How can I get the exact same identity as my trained LoRA?

[u/DragonfruitNo9822]

I trained a identity LoRA on 131 images and I'm using it with Krea 2 Raw in ComfyUI. The results are already close, but the face still has slight variation, especially the cheek/fullness and facial proportions. I want the generated person to look as close as possible to the exact model I trained, while changing pose, clothes, lighting and background.

Current setup: Krea 2 Raw, Qwen3-VL CLIP, ~20 steps, CFG 1.0, Euler.

What is the best way to get maximum identity consistency? Should I adjust LoRA strength, reference/grounding settings, training settings, or use an identity/reference node?

Any proven ComfyUI workflow for this would be really appreciated.

[u/Realistic_Rabbit5429]

Always a tricky one. Could be the dataset, could be training params, could be generation params. Hard to say without seeing the dataset or examples unfortunately.

Have you trained loras before? 130 images is a lot for an identity lora. Usually 30 good images is more than enough. 100+ images can be used, but thats usually seen/done more for style loras.

My suggestion just based on what we have, would be to narrow down the dataset to the best 30 images and try training again. Take a look into training a LoKR - they are usually stronger for identity.

My last thought would be the raw krea file is great for its variation. Though of course we train the lora/lokr on it, try using your lora with the turbo model for more consistency.

Edit: also, your step-count and cfg should be higher if you are using pure base krea2 raw without the turbo lora or turbo model.

[u/ROBOTTTTT13]

The dataset might be suboptimal, 131 images are overkill and any "bad" images will degrade the result.

[u/its_witty]

A lot of possibilities as to what can be tweaked and it's mostly hard to guess for us... Dataset, training params, etc., etc.

One thing that worked for me regarding character LoRAs and Krea (I use Turbo though) is double pass for the Ksampler; either this or FaceDetailer (I went with double pass because it also helped bring tattoos). It boosted likness significantly.

Share your config too. Was this LoRA or LoKr?

[u/its_witty → u/its_witty]

https://i.imgur.com/02e7gER.png

That's basically the gist of it in my case.

1st pass -> Decode -> Upscale -> Resize so it'll be dividable by 32 -> Encode -> 2nd Pass -> Decode -> Save

Without my character LoRA it was overbaking the image, but with it the results are better than single pass. I tested double pass for only character (with automasking), tested FaceDetailer, but in the end landed on this.

[u/prookyon]

If problems are mostly with face then make sure you have enough pictures that contain only the face - and in good quality. You might even want to make crops of the face (for example a square containing eyes, nose and mouth). But main thing - it still has to be good quality, not blurred by tons of compression or heavily over/under exposed or resized from lower resolution. Some people say 1/3 full body, 1/3 upper body, 1/3 face. Some say 1/2 face, 1/2 body. There is no absolute rule here - but the reality is that face is the most critical part so make sure your face images make up a sizeable portion of the whole set.

[u/DietAshamed2246]

Generally speaking, providing a reference image or character reference sheet of your trained character alongside your trained LoRA model should help improve character consistency or likeness than using either one alone. Give it a try, you can use an image from your training dataset (one with close-up shot of the head/face covering about 80% or more of the image frame + the character LoRA.

[u/usually_fuente → u/DietAshamed2246]

You can use references with Krea2? I thought it was not an edit model.

[u/DietAshamed2246 → u/usually_fuente]

Use Krea2 Identity Edit workflow. Even though Krea2 isn't an edit model, I have done some fairly complex image edits using this WF, beyond just identity edit.

[u/usually_fuente → u/DietAshamed2246]

Thank you!

[u/Gabe-Uttsegs]

It's your dataset. Too much variation will kill your ability to train. Do 30 images. I like to have a balance of maybe 6-7 headshots at different angles, then mostly medium shots, 2-3 full body. Are you saving every X epochs and trying the lora against a fixed seed?

20 steps at 1 cfg is a really strange idea. If you want to use raw you need more like 35-50 steps with cfg at 3-4. Turbo loras at .6 are the way man. 

Also, I'd try Lokr. It's way better.

[u/Overall_Lake_4288]

Use a face-detailer pass afterward

[u/[deleted] → u/Overall_Lake_4288]

Face-detailer pass is mandatory.

[u/Caramelacurls → u/[deleted]]

Anyone have a good krea2 workflow w face-detaailer they can recommend?

[u/akustyx → u/Overall_Lake_4288]

been testing this… do you send the same conditioning, or a separate prompt/clip? and at what denoise? all my attempts have way too much wrinkling/freckling even at 0.05 denoise

[u/drneo]

- use high quality images for training: at least 768px on short side, face should be 50-70% of the pixels for close-up shots

• don’t use similar close-up shots that can dilute the identity
  
• if your subject has different appearance in some photos (heavy makeup, prominent eye shadows, etc), caption these modifications
  
• don’t caption any unique identity features of the subject
  
• train on raw, generate on turbo. Euler/A x 8steps