main components | |
| - You MUST use the Stable Diffusion V2.1 512 **EMA** checkpoint (~5.21GB) from StabilityAI | |
| - You can download it from [HuggingFace](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) | |
| - Put into stable-diffusion-webui/models/Stable-Diffusion/ | |
| > While it requires a SD2.1 checkpoint, you can still upscale ANY image (even from SD1.5 or NSFW). Your image won't be censored and the output quality won't be affected. | |
| - Download the extracted StableSR module | |
| - Official resources: [HuggingFace](https://huggingface.co/Iceclear/StableSR/resolve/main/weibu_models.zip) (~1.2 G). Note that this is a zip file containing both the StableSR module and the VQVAE. | |
| - My resources: <[GoogleDrive](https://drive.google.com/file/d/1tWjkZQhfj07sHDR4r9Ta5Fk4iMp1t3Qw/view?usp=sharing)> <[百度网盘-提取码aguq](https://pan.baidu.com/s/1Nq_6ciGgKnTu0W14QcKKWg?pwd=aguq)> | |
| - Put the StableSR module (~400MB) into your stable-diffusion-webui/extensions/sd-webui-stablesr/models/ | |
| ### 3. Optional components | |
| - Install [Tiled Diffusion & VAE]((https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111)) extension | |
| - The original StableSR easily gets OOM for large images > 512. | |
| - For better quality and less VRAM usage, we recommend Tiled Diffusion & VAE. | |
| - Use the Official VQGAN VAE | |
| - Official resources: See the link in 2. | |
| - My resources: <[GoogleDrive](https://drive.google.com/file/d/1ARtDMia3_CbwNsGxxGcZ5UP75W4PeIEI/view?usp=share_link)> <[百度网盘-提取码83u9](https://pan.baidu.com/s/1YCYmGBethR9JZ8-eypoIiQ?pwd=83u9)> | |
| - Put the VQVAE (~700MB) into your stable-diffusion-webui/models/VAE | |
| ### 4. Extension Usage | |
| - At the top of the WebUI, select the v2-1_512-ema-pruned checkpoint you downloaded. | |
| - Switch to img2img tag. Find the "Scripts" dropdown at the bottom of the page. | |
| - Select the StableSR script. | |
| - Click the refresh button and select the StableSR checkpoint you have downloaded. | |
| - Choose a scale factor. | |
| - Upload your image and start generation (can work without prompts). | |
| - Euler a sampler is recommended. CFG Scale<=2, Steps >= 20. | |
| - For output image size > 512, we recommend using Tiled Diffusion & VAE, otherwise, the image quality may not be ideal, and the VRAM usage will be huge. | |
| - Here are the official Tiled Diffusion settings: | |
| - Method = Mixture of Diffusers | |
| - Latent tile size = 64, Latent tile overlap = 32 | |
| - Latent tile batch size as large as possible before Out of Memory. | |
| - Upscaler MUST be None (will not upscale here; instead, upscale in StableSR). | |
| - The following figure shows the recommended settings for 24GB VRAM. | |
| - For a 6GB device, **just change Tiled Diffusion Latent tile batch size to 1, Tiled VAE Encoder Tile Size to 1024, Decoder Tile Size to 128.** | |
| - SDP attention optimization may lead to OOM. Please use xformers in that case. | |
| - You DON'T need to change other settings in Tiled Diffusion & Tiled VAE unless you have a very deep understanding. **These params are almost optimal for StableSR.** | |
|  | |
| ### 5. Options Explained | |
| - What is "Pure Noise"? | |
| - Pure Noise refers to starting from a fully random noise tensor instead of your image. **This is the default behavior in the StableSR paper.** | |
| - When enabling it, the script ignores your denoising strength and gives you much more detailed images, but also changes the color & sharpness significantly | |
| - When disabling it, the script starts by adding some noise to your image. The result will be not fully detailed, even if you set denoising strength = 1 (but maybe aesthetically good). See [Comparison](https://imgsli.com/MTgwMTMx). | |
| - If you disable Pure Noise, we recommend denoising strength=1 | |
| - What is "Color Fix"? | |
| - This is to mitigate the color shift problem from StableSR and the tiling process. | |
| - AdaIN simply adjusts the color statistics between the original and the outcome images. This is the official algorithm but ineffective in many cases. | |
| - Wavelet decomposes the original and the outcome images into low and high frequency, and then replace the outcome image's low-frequency part (colors) with the original image's. This is very powerful for uneven color shifting. The algorithm is from GIMP and Krita, which will take several seconds for each image. | |
| - When enabling color fix, the original image will also show up in your preview window, but will NOT be saved automatically. | |
| ### 6. Important Notice | |
| > Why my results are different from the offical examples? | |
| - It is not your or our fault. | |
| - This extension has the same UNet model weights as the StableSR if installed correctly. | |
| - If you install the optional VQVAE, the whole model weights will be the same as the official model with fusion weights=0. | |
| - However, your result will be **not as good as** the official results, because: | |
| - Sampler Difference: | |
| - The official repo does 100 or 200 steps of legacy DDPM sampling with a custom timestep scheduler, and samples without negative prompts. | |
| - However, WebUI doesn't offer such a sampler, and it must sample with negative prompts. **This is the main difference.** | |
| - VQVAE Decoder Difference: | |
| - The official VQVAE Decoder takes some Encoder features as input. | |
| - However, in practice, I found these features are astonishingly huge for large images. (>10G for 4k images even in float16!) | |
| - Hence, **I removed the CFW component in VAE Decoder**. As this lead to inferior fidelity in details, I will try to add it back later as an option. | |
| *** | |
| ## License | |
| This project is licensed under: | |
| - S-Lab License 1.0. | |
| - [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa], due to the use of the NVIDIA SPADE module. | |
| [![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa] | |
| [cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| [cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png | |
| [cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg | |
| ### Disclaimer | |
| - All code in this extension is for research purposes only. | |
| - The commercial use of the code and checkpoint is **strictly prohibited**. | |
| ### Important Notice for Outcome Images | |
| - Please note that the CC BY-NC-SA 4.0 license in the NVIDIA SPADE module also prohibits the commercial use of outcome images. | |
| - Jianyi Wang may change the SPADE module to a commercial-friendly one but he is busy. | |
| - If you wish to *speed up* his process for commercial purposes, please contact him through email: [email protected] | |
| ## Acknowledgments | |
| I would like to thank Jianyi Wang et al. for the original StableSR method. |