Edit
Outfit swap on a full-body or three-quarter photo — keep pose and identity, change garments with fabric-realistic drape.
Pose stays, threads change.
Fashion ecommerce, lookbook iteration, dating-profile refreshes, and costume prototyping all need the same thing: believable garment replacement on a real photo without plastic face swaps. Upload a portrait or three-quarter shot, describe the new outfit in plain language, optionally lock face and hair preservation, and pick a style era to bias silhouette choices. The model is steered to keep pose, background, and lighting continuity; only the wardrobe changes. Output respects identity and skips the uncanny morphing that defeats the purpose.
Five inputs for credible wardrobe iteration.
Each era biases silhouette, fabric, and accessory choices.
Modern casual
Current denim, sneakers, layered basics — the default for everyday social and dating use.
Suiting + dresses
Tailored construction, classic palettes, conservative accessories — for professional headshots.
Decade-specific
Oversized silhouettes, mom jeans, color-block — for creative campaigns and editorial shoots.
Formal occasion
Cocktail dresses, tuxedos, structured gowns — for event invitations and editorial stylings.
Active casual
Technical fabrics, performance fits, athletic accessories — for fitness and lifestyle brands.
Wardrobe-swap moments where reshoots are too expensive.
The point is wardrobe iteration, not identity replacement.
Generic AI photo editors love to drift on faces — small changes to lighting and tone become subtle facial restructuring that erodes identity over a few iterations. This template defaults to face preservation ON because the use case is wardrobe-first: you want the same person in different clothes, not a new person in your clothes. When face preservation is on, the model anchors facial features and lets only the garments change. Turn it off only when the use case genuinely calls for a more expressive edit, and never when consent is unclear.
Habits that compound across fashion and personal-brand work.
No — the tool is for clothing replacement on dressed subjects with consent. Misuse violates policy and applicable laws around non-consensual imagery.
With face preservation toggled on, identity remains stable across the swap. Some subtle drift is normal; verify before publishing in identity-sensitive contexts.
The tool focuses on garments, not bodies. Some silhouette change happens naturally when going from form-fitting to oversized, but body morphing is intentionally out of scope.
Best results are on single-subject photos. Group shots often need targeted edits per person via the AI Image Editor instead.
For marketing or editorial use, yes — but you must own rights to the source photo and the depicted person must have consented to AI editing of their image. Always disclose where context demands.
Image-edit-capable models tuned for identity preservation. Defaults work well; switch when one model struggles with a particular fabric or pose.
Describe fabric weight and finish — "raw denim, structured" beats "jeans." Material vocabulary translates directly into render quality.
Cheaper than the fitting room line.
Explore palette and silhouette directions fast, then take the winning concept to a real fitting or shoot. The iteration cost difference is the entire point — you settle on a direction in pixels before committing to fabric.