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Report good images and images to be improved. 【报告优秀和待改进的图像】 #42
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This is a great model. It literally destroys the very expensive SaaS Magnific. I compared with 10 unique images here : #38 My first suggestion would be adding CPU offloading and reducing it fitable to 8 GB gpus if be doable And here 1 image that failed. My followers trying to upscale a movie and such images are problematic |
Yes the motion and degradation in video is different to images. We plan to make a video restoration large model in the future. We are raising resources and planing for this. |
One another suggestion from people is that being able to change the used SDXL model on the fly. Currently all models are loaded from single yaml file. |
@ivaxsirc We have not applied face restoration pipeline yet. Generally, like CodeFormer, it requires three stage, 1) face detaction 2) restoring each face independently 3) pasting face back. |
Thanks for your answer, i think that SUPIR mark and before and after in the restoration, another suggestion in a older photos with scratches the restoration is not successful, maybe with before works https://github.com/sanje2v/OldPhotoRestorationDLST thks for your excellent work |
@ivaxsirc 老照片修复 项目 |
Thanks stable diffusion has a extension restore old photos that repair scratched images perfectly |
@ivaxsirc Maybe you can try the new updated |
Currently, colors of restored images are strictly aligned with LQ. Repairing sun damage may require combining other projects. |
Yes, i can try, i have several older movies of 70's that we want see if it's possible restore with a 4k quality, and with SUPIR i think that will be possible, SUPIR could be a referent to restauration older movies, and why not in SVD |
I know, at this moment SUPIR with the restoration of images plus the restoration of faces that you have shown me, is unbeatable, but if I were also able to fix old photos with scratches and with images of color worn by the sun, or the years, then I would be light years ahead of everyone, because there is no tool that can do that, only topaz with the color in beta, but the overall restoration quality is very, very below supir, even from what you have shown me with the faces. I always make the proposals with a constructive purpose so that you are a reference in the subject of image restoration, which you already are, because I suppose that you have realized that with supir all the upscaler models are over, since it is superior to all of them. The only problem is the graphics requirements, but if Forge will implement it I think that even with 8GB VRAM cards it could be used. |
The RAM requirement depends on how big the image you start with and how big you want to go How does this work out... Fix the damaged photo with Topaz Photo AI first then SUPIR |
I'm used llava to generate the prompt |
Could i try with your images? |
The first video with restauration of SUPIR Any idea for consistency image? Video.de.WhatsApp.2024-03-05.a.las.23.13.52_fa8c53a2.mp4 |
Fix the seed seems to help with consistency between generations. |
Yes, please help me try to fix it |
Using a fixed noise map can mitigate video consistency issues in a degree. However, high-frequency details will stick to the corresponding pixel, and will not move with objects. For video restoration, tuning image model and adding temporal information are vital. |
More tested on face restoration Original image Image supir without checked anything The image is good, but the face is not similar to the original Same parameters face restoration checked The face is restored but it's not similar to the woman original Same parameters BG and face restoration checked The global quality is very good but the face is not similar to the original I used Forge and 2 controlnets 1) mediapipe_face
With inpaint result The face image does not have much quality But with SUPIR... Comparison This is the face of the real artist As you can see there is a great similarity in the faces, now all you have to do is join the face with the part of the image already restored, it would be great if SUPIR had some tool to do it automatically In conclusion, with face images of very low resolution, SUPIR cannot save the fidelity of similarity, but if it were able to understand a reference image as you have seen, the similarity would be very high |
If the noise level is lowered through the parameter s_noise, how does this value affect image noise? Can you explain Why is the default value a 1.003 |
Can anyone (who has a bit of time) try this here for animation: https://www.reddit.com/r/StableDiffusion/comments/1bk9e0d/smooth_diffusion_code_released/ in combination with SUPIR? Could potentially lead to less artifacts when using SUPIR for a video. |
I tried it in last month, but I found my image quality has been worse. |
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In a future version of SUPIR v2, and possibly in the video version you're working on, I would recommend making it open source and, if you prefer, non-commercial, similar to the Flux models. I understand that proprietary code is very important, but with AI, the community that tests and sometimes improves existing code is, in my opinion, what has significantly advanced the entire AI field. I have a suggestion: establish goals, similar to how Civitai does with people who train models and loras, by setting a price target. If that target is reached, release the code and models as open source. This approach could provide you with the necessary funding to continue researching and developing SUPIR, while also allowing the community to benefit from using the tool for personal use (I understand it wouldn’t be for professional use). This way, both parties would benefit, and I believe the community could continue adding value through testing and improvements. I also wanted to ask if you plan to develop a version of SUPIR that uses FLUX models. Thank you very much. |
Hi, @ivaxsirc , Thank you for your kind words. The insights you provided are very helpful in addressing the challenges of acquiring the significant resources needed for developing new models and maintaining the community. We have already invested substantial funds and time into SUPIR and future research—time, in my opinion, being even more valuable than money. The amount of funding required for new research is overwhelming, and we hope to find a dignified way to obtain these resources without sacrificing our independence. I believe this is a very real issue. I’ve always thought that if the algorithms we develop aren't used, they lose their value. SUPIR is meaningful precisely because it is widely utilized. In the past, scientific research funding was sufficient to achieve this effect. Our previous projects like ESRGAN, RealESRGAN, and many others have benefited from it. Research funding covered the costs, and we open-sourced all the knowledge, benefiting both society and the community. However, the resources required by new technologies today have surpassed the scope of traditional research funding. We need a new allocation mechanism where the market decides the most effective way to support such innovations. We will carefully consider the suggestions you've mentioned and hope that the knowledge we uncover can directly contribute to the community. Regarding other matters, we have already made some progress with Flux, SD3, and SUPIR-Video. We will also continue to invest millions of dollars in the development of related technologies. I sincerely hope that these technologies can be used by more people without requiring me to engage too much in commercial efforts (which I really do not enjoy or excel at). |
Upscale 4, Quality, Texture 5 |
Dear community members,
First of all, I would like to express my sincere gratitude to everyone who uses and supports SUPIR. Your feedback is a key driver for our improvement and development. In order to further improve the performance and user experience of our model, we sincerely invite you to share your experience in this issue.
首先,我想对每一位使用并支持 SUPIR 的用户表示衷心的感谢。您的反馈是我们改进和发展的关键动力。为了进一步提升我们软件的性能和用户体验,我们诚邀您在这个issue中分享您的使用经验。
We welcome your reports:
Exceptional Images: Share images that you think our software did a great job with. Please briefly describe the image content and why you think the treatment worked well. If possible, include a link to the image or the image itself.
特别好的图像:分享那些您认为我们软件处理得非常出色的图像。请简要描述图像内容,并说明为什么您认为处理效果好。如果可能,附上图像链接或图像本身。
Images to be improved: If you encounter some poor image processing, please also report it here. Sometimes, unsatisfactory processing results can be caused by improper use of SUPIR. To help us diagnose the problem more accurately and provide a more effective solution, please describe the problem in as much detail as possible and provide image examples and what you think may be the cause or suggestions for improvement. At the same time, it is very important that in order for our team to better understand the problem and try to reproduce it, we recommend that you also provide the input original image. We understand that every image and every process is unique, and by providing enough information, you will help us deeply understand how SUPIR performs in different situations and optimize accordingly.
待改进的图像:如果您遇到了一些图像处理效果不佳的情况,请在这里报告。有时候,不理想的处理效果可能是由于软件使用不当导致的。为了帮助我们更准确地诊断问题,并提供更有效的解决方案,请尽可能详细地描述问题,并提供图像示例以及您认为可能的原因或改进建议。同时,非常重要的一点,为了让我们的团队能够更好地理解问题并尝试复现,建议您也提供输入原图。我们理解每一张图像和每一次处理都有其独特性,通过提供足够的信息,您将帮助我们深入了解软件在不同情况下的表现,并作出相应的优化。
We believe that with your valuable feedback, together we can take this project to new heights. Please remember to keep your feedback objective and respectful, we are committed to providing an open and inclusive communication environment.
我们相信,通过您的宝贵反馈,我们可以一起将这个项目推向新的高度。请记得保持反馈的客观和尊重,我们致力于提供一个开放和包容的交流环境。
Thank you for your contribution and support!
best wishes,
XPixel, The Author Group
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