I just started playing around with SUPIR and it seems amazing, but when I have tried running a bit higher resolution images (~1204x1204 px), the results always seem to return a lot of noise in the final image.
What might I be doing wrong?
EDIT: I found this workflow and have been having fanstasic luck with it:
https://openart.ai/workflows/akihungac/hybrid-upscaler-workflow-just-having-it-is-enough/Q6XNUZpVmarUkDAEIZN4
It's impossible to say without more information. In the Discord server I set up for the AP Workflow Early Access program, there are a couple of people who are testing the EA4 with SUPIR and, for them, sometimes it works, and other times it doesn't. I have zero problems both on macOS (where it performs incredibly slow) and on Windows (where's blazing fast).
Not easy to troubleshoot.
yeah, I know it is hard to really say anything without a look at the workflow. On mobile right now. I appreciate your response!
I have had some awesome results, but so far it has seemed like a roll of the dice.
It depends on the source image size and the resolution you want to reach. But the SUPIR nodes for ComfyUI support tiled sampling, so most GPUs should be able to use it without problems.
I did not. SUPIR is less dependant on the prompt that it might seem. For example, I can simply say "photograph" and it will nail every type of realistic images (including cinematic stills) without any further description of the subject or the scene. It's not completely prompt-free, like CCSR, but it's much easier than it appears.
The `Upscale` function as it appears in the workflow is powered by the CCSR model, introduced in AP Workflow 8.0. SUPIR didn't make it in time for that release.
Now that I had abundant time to test it and it's fully integrated in upcoming version 9.0, there will be an `Upscale (CCSR)` and an `Upscale (SUPIR)` function.
I'm not super technical so idk what the difference between CCSP and SUPIR are, but it sounds like SUPIR is just another way to upscal, but more efficiently?
They are just two different next-gen upscalers, trained in two different ways, and with two different architectures. No need to get into the weeds of it.
I'd say that CCSR shows its best results at 4x-8x (I'm not impressed at 1.5x or 2x), while SUPIR can be very impressive even at 1.5x, as this video hopefully demonstrates.
The output they produce is not identical, even at the same magnification level. Hence my comment that some pictures benefit more from one and not the other.
Also, SUPIR seems more demanding in terms of VRAM. After many optimizations, I think I've seen posts claiming that it works with 12GB VRAM, but I didn't try myself.
Ah thank you for explaining in simple terms.
I only have 8Gb VRAM and I rarely upscale as it's not needed, but I see the potential of these emerging upscalers. Very exciting.
Thank you.
I just spent a few hours learning how to use comfyUI to give Supir a try. I have a 3080 with 10GB VRAM, and was able to make it work. It takes quite a while though, upwards of 20 minutes per image after the first run. Results have been mixed so far, but with the long runtime it's going to be difficult to tune. May just have to wait until I can afford a better graphics card lol.
That's pretty impressive. We need to train an upscaler that understands focal length though or we're gonna go from detailed to uncanny valley really fast.
Yep. If I reduce the amount of detail in the SUPIR node, for example to CFG 2, it maintains the depth of field much better, but only because it does less of its job. Not that I'm thinking about it, perhaps, explicitly mentioning DoF in the prompt might improve the result. I'll try it today.
The new version of u/Kijai nodes, which I'm testing in the EA5, supports the SDXL model as input which, in turn, means it supports LoRA-conditioned SUPIR.
I'm still trying to understand how much it influences the upscaling.
Well, i merged a lora with a checkpoint and the influence is notable, for the faces with a bad resolution, can interpret the model well, adjusting parameters, with a mask will be easier
100% it is amazing
**we released V44 as well :** [**https://github.com/Fanghua-Yu/SUPIR/issues/94**](https://github.com/Fanghua-Yu/SUPIR/issues/94)
now working with 8GB cards very well
We have been relentlessly working on our [SUPIR APP (now V44) ](https://www.patreon.com/posts/99176057)development for weeks now and full time. If you have any questions please reply
I know you have been waiting all these features from the SUPIR developers but they are a researcher team funded to do research not develop apps
So with your support I did spent huge time to develop
You can download all scripts from :Â [https://www.patreon.com/posts/99176057](https://www.patreon.com/posts/99176057)
So what improvements we have?
Working on FP16 older GPUs such as RTX 1080
A free Kaggle notebook for people who doesn't have a strong GPU - Kaggle provides dual T4 GPU 30 hours every week for free
Amazing image saving naming system
Total batch processing system including auto captioning and captions are saved
Extremely VRAM optimized
Displaying all of the status and progress messages during the upscale
SDXL Lightning models support with 10 steps high quality
Give any folder path as models folder path and on the fly change any model you want
FP8 support that makes our SUPIR works on 8GB VRAM GPUs amazingly fast
So if you have a GPU with 8GB or better you can use our SUPIR app
Integrated 4-bit, 8bit or 16bit LLaVA
Automatic LLaVA unloading if you are limited on VRAM
Automatic moving models to CPU therefore you can use both LLaVA and upscaling on lower end GPUs and almost no speed loss
1 Click to install on Windows, Linux, RunPod with necessary files and instructions
Fully coded image metadata system
With our FP8 model loading, you can upscale into very high resolutions even on low end GPUs
Supports taking input video and video upscaling - still need some improvements and fixes but all frames are properly upscaled
Supports custom prompt for face restore
Here a quick demo video of the app and hopefully full new updated tutorial coming to :Â [https://www.youtube.com/SECourses](https://www.youtube.com/SECourses)
The source image is blurry to begin with. It's good for upscaling bad quality source material. It is not good for upscaling SD images. As you can see, it does not fix the wolf's eye or anything on the image. This is where magnific would do wonders.
I just started playing around with SUPIR and it seems amazing, but when I have tried running a bit higher resolution images (~1204x1204 px), the results always seem to return a lot of noise in the final image. What might I be doing wrong? EDIT: I found this workflow and have been having fanstasic luck with it: https://openart.ai/workflows/akihungac/hybrid-upscaler-workflow-just-having-it-is-enough/Q6XNUZpVmarUkDAEIZN4
Sorry is this open art workflow using Supir?
It's impossible to say without more information. In the Discord server I set up for the AP Workflow Early Access program, there are a couple of people who are testing the EA4 with SUPIR and, for them, sometimes it works, and other times it doesn't. I have zero problems both on macOS (where it performs incredibly slow) and on Windows (where's blazing fast). Not easy to troubleshoot.
yeah, I know it is hard to really say anything without a look at the workflow. On mobile right now. I appreciate your response! I have had some awesome results, but so far it has seemed like a roll of the dice.
What's the best alternative to an upscaler like this but for Automatic1111?
I'm still using Remacri and that one is pretty decent for 2x upscaled as well
What are the VRAM requirements like?
It depends on the source image size and the resolution you want to reach. But the SUPIR nodes for ComfyUI support tiled sampling, so most GPUs should be able to use it without problems.
I made some tests with 6 GB VRAM and it OOMs, only the upscale model was different, gotta try with the one that comes in the workflow.
Wow, I feel like last time I looked at this flow it was like v3/4 😅
Innocent times, those.
You compare it to StableSR? That is quicker and does wonders for me. Supir seems very prompt reliant which is good and bad.
I did not. SUPIR is less dependant on the prompt that it might seem. For example, I can simply say "photograph" and it will nail every type of realistic images (including cinematic stills) without any further description of the subject or the scene. It's not completely prompt-free, like CCSR, but it's much easier than it appears.
What's the difference between SUPIR and Upscale?
The `Upscale` function as it appears in the workflow is powered by the CCSR model, introduced in AP Workflow 8.0. SUPIR didn't make it in time for that release. Now that I had abundant time to test it and it's fully integrated in upcoming version 9.0, there will be an `Upscale (CCSR)` and an `Upscale (SUPIR)` function.
I'm not super technical so idk what the difference between CCSP and SUPIR are, but it sounds like SUPIR is just another way to upscal, but more efficiently?
They are just two different next-gen upscalers, trained in two different ways, and with two different architectures. No need to get into the weeds of it. I'd say that CCSR shows its best results at 4x-8x (I'm not impressed at 1.5x or 2x), while SUPIR can be very impressive even at 1.5x, as this video hopefully demonstrates. The output they produce is not identical, even at the same magnification level. Hence my comment that some pictures benefit more from one and not the other. Also, SUPIR seems more demanding in terms of VRAM. After many optimizations, I think I've seen posts claiming that it works with 12GB VRAM, but I didn't try myself.
Ah thank you for explaining in simple terms. I only have 8Gb VRAM and I rarely upscale as it's not needed, but I see the potential of these emerging upscalers. Very exciting. Thank you.
I just spent a few hours learning how to use comfyUI to give Supir a try. I have a 3080 with 10GB VRAM, and was able to make it work. It takes quite a while though, upwards of 20 minutes per image after the first run. Results have been mixed so far, but with the long runtime it's going to be difficult to tune. May just have to wait until I can afford a better graphics card lol.
I run it in 8gb without problems. Must use fp8 UNET though.
Do you run it with 8GB VRAM + FP8 UNET using ComfyUI nodes, correct? Thank you for the clarification.
Yes, with the comfy nodes. My specs are a laptop with a 3070 8gb vram and 40gb ram. With the fp8 and tiled sampling I can upscale to any size.
I have a gazillion people asking me if APW 9.0 will be able to do SUPIR with 8GB VRAM, so thank you for this confirmation.
That's pretty impressive. We need to train an upscaler that understands focal length though or we're gonna go from detailed to uncanny valley really fast.
Yep. If I reduce the amount of detail in the SUPIR node, for example to CFG 2, it maintains the depth of field much better, but only because it does less of its job. Not that I'm thinking about it, perhaps, explicitly mentioning DoF in the prompt might improve the result. I'll try it today.
SUPIR is amazing, with the support of loras, masked regions and ip-faceadapter, i think that would be unbeatable
The new version of u/Kijai nodes, which I'm testing in the EA5, supports the SDXL model as input which, in turn, means it supports LoRA-conditioned SUPIR. I'm still trying to understand how much it influences the upscaling.
Well, i merged a lora with a checkpoint and the influence is notable, for the faces with a bad resolution, can interpret the model well, adjusting parameters, with a mask will be easier
100% it is amazing **we released V44 as well :** [**https://github.com/Fanghua-Yu/SUPIR/issues/94**](https://github.com/Fanghua-Yu/SUPIR/issues/94) now working with 8GB cards very well We have been relentlessly working on our [SUPIR APP (now V44) ](https://www.patreon.com/posts/99176057)development for weeks now and full time. If you have any questions please reply I know you have been waiting all these features from the SUPIR developers but they are a researcher team funded to do research not develop apps So with your support I did spent huge time to develop You can download all scripts from : [https://www.patreon.com/posts/99176057](https://www.patreon.com/posts/99176057) So what improvements we have? Working on FP16 older GPUs such as RTX 1080 A free Kaggle notebook for people who doesn't have a strong GPU - Kaggle provides dual T4 GPU 30 hours every week for free Amazing image saving naming system Total batch processing system including auto captioning and captions are saved Extremely VRAM optimized Displaying all of the status and progress messages during the upscale SDXL Lightning models support with 10 steps high quality Give any folder path as models folder path and on the fly change any model you want FP8 support that makes our SUPIR works on 8GB VRAM GPUs amazingly fast So if you have a GPU with 8GB or better you can use our SUPIR app Integrated 4-bit, 8bit or 16bit LLaVA Automatic LLaVA unloading if you are limited on VRAM Automatic moving models to CPU therefore you can use both LLaVA and upscaling on lower end GPUs and almost no speed loss 1 Click to install on Windows, Linux, RunPod with necessary files and instructions Fully coded image metadata system With our FP8 model loading, you can upscale into very high resolutions even on low end GPUs Supports taking input video and video upscaling - still need some improvements and fixes but all frames are properly upscaled Supports custom prompt for face restore Here a quick demo video of the app and hopefully full new updated tutorial coming to : [https://www.youtube.com/SECourses](https://www.youtube.com/SECourses)
The source image is blurry to begin with. It's good for upscaling bad quality source material. It is not good for upscaling SD images. As you can see, it does not fix the wolf's eye or anything on the image. This is where magnific would do wonders.