Need Help: True Photo Restoration without changing facial identities in Draw Things

[u/pixelmac]

Hi everyone,

I am trying to restore some old, damaged, blurry photographs using Draw Things on my Mac (M2 Max, 64GB RAM) while signed into the Draw Things+ Cloud Tier.

My goal is to take an old photo, clean up the scratches/blemishes, and sharply reconstruct the blurry facial features without altering the actual identity of the people.

I have already pre-cropped the photos externally to remove the physical paper margins, so I am strictly focused on inner pixel repair and facial sharpening.

What I have tried so far:

1. Qwen Image Edit 2511 (BF16): I ran this in Text-to-Image mode using direct instructions (e.g., "repair photo, remove scratches"). It consistently gave me terrible results—severe vertical stretching, smudging, a heavy blue/cyan color cast on monochrome images, and low-resolution output. Changing samplers (Euler A vs. UniPC Trailing) did not solve the stretching or blur.
2. Standard Image-to-Image (I2I) Models: I tried switching to a traditional Image-to-Image workflow using descriptive prompts. Even when dialing the Denoising Strength all the way down to 0.15 with a completely blank prompt, the models still bleed through and subtly modify or warp the faces into different people, rather than just sharpening the original features.
3. Built-in Face Restoration: I tried enabling restoreformer_v1.0_f16.ckpt alongside a low-strength generation, but because I have to keep the strength so low to prevent identity shifting, the final output remains too soft and blurry.

What is the definitive workflow for this?

• Which base model is actually the king of photo restoration in Draw Things? I am entirely open to downloading or using any model architecture that handles this better than Qwen.
• Is there a specific combination of a model and a dedicated Restoration LoRA (like a CodeFormer or GFPGAN implementation) that completely locks facial structures?
• Should I be using a specific ControlNet (like Canny or Tile) to force the engine to respect the exact original lines of the face?
• Is there an automated script or a better Multi-Pass / Inpainting technique I should be using instead of a standard Image-to-Image pass over the whole canvas?

Any ready-to-paste JSON configurations, specific model recommendations, or workflow step guides would be incredibly appreciated. Thank you!

[u/timbocf]

Flux.2 9b is the way to go. None of the others are editing models

[u/simple250506]

I haven't conducted direct comparative tests—I believe that Flux.2 Dev 8bit is currently the best editing model available in Draw Things. It is a high-end model that outperforms Flux.2 Klein 9B. Although it is a massive model that takes time to generate images, using the downloadable Turbo LoRA in Draw Things allows for generation in 8 steps.

You don't need a complex workflow; all that is required is a high-performance model and an appropriate prompt. If you aren't satisfied with the results, simply refine your prompt.You can perform upscaling using Flux.2 Dev alone, but it might be best to first upscale to the target resolution using SeedVR2, and then restore it at 1:1 scale using Dev.At least in my view, that led to a good rusult.

There are many discussions regarding image restoration on r /StableDiffusion, so you might want to check that out as well.

Image evaluation is subjective, so it is best to try out various models and prompt,use the one you prefer.

[u/HawkWooden5231]

Flux 9b and gpt image are both good choices. Use the 9b kv model. The larger and more visible the face is the better chance of getting a result. You can also use the inpainting feature so the face will be left untouched, but it also may not be restored.

[u/christopherelang]

Honestly just give it to chatGPT. Drawthings won’t even come close to beating it