Krea 2 Identity Edit

Instruction-based, identity-preserving image editing for Krea 2 (12.9B single-stream MMDiT). Give it an image and a plain-language instruction; it edits while preserving what you didn't ask to change β€” including the person.

An unofficial community fine-tune of Krea 2 Raw. Not an official Krea product; not affiliated with or endorsed by Krea.ai, Inc.

Requires the ComfyUI-Krea2Edit node pack β€” the LoRA is trained with dual conditioning (in-context VAE tokens + image-grounded Qwen3-VL encoding) that stock nodes don't provide. Two ready-made workflows ship with it.

What it does

  • Person re-staging with likeness: "create a photo of this person at a night market" β€” same face, same outfit down to individual moles and marks, fully relit to the new scene. New camera angles and poses included.
  • Local edits: recolor, add/remove/replace objects, attribute and outfit changes, with near-pixel preservation of the rest of the frame.
  • Replace-with-reference: "replace the woman with a big orangutan" β€” the replace verb is trained, locality holds.
  • Full-image restyles: global style with preserved composition.
  • Two-input edits (experimental): scene + person as separate references. Outfits and placement work well; see limitations for faces.
  • Composes with your LoRAs: character/body/style LoRAs stack on top and steer the prior β€” something closed editors structurally can't offer.

Recommended settings

Task type Model Steps CFG
Most edits (add, recolor, restyle, re-stage) Turbo 8 1.0
Removals / large deletions Raw 20 3.0
  • Match the output aspect ratio to the source image. Training pairs are same-size; AR mismatch degrades preservation (edits may apply to only part of the frame).
  • Generate at ≀2MP. Above that, source content can bleed or subjects duplicate (training was 768/1024-class).
  • grounding_px is a real dial (trained range 512–1536): lower values = stronger edit adherence and more uniform scene changes; higher values = stronger identity/likeness. 768 is a balanced default; try 1024+ for people.
  • At CFG > 1, ground the negative too (empty prompt + same image).
  • LoRA strength 1.0.

Known limitations (honest list)

  • Likeness is texture-faithful, proportion-conservative. Moles, skin character, hair, and lighting adapt beautifully; strongly distinctive facial geometry (unusual nose, eye spacing, face length) regresses toward typical proportions. People whose identity lives in texture and structure transfer best; geometry-defined faces read as a "close relative."
  • Two-person inputs keep outfits distinct but faces drift toward each other. Workaround that works today: chain single-ref inserts (place person A, then a second edit pass adding person B from their reference).
  • Removal works but is not yet reliable β€” always use the Raw/CFG 3 recipe; expect occasional re-renders instead of deletions.
  • Outfit swaps are hit-or-miss β€” changing what a person wears sometimes works cleanly and sometimes doesn't apply; reroll or rephrase.
  • Local edits aren't always perfectly local β€” add/remove/replace operations can sometimes alter other parts of the frame or shift the overall color grade. If preservation matters, compare against the source and reroll.
  • Highly unusual visual content (extravagant hairstyles, extreme body types) can drift toward the base prior β€” a subject LoRA stacked on top fixes this.

License

The LoRA weights are a Derivative Model of Krea 2 and are distributed under the Krea 2 Community License Agreement (see also NOTICE). Key points for users: commercial use is permitted under the license's revenue threshold (Β§2.3, currently <$1M/yr β€” above that, contact Krea for an enterprise license); deployments must implement reasonable content moderation (Β§4.2); AI disclosure obligations apply where required (Β§4.3). This repository modifies the Krea Model as permitted by Β§3; it is not endorsed by Krea.

Research/portfolio release by a self-funded hobbyist.

Showcase

All reference people below are themselves AI-generated β€” no real likenesses. Prompts are embedded in each image.

Two-reference composition Outfit swap + scene + weather Person re-staging with relight New camera angle Replace with preservation Full-image restyle Object addition

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