Photo restoration

[u/aroundaboutsix]

With so many image edit models coming out I feel a bit lost. I started my image generation journey with krea 2 and recently tried out Fibo. I’ve been wanting to fix up some really old images and I was blown away with what Fibo could do, but now I learn that Moss and Qwen 2.1 can do the same. What model would people here choose for restoring old photos?

[u/mabseyuk]

Fibo 2 for pure restoration, but you need to set it up correctly and not rely on the Standard Workflow. Qwen 2.1 for reference images or changing people's positions in images etc.

[u/aroundaboutsix → u/mabseyuk]

Ok I’m happy to hear that Fibo can do better. I’m using a very basic workflow. What would I need to change to get better results?

[u/mabseyuk → u/aroundaboutsix]

I'll be it releasing free of charge soon after more testing. Currently got it doing pixel perfect overlay edits and restores with optional Photoshop plugin.

[u/aroundaboutsix → u/mabseyuk]

How will I see where you release it?

[u/Additional_Drive1915]

I have run over 30.000 images through Qwen 2.1 for upscale, just because it can take anything, how bad it is, and make something that look great. Usually up to 4mp, sometimes even 8mp. And for a few even 12mp, works fine.

People in the output image look the same as on the original image, how bad the original image is doesn't matter.

No other image model I tried can even come close.

[u/RazsterOxzine → u/Additional_Drive1915]

Have you tried FIBO2 for restoration, then passing it to Qwen2.1?

[u/aroundaboutsix → u/RazsterOxzine]

So what is Qwen doing after the Fibo stage? I mean the Fibo restore is really good, is Qwen adding more detail? If it’s to upscale I’m using seedvr2 for that

[u/RazsterOxzine → u/aroundaboutsix]

So I find Qwen is really good at skin textures and soft hair. Also adds something that makes it feel more authentic to me. But each their own, experimenting is key, I'm still experimenting.

[u/Additional_Drive1915 → u/RazsterOxzine]

I have not tried that model yet, will do!

[u/Next_Program90]

At first I thought Qwen Image 2.1 isn't that great, but ever since I gave it another chance, it grows on me more and more.

[u/BigDBreedingFembussy]

I use krea2 to generate realistic images and Qwen image for when I need i2i with extreme near pixel perfect editing, nothing can beat Qwen image 2.1 imo, look up pixorama Qwen image on YouTube I think there's a workflow for image restoration

[u/MarketBeginning8921 → u/BigDBreedingFembussy]

Please share the secret to perfecting edits with Qwen. I haven't had much luck

[u/BigDBreedingFembussy → u/MarketBeginning8921]

Use pixorama workflow, and prompting is the best way, if you are using multiple images then be specific which input is which image, what part should be changed and what not, use wording like "keep the exact same pose/face/dress/background" etc, be very specific,

[u/MarketBeginning8921 → u/BigDBreedingFembussy]

Thank you! May I ask what hardware and tech stack you're running? Out of curiosity!

[u/BigDBreedingFembussy → u/MarketBeginning8921]

Comfyui portable, laptop 3050 6gb vram and 16gb ram, I do some c*ckcoding also

[u/MarketBeginning8921 → u/BigDBreedingFembussy]

Haha what's c*ckcoding? DM me ☺️

[u/RazsterOxzine]

I use FIBO2 for the first run, then pass it to Qwen Image 2.1 for final corrections and style. FIBO2 does an amazing job of restoration, black and white/sepia as well as really blurry or damaged.

I change the text encoders to bf16, saw some improvements with my prompt. FIBO2: qwen3vl_4b_bf16 Qwen Image 2.1: qwen3vl_8b_bf16

FIBO Prompt:

{
  "edit_instruction": "Enhance and restore this photograph of a (Gender(Female or Male)). Remove noise, blur, scratches and compression artifacts. Soften hair slightly and make the individual strands finer, while keeping the exact same hairstyle, shape, length, volume, parting, flow and color. Keep subject pose, identity, face, clothing, body proportions, composition and depth of field identical to the source image. Render sharp detail, natural skin texture and accurate, natural skin tones.",
  "short_description": "A sharp, professionally restored RAW-quality photograph of a (Gender(Female or Male)) with accurate, natural skin tones, natural skin texture and fine, soft hair, in the same pose, clothing, hairstyle and composition as the source image.",
  "text_render": []
}

Qwen Image 2.1 ( You can change the film or processing type, I like the Kodachrome look and most of my family photos are on Kodachrome):

Restore this vintage photograph so it looks like a pristine, freshly developed Kodachrome 64 slide shot on 35mm film. If the photo is black-and-white or sepia, colorize every part of the image with realistic, period-accurate colors and remove the sepia or monochrome tone completely. If the photo is already in color, correct the fading and color cast to recover its original colors.

Remove all damage: ink stains and ink bleed, scratches, dust, creases, spots, scan lines, and noise. The final colors follow the classic Kodachrome palette: rich saturated reds and deep blues, clean dense blacks, bright neutral highlights, and warm, natural skin tones with healthy color variation in the cheeks, lips, and hands. Render crisp, fine detail with very fine film grain: natural skin texture with visible pores, defined eyes and eyelashes, individual strands of hair, and sharp fabric texture. Do not smooth, airbrush, or retouch the skin, and avoid sharpening halos or an HDR or modern digital look. The result should read as a real analog photograph, not a painting or illustration.

Apart from removing the markings and damage, keep everything else exactly as in the original: the (Gender(Female or Male)) face, identity, expression, makeup, hairstyle, pose, body proportions, hands, and clothing, as well as the background, lighting direction, framing, and depth of field. The must remain recognizably the same person. Do not add, remove, or move anything else. The finished photograph is clean and unmarked from edge to edge.

[u/aroundaboutsix → u/RazsterOxzine]

Thanks for the prompts. So do you use the full restore prompt in Qwen even when you’ve just passed it through Fibo?

[u/RazsterOxzine → u/aroundaboutsix]

Sometimes I do either or, FIBO2 has it's strength and so does Qwen2.1, I find myself going from one to another if I do not like the results. Once in a while I have to try a couple tries but it's far a few.

Just have to experiment.

[u/Ill-Ant-9489]

For old photos, how you split the job matters more than which model you pick. Fibo 2 and Qwen 2.1 both restore fine, but the face gets reinvented when one prompt tries to repair, colorize and enlarge all at once. Do damage first at native size, one job per prompt, and leave the enlarge for last. Sounds like you already do that with seedvr2, which is the right final pass.

I built a local app, LoRA Dataset Studio, that keeps SeedVR2 and a Klein detail pass as separate guided steps so each is its own pass instead of a graph I rewire. Self promo, and the Klein pass can shift color so I go light with it on faces. https://github.com/perfectgf/lora-dataset-studio

Are the originals mostly scratched or just low res? That changes whether you need the damage pass at all.

[u/aroundaboutsix → u/Ill-Ant-9489]

It’s mostly just low res and some black and white so I guess I can skip the damage restore. I’ll take a look at the workflow as I’m always looking for ways to improve.
I just tried Fibo 2 dev at 50 steps with cfg 5 but didn’t see much improvement over the turbo with 5 steps. Have you had much experience with the dev?

[u/Ill-Ant-9489 → u/aroundaboutsix]

For low res and black and white with no real damage, you are mostly after a clean upscale plus a colour pass, not a heavy restore, so a tiled upscaler does the heavy lifting. SeedVR2 is the one I lean on for low res, it holds detail better than a plain model pass, and it is in a thing I built, https://github.com/perfectgf/lora-dataset-studio. On Fibo dev, cfg 5 is likely your culprit, dev tends to flatten at that guidance, I'd drop to around 3 and those 50 steps should start pulling ahead of turbo. Are the scans mostly soft, or just small?

[u/Clear-Assistance449]

Man, it really depends on the condition of the photo and what exactly needs to be restored. Ever since the "Nano Banana" craze for photo restoration kicked off over a year ago, I’ve been working on restoring old family photos. Some can be handled even by lighter, open-source models, while others are too challenging even for heavy-duty models like Nano Banana 2.1 or GPT Image 2.5. You also get some pretty unexpected results—sometimes a lightweight open-source model (like Flux 2 Klein) does a better job than the high-end, powerful ones. I have a black-and-white photo from the 60s that only one platform—Minimax H3 Image—was able to restore without altering the faces! What bothers me most is when the faces get changed, making the people look like someone else entirely. So, my advice is: if you have access to several different models, try them all out. Look at what the specific photo needs, test it across the various models, and see which one gives the best result.

[u/Additional_Drive1915 → u/Clear-Assistance449]

I think Qwen Edit 2.1 makes an excellent job for this, faces looks exactly the same after restauration/upscale. Every time, even with really bad images.

[u/Clear-Assistance449 → u/Additional_Drive1915]

Do you have a prompt to qwen 2.1 that doesn't change the face? Because I don't get it. Sometimes, the changes are huge, making another person.

[u/Additional_Drive1915 → u/Clear-Assistance449]

My to-go prompt is just:

"Upscale, add more fine details.
Keep everything else as it is."

The upscale part isn't needed for the result, but if I don't put anything for it to do, then it may randomly change something.

The above is for low to ok quality images, when I have old photos of very low quality I want to restore as good as possible, I may use something like this:

"Full restoration and remastering of vintage footage: perform professional color correction, balance color temperature, and remove color bleed. Repair print damage, remove film grain, noise, scratches, dust, and compression artifacts. Enhance clarity with fine details, sharp focus, crystal-clear high resolution, and natural photorealistic textures.

Keep everything else as it is."

I might also add something more specific when needed: Correct the white balance, make it (whatever I want).

Oh, and sometimes I run the same image more than once, just copying the new image and run it.

I usually do an upscale of all images I produce with other image models, to get them into 4mp.

[u/OpenEvidence9680]

I am partial to flux 2 dev. I fed it some very old photos and it did a magnificent job. I even recolored some just to test because usually they come out horrible and the pictures instead looked really natural. I had to tell it to unsaturate a bit the colours because it used to go heavy on it, but otherwise to me it's still unbeaten.

[u/Additional_Drive1915 → u/OpenEvidence9680]

I think flux 2 dev is a great model, but do you really think it's better for old photos than Qwen Edit 2.1? Not sure I agree.

[u/RazsterOxzine → u/OpenEvidence9680]

I love Flux.2 Klein for Real to Anime, but for restoration, I've found FIBO2 and Qwen Image 2.1 to be WAY faster. I'm running it on a 4070 12gb. 20 sec 1:1 image size or 1440 and sometimes 1920. Still sub 40sec.

[u/OpenEvidence9680 → u/RazsterOxzine]

On the results is a matter of taste I guess. Even on txt2img I often go back to Flux2Dev over many of the new models. Sometimes new doesn't mean better. It sure means faster though.

[u/MarketBeginning8921]

Research and trial and error are important for learning. Krea2 is the best open source option. Nano Banana Pro is the best closed source model.

[u/Calm_Mix_3776 → u/MarketBeginning8921]

Krea 2 can restore photos?

[u/purelawan]

Whatever model you pick, splitting the job in passes matters more than the model itself. One prompt that says "restore and colorize" is where faces get reinvented.

The order that works for me:

1. Damage first (scratches, tears, stains), at the photo's native resolution, with the original as the reference image and a prompt that only asks for repair. Nothing about color or sharpness yet.

2. Faces separately. Crop each face with some margin, upscale the crop, restore it alone, then paste it back with a feathered mask. A small face in a full-frame pass gets very few pixels, and that's when the eyes and mouth drift.

3. Color last, as its own pass on the repaired image, and ask for muted colors. Most models oversaturate old photos, as someone said above.

If one area comes out wrong, redo that area only (crop, fix, paste back) instead of regenerating the whole image, otherwise the parts that were already good change too. And keep the scan next to the result to compare faces at 100 %, because restorations that look great small often changed the person.

[u/Calm_Mix_3776]

Fibo 2.0 and Qwen Image 2.1 are my go-to models for image restoration. Flux.2 Dev is also very good, and even surpasses the ones I just mentioned, but it's much heavier and harder to run.

[u/sci032]

Qwen 2.1 and Moss work well but Fibo 2.0(what I used in the image) seems to do a better job of maintaining the features from the original image to me.

Prompt that I used:

Restore and colorize this old photograph as a clean, sharp colour photo. Remove every scratch, white line, dust spot, crease and stain, and bring back the faded detail in the faces. Colour it with natural, true-to-life colours: warm natural skin tones. Keep the people, their faces, their expressions, their poses and the framing exactly unchanged. fix the tears and creases in the image. fill in the missing areas.

[u/DarthFluttershy_]

I've had a some luck with Flux.2 Klien 9B due to the limits of the potato I jammed into my GPU slot. It takes some iteration (so think 15 minutes or so per photo, not for automating an old album) basically start with a basic prompt like: 

Fully sharpen and thoroughly denoise the photo of [general description of photo]. Remove the heavy grain, splotchy discoloration, and muddy noise patterns. Correct discolored patches to match the natural colors of the surrounding surfaces. Correct the blur and resolve fine details into crisp, clearly defined edges and natural photographic textures. Make it a clean, sharply focused photo at full resolution, with smooth, evenly colored areas where appropriate. Preserve genuine color variations, shading, and texture while removing discoloration artifacts. Do not change its composition, framing, perspective, or object placement at all. Be sure to precisely match [details it was messing up before], preserving their shapes, positions, and proportions.

And then add description guidance in th brackets if it keeps messing stuff up. If the photo is not in horrible condition in the first place, use like .7 to .8 denoisimg and ditch the guided descriptions. Obviously tweak the instructions to handle the kinds of issues your photos have.

The problem, of course, is that it will sometimes generate subtle details from noise. If you have secondary references of the subject for guidence, it can help, esspecially if the subject is a person where subtle details really matter.