ComfyUI: Scaling-UP Image Restoration, SUPIR (Workflow Tutorial) 

Do you mean from the "Divisible by 64" group? I'm reading what you wrote here as exactly what is already happening in the video.

Additionally, are you supposed to connect the image output from the image crop in the "divisible by 64" group and apply that to the image resize image input in the "upscale factor" group? or are you supposed to use the original image as seen in the video? I dont understand why you wouldn't always use the cropped image especially if your upscale factor group is already changing the size to the cropped image heights & widths

Please Check the video further. All output from the image resize is connected to the switch which passes on to the upscale. If you are doing directly connect from the bottom group to upscale factor.

@@KQforever Yes divisible by 64 group (as per that section of the video), When making the video it I was still testing it was 64, then in between I had to switch to 32, finally went with 32. if it works with 32, it will work with 64.

Thank you!

Glad it was helpful!

www.youtube.com/@stephantual

I agree with you. This is God level

Thanks! Gemini will give error on any photo with a face. They have blocked people photos. So even if you upload on gemini pro in browser, it gives error. Everything else works.

Thank you! That image resize is from comfy essentials custom node, there are multiple image resizes look for the one with the wrench icon.

Hey, Thanks! Okay, you got the oversight accurately. Let me explain what I was thinking when I did that. If the image is divisible by 32, the crop will not do anything. If not, it will crop the image to the nearest number, which is divisible by 32. For the downscale, you are correct. The image resolution is from the original, but the image source is from the cropped. The correct way would be to connect the cropped width and height to the downscale input instead from the original. Why it doesn't matter. Because if you have a high res image, we are not going to use SUPIR for restoration. The image is already high res and proper. The downscale method here is a rinse-and-repeat method, meaning you take a low-res image and correct it by making it divisible by 32, which is done during upscale, we then use that to downscale, upscale again (rinse and repeat). The divisibility by 32 is fixed during the first upscale pass. Therefor calculation will always be correct in the downscale in the second and subsequent passes, whether width and height are coming from the crop output or the new original. This is an oversight from my side, as the downscale was never meant to be used for directly inputting a 4 K image, for example, and downscaling to upscale. It was meant for low-res, to upscale through multiple passes. The first pass would correct the divisibility by 32. So, you are the first person to get this oversight correctly. To answer your query, the 100% correct way would be to take the width and height values of the downscale from the cropped output. I got the oversight; however, I did not correct it since I only use the downscale for the rinse and repeat, so the res is always divisible by 32, no matter if it is coming from the original or crop output. (by image crop output I mean, the width and height from the image resize node in the bottom group) I have pinned a message mentioning the correction for the oversight.

Hi, yes for the json, however nothing is hidden behind a paywall in regards to the tutorial. I always showcase everything in the video, showing how to build the entire workflow. But do appreciate any support given. 👍🙏

@@controlaltaiI see. How does your workflow differ from other Supir workflows available? do they have the divisible by 8 and 32 nodes etc that you have? ar they dynamic like yours?

@gohan2091 You can check out the SUPIR workflow by Dev himself, who implemented this, you will get it under custom node, SUPIR, examples folder. The SUPIR upscale group in the video that’s what the basic workflow consist off, everything else is additional and done by me. Also the settings used for the sampler are very different. The workflow will give consistent accurate results, with these settings. The only limiting factor I see is the hardware. If I had better hardware I would just use full tiling for every image and be done with it. The workflow has dynamic automation for practical use. For example, you don’t want to calculate every image manually, different tile setting is a unique approach, ability to switch things on the fly and so on….I cannot speak about other SUPIR workflows. I have only seen the default given by the dev. Edit: divisibility by 8 is taken care of by comfy, not 32. The issue comes to convert to 8/32 both. You can always manually convert crop outside comfy. Images generated using Stable diffusion won't have any compatibility issues.

@@controlaltaiWe appear to have the same hardware. It's the best we can get at the moment (without spending tens of thousands) I must admit, I am not fully understand the 3 different modes but I will re-watch your video later. I am using the dev workflow now, cannot even figure out how to increase the size but it's definitely improving quality. I am having to guess settings though like s_chum, s_noise, DPMPP eta etc. I guess with your workflow, I would still have to guess the settings?

@@gohan2091 I do explain the settings in detail, it’s complicated. If you want consistent, high accuracy result, try with the settings I used, changes in the setting mostly result in creative output, which personally, should be avoided for upscaling. But yeah, for example if you want some color change or add more details etc, you have play around with it. The tiles matter, in terms of vram usage. Typically close to original, will always give best quality, but above 2k it’s very difficult on 24gb vram. Secondly, on that setting it takes more time, if doing in batches, then maybe a middle ground would be a good balance on speed and quality. It just good to have flexibility in the workflow.

I show everything in the tutorial video. You can just follow that and make the workflow yourself.

@@controlaltai Yup, TNX again)

@@Gmlt3000 Definity unfollowed. People are taking this "workflow" too far as if they are the people that MADE the software. peace.

The multiple of 32 applies only if it's not a multiple of 32. Technically it's doesn't matter. You would want the image to be as close to the original as possible. There is no image upscaling before conversion otherwise supir gives error. Downscale is case to case bases. Once the image is a multiple of 32. The entire multiple of 32 process is ignore and nothing in terms of resolution happens to the image.

I agree with you @andrewq7125 . This workflow makes the assumption that you don't start with a downscale. So as long as you start with an upscale it works fine. I have a partially blurry image I wanted to try this workflow on with a size of 3168 (w) by 4752 (h). The workflow cropped the image down to 3168 by 3168 but then when downscaled 4x it becomes 792 by 792 which cannot be divided by 32. If I changed the crop factor to being divisible by 128 instead of 32 it worked fine. It just doesn't make sense to have to manually calculate those things in advance considering how automated this workflow is, so best to change the workflow to start with the downscale at the very least, bypass it if not downscaling and then crop and upscale. That being said, it's a good tutorial though. As a beginner there's alot I've learned from this tutorial

Hi, I saw the oversight some days back, as pointed out by another user, and provided a solution in a pinned comment. If you start downscaling from the beginning, you just have to make one change. "@21:29 Slight oversight. Connect the Width and the Height to the downscale from the Image Resize at the bottom (divisible by 32 group) and NOT THE ORIGINAL. Thanks to the user "dr.gurn420" for correctly catching this oversight. The oversight would affect only if Downscaling an non 32 divisible image. Would have no effect if using the rinse and repeat (upscale downscale method) as shown in the video." I hope with this change, the workflow is now fully automated, even in the case of downscale first.

Its SUPIR, try searching again. I can find it in manager. What environment are you running comfy in?

@@controlaltai Sorry, typing error. Now it works!, python is 3.11 (in the zip file ComfyUI is cu121); Congratulations for your explanation and patience.

Great and Thank You!

Hi, When using tiled restore, ensure that the tile size is default, this won't cause the error. Do not use the standard or full tile size with tile restore, for some images the number is not divisible correctly.

@@controlaltai cool😀, but cause another error'Error occurred when executing ColorMatch: stack expects a non-empty TensorList'🙏

Do one thing close and restart command prompt and run tiles fresh. Make sure the color match nodes source is correct. I never encountered that color error. Use the default one. Let me know.

@@controlaltai i tried several times, it occurs ocasionally, dont know why

Well only way to know for sure is to check the workflow. And the image. Sendnit to me via email will have a look mail @ controlaltai. com without spaces

Hi, no this workflow won't work with a 6Gb VRAM. I recommend 12 to 16 GB at least.

@@controlaltai Yes, I tried this workflow, but it didn't work out, haha... Hello, I would like to ask if you have considered developing a workflow that involves sketching, coloring, and assigning material textures to objects. From a product design perspective, this kind of workflow aligns with the product design process and is highly practical, but I am unsure if current technology supports it to achieve ideal results. If it can be implemented, I believe many people would enjoy it.

Hi, yeah don't use this workflow, this one is complicated and its not image 2 image. Check out this Ultimate SD Upscale tutorial which allows you to do image 2 image in Comfy easily. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-NDw9AjjW1t4.html

@@controlaltai Thanks for replying! I saw the tutorial and indeed is easy, but my problem remain, the img generated is still unrealistic (ok, I know fro the tutorial you used an art image) maybe I have to look for some upscaler that gives more realistic appearance to the skin? If it exist :) Thanks!

@@giusparsifal skin is different, and realistic skin is very different, along with the upscale a specific checkpoint would be needed to add details only to skin, plus some Lora’s to make the skin natural. AI has a habit of making the skin like plastic. Civit AI would be a good resource for the checkpoint and Lora. Juggernaut, RealVisXL are two very good checkpoints for skin. Check the trained settings for steps and cfg. Hope this helps.

@@controlaltai yes, I generally use epicrealism as checkpoint too, the problem, for me, is create a workflow to get what I wish... Thanks anyway, you're very kind!

Ermm sorry, I am not aware on any such specifically trained models. However I am sure you will find something at civil ai. The only way is to download and test with your prompts as they don't say on what dataset the model is trained in.

@@controlaltai 👍 so seems like the best approach is to experiment with different models and find the ones that work well..in my testing even SD3 doesn't seem to have a perfect grasp of room structures, so it might be challenging with XL but yeah I'll see what I can find. Thanks!

For old images discoloration it's a bit more complicated. The first thing is to get it to restore to some degree, 1k. Then you have to use another workflow probably the ControlNet re color one. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-hTSt0yCY-oE.htmlsi=bF4qIFUg3K7lnMrk The simplest trick would be to make the image black and white and then add color again. Finally use SUPIR again to upscale for 2k or higher. For cracks and other stuff you can use Fooocus inpainting as shown here... ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-wEd1wPlCBaQ.htmlsi=yQJibUveCYe_oaFl

Hello, What link doesn't work? JSON is for channel members. And what does white screen help mean. Elaborate

​@@controlaltaiI joined a RU-vid community, but nothing happens!!!

​@@controlaltaia blank screen, dots and a cross...empty...

Well I cannot help with that. Check with RU-vid support if memberships is supported in your country. As far as I can see you are not a member, maybe a subscriber. Contact RU-vid support for further help.

This depends on your image, the sudden cut parts are to streamline the video, nothing regarding the workflow is actually cut. When you are using a 512 image, is the image clear or in poor not recognizable quality, that would determine the upscale factor. If the image in clear, try upscale from 512 to 1500 custom. Check, then proceed. Imperceivable difference comes with very clear images using 1x upscale. Unless I see your image I cannot tell you what is going wrong. You might want to send the image to me via email and I will have a go with it, reply back with the results. (mail @ controlaltai . com) without spaces.

I sent you 2 of my test images. 1 lowres photo and 1 512x512 AI generated @@controlaltai

Yup received and replied via email.

@@controlaltai thanks again 😊👍

Hi, please rephrase the exact name of the group as shown in the video. Is it downscale or are you talking about 4x upscale?

@@controlaltai Sorry friend, that's google auto-translate. I'm from Russia and I use a translator. I stand corrected. I'm interested specifically in the group with the image reduction. timecode 34:13

@video-sketches Hi, check this 44:31 on why downscale is there. Basically, you can upscale to add details downscale then upscale again, to get desired results.

Hi, Check the members post in community. You should have access to it.

@@controlaltai Got it Gaurav Seth! Thanks for your work!

Thats complicated to explain in a comment. I do explain it in the video. If you have any specific questions, feel free to ask.

​@@controlaltai i would absolutely love if you could make a tutorial of how to remove bends scratches and such, if possible 🤩

A tutorial is not warranted for that, as it’s dependant on the image. But basically using fooocus in paint technique, masking, cssr or SUPIR bend and scratches can be removed. The workflows depends on the image, hence the tutorial won’t matter, as what will work for a single image won’t work for any other.

​@@controlaltai okay i saw it a while ago in a tutorial in stable diffusion automatic1111 tho.. But They did use inpainted and it actually worked for a couple of pictures.. Maybe i should see if i can find that again and see if i can replicate in comfyui..

@@supernielsen1223 check out the refinement method in the yolo world in paint out paint workflow. I don’t have a cssr workflow but SUPIR or cssr both should work for restoring.

I don’t know what that is, but am learning new things every day. If you could elaborate…

@@controlaltai Sorry, I guess % is more common for Modulo. So the function above should be "a-(a%64)" where a is your input resolution, which allows you to get the nearest resolution divisible by 64 (or 32 etc. as needed). To elaborate, assuming an image with a width of 550px, the function above would be 550-(550%64) = 550 - (38) = 512. Regardless, thanks for the elaborate Tutorial.

​@@thevoid6756 Thanks for the explanation. Yup I am aware of this.

What's the upscale factor? For good enough images (very clear) 2x upscale will work, 1x spoils it, 1.5x little better....

I refreshed it and it worked

JSon is only made available for paid channel members who monetarily support the channel. You can, however, just watch the entire tutorial and create the workflow. Everything is shown in the video. We make it a point with every tutorial that the entire workflow can be created for free and not hide the creation process behind the paywall.

There is no image to seed node.

@@controlaltai my bad, I've edited the comment above!

Tutorial for Pix2Pix will be out next week....:)

Please don't call people on RU-vid with 10 IQ level. Most of the viewers are smart business professionals. On the technical level I don't want to get to an argument cause such a statement would not been made in the first place. Technically every pixel has data and if you read the research paper you would know how the model is trained and what actually happens. So yeah details are added to the police officer, if you notice the hat and everything else the whole image is indeed restored from broken pixel. It did not put a party hat or a different hat design. Restoration means taken 5% pixels even 5% and building on that. If the image is that broken even a human won't be able to restore from that level of data. I never comment on opinions however Channel viewers should not be insulted for no reason. Thank you for your opinion and offcourse your are entitled to your views regarding the AI tech. It's a free world.

My mans just said that about watching youtube... while watching youtube 😂 bro what does that make your iq? 5??

The thing is... People request these kinda things.. Often another family member or such will tell you how close it is.. It could be way off it could be pretty close... No way to tell really..

​@@supernielsen1223 That's exactly why it was a terrible showcase. I am interested in a process to restore some detail, not to completely reimagine a photo. After seeing that horrible example at the start, I stopped watching this video. Waste of time.

@@supernielsen1223 It's very easy to tell with the policeman, lol. The original image is of a dorky, bewildered English-looking guy. The after image is of a less bewildered, somewhat middle-eastern man. It's not just hallucinating new detail; it actually completely changed the obvious remaining detail from the original image.

Grandpa is now an AI model.

jupp, its a replace generator with a guide.

Yes, it uses RealVis_XL version 4 (baked vae), normal one.

Switch to default tile, use custom resolution, don't upscale 2x. Check original image size. If higher than 1024 then downscale to 1024. One of the above issues, low vram/system ram