cocktailpeanut / krea2-identity-edit

Krea 2 Identity Edit

v1.1 (recommended): krea2_identity_edit_v1_1.safetensors — substantially improved face likeness and image fidelity, much stronger edit locality (camera, pose, and untouched elements stay fixed far more reliably), better two-person identity separation, more reliable object remove/replace, better compound outfit-change compliance, corrected reference geometry handling. One honest regression: person -replacement ("replace the woman with an orangutan") is currently weaker than v1 — keep v1 for that use case until v1.2. No high-resolution adaptation pass yet: at high resolutions (especially two-person edits) identities can bleed together — prefer ~1–1.5MP and upscale. v1 remains available for workflow reproducibility. Low-VRAM variants: ..._v1_1_r128.safetensors (0.91GB) and ..._v1_1_r64.safetensors (0.46GB) — SVD rank-reduced from v1.1, near-identical quality.

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 — 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 — 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" — 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" — the replace verb is trained, locality holds.
• Full-image restyles: global style with preserved composition.
• Two-input edits: scene + person as separate references — "create a photo of this man next to the tractor." Input order matters and is fixed: the scene is always image 1 ( source_latent / image ), the person is always image 2 ( source_latent_b / image_b ). Swapping them sharply degrades results (this matches the training layout).
• Composes with your LoRAs: character/body/style LoRAs stack on top and steer the prior — something closed editors structurally can't offer.

Recommended settings

• 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 (source bleed / duplication above). For v1.1 two-person edits, prefer ~1–1.5MP — at higher resolutions the two identities may blend together; generate lower and upscale instead.
• Step count is a mild dial too: fewer steps (8) favor composition adherence, more (12) favor face detail; ~10 is a good balance.
• grounding_px is a real dial. Lower values = stronger edit adherence and more uniform scene changes; higher = stronger identity/likeness. v1.1's trained range is 384–768 (768 default); 1024 often still works nicely. If you get duplicated/split compositions ("double pictures"), lower grounding_px — running far above the trained range is the most common cause. (v1's trained range was 512–1536.)
• 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 — always use the Raw/CFG 3 recipe; expect occasional re-renders instead of deletions.
• Outfit swaps are hit-or-miss — changing what a person wears sometimes works cleanly and sometimes doesn't apply; reroll or rephrase.
• Local edits aren't always perfectly local — add/remove/replace operations can sometimes alter other parts of the frame or shift the overall color grade (substantially improved in v1.1). If preservation matters, compare against the source and reroll.
• Highly unusual visual content (extravagant hairstyles, extreme body types) can drift toward the base prior — 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 (§2.3, currently <$1M/yr — above that, contact Krea for an enterprise license); deployments must implement reasonable content moderation (§4.2); AI disclosure obligations apply where required (§4.3). This repository modifies the Krea Model as permitted by §3; it is not endorsed by Krea.

Research/portfolio release by a self-funded hobbyist.

Showcase

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

v1.1 (recommended)

v1 gallery