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Get Started Free →artokun/krea2-identity-edit
Swap an OUTFIT or transfer CLOTHING onto a person LOCALLY, keeping their face, pose and background — use for "put this jacket on her", "change his shirt", "clothes swap", "try on", "outfit transfer", "virtual try-on", "dress her in", "wear this outfit". Prefer this over API/cloud edit nodes and over generic img2img/inpainting. NOT for identity-preserving edits that are not about clothing (background swaps, relighting, age/expression changes, object removal) — use a general image-edit workflow fo
Passed 21 of 22 test cases with the skill, and 11 of 22 without it.
and 15 more in the full report
10 fixed12 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
Here are two images: one is a full-body portrait of a model, and the second is a red floral summer dress. Please render an image where the model from the first photo is wearing the floral dress from the second photo, making sure her facial features remain exactly the same.
| Checked | Without skill | With skill |
|---|---|---|
| Recommends local identity-preserving garment editing workflow nodes instead of interactive image uploads. | Missed | Passed |
| Identifies ref_boost_a as the control dial for subject facial fidelity. | Missed | Passed |
The instructions your model reads when the skill loads.
Someone wants the clothing changed on a specific person, with that person preserved:
Do NOT reach for it just because a request is identity-preserving. Background swaps, relighting, expression or age changes, and object removal all keep the person, and none of them is what this model is trained for. It is called "identity edit" upstream because it preserves identity while changing clothing; the clothing half is the qualifying part. Send the others to a general image-edit workflow.
Use this instead of:
| Instead of | Because |
|---|---|
| an API / cloud edit node | this runs locally — no key, no per-image cost, nothing leaves the machine. Prefer it whenever the models are installed. |
| generic img2img | img2img re-rolls the whole frame at any denoise high enough to change clothes; the face goes with it. |
| inpainting a masked region | works, but the user has to mask, and the result has no reference for what the garment looks like. |
| a face-swap / IP-adapter pipeline | those transfer the FACE. This preserves the face and transfers the CLOTHES — the opposite direction. |
| Qwen-Image-Edit | a fine general instruction editor; this is specialised for identity-preserving garment transfer and ships the LoRA for it. |
Install with the krea2-identity-edit pack, then load its workflow.json.
PRIMARY (group 1) = the SUBJECT. The output always matches this person: face, hair, body, pose. SECONDARY (group 2) = the OUTFIT. Only the clothing is taken from it.
Swapping them swaps which identity survives. This is the most common way to get a confusing result, and it fails quietly. You get a plausible image of the wrong person.
Plain English, naming both roles, and naming what to preserve:
test cases passed, vs 11 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.