Virtual Outfit Try-On
E-commerce fashion display
Virtual Outfit Try-On
E-commerce fashion display
Showcase
Description
Uses the user-uploaded person photo as the sole source for the person, generating photorealistic images of that person wearing multiple different outfits. It strictly preserves real identity features—no face swapping or facial feature changes. The GPT image model is used by default, and the number of outfits is confirmed with the user before generation. Best for: fashion e-commerce owners, brick-and-mortar clothing store owners, and fashion influencers who sell through livestreams
Recommended by
Dancang
Why we love this skill
Uses one source photo, confirms the materials, outfit direction, and quantity, then checks consistency across each look—preserving clothing detail and natural smartphone-snapshot realism.
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ImageSame Model, New Outfits
AI virtual fitting room: Upload a person photo (+ clothing photo) to generate e-commerce-ready outfit swaps with the same face kept consistent across images and clothing reproduced faithfully. Supports: outfit swaps (one person, one scene, multiple outfits), scene swaps (one person, one outfit, multiple scenes), and full-season batches (a complete set of product detail images in one go); it also supports pet outfit swaps and pure white e-commerce backgrounds. Trigger when users say “change the outfit,” “try on clothes,” “help me change the clothes and generate an image,” “clothing product detail images,” “model photos,” “lookbook,” “styling images,” “wholesale market product images,” “on-model images,” “dress the pet,” or “change the scene while keeping the clothes unchanged.” Core rules: three locks (identity/clothing/scene), change only one thing per image, lock clothing down to the buttons, and keep colors neutral without color casts. The default canvas matches the uploaded image, and the aspect ratio can also be customized.
AI Try-On Video Generator
Transform a portrait and clothing images into a first-person interactive vertical short video for virtual try-on. [Input] * Portrait photo (optional): maintains face and person consistency if provided; otherwise automatically generates a matching protagonist based on style * 1-4 clothing images: tops, bottoms, shoes, bags, or accessories, with the upload order matching the dressing sequence * Optional parameters: style, scene, interactive effects, duration, and video count [Output] 9:16 vertical virtual try-on short video. The character remains consistent throughout, the scene is unchanged, clothing strictly matches the uploaded images and is put on one by one by "first-person hands," concluding with a full look freeze-frame. [Core Differences] * Two workflows: storyboard generation followed by video synthesis (controllable, precise clothing order) or direct one-step video generation (fast, suitable for batch production with few garments) * Full automation: automatically generates a matching protagonist without a portrait photo for zero threshold entry * Consistency locking: stable face, hairstyle, scene, and clothing style without drifting across the video * Default compliance: built-in clothing whitelist and negative words with initial styling forced to modest base layers, preventing prohibited content such as underwear, swimwear, stockings, or translucent items for immediate publishing [Who Is It For] * Fashion bloggers and content creators: try three outfits in one video and test styling without wearing them physically * E-commerce and apparel merchants: turn new arrivals into dynamic videos instantly, eliminating model and studio costs for content creation * Xiaohongshu/Douyin/TikTok operators: batch-produce hook videos featuring auto-dressing characters with completion rates higher than static outfit posts * Fashion styling educators, stylists, and buyers: quickly demonstrate multiple outfit options to clients * Independent designers and white-label sellers: create model showcase videos without physical photo shoots [Monetization Opportunities] * E-commerce sales: drive traffic with product links in videos and close sales directly using before-and-after try-on comparisons * Brand commercial deals: batch-produce promotional content for clothing brands with one style per video at a fraction of live-action shoot costs * Account growth: build series columns around try-on videos to grow accounts and monetize through traffic rewards and brand sponsorships * Asset resale: sell generic try-on template packs to peers or use them as training cases for coaching tutorials * Cost reduction for personal use: build an in-house product video asset library, saving time and money on repeated shoots [Applicable Scenarios] Outfit channel content production, e-commerce new arrival showcases, AI short video matrix marketing, outfit styling demos, social media grid posts, and client pitch samples.
VideoVirtual Try-On Video Generator
[Target Audience]: Apparel store owners, fashion bloggers, shopping short video creators, brand new arrivals, and transformation content for platforms like Xiaohongshu and Douyin. [Features]: Consistent face and accurate clothing colors: each outfit is independently generated using "character + that outfit" 6 mature styles, plus support for custom scenes Automatically matches YouMind's image and video models, defaulting to the most stable combination Generates images first, waits for your confirmation, then generates videos to save video credits [Styles or Scenes]: 1. Fisheye Glare: circular fisheye + flare jump cuts, trendy, fast, eye-catching 2. Magazine Editorial: neutral grey background + slow push-in + cross dissolve, high texture 3. Street Snap Camera: street walking + whip pan outfit change, authentic lifestyle feel 4. Retro Film: grain + date stamp + film burn edges, nostalgic and artistic 5. Beat Sync Transformation: fixed camera + snap/spin instant outfit change, great with music 6. Selfie Vlog: front phone camera perspective + hand-covering-lens outfit change, great for product recommendations · Defaults to style 1 if unselected; you can also write "I want something like a Japanese magazine style" or "in a coffee shop", etc. [One-Sentence Summary]: You just need to upload a portrait photo (or skip it, and a matching model will be automatically generated) and 3 to 6 clothing images, then choose a style: Fisheye Glare, Magazine Editorial, Street Snap Camera, Retro Film, Beat Sync Transformation, or Selfie Vlog, or directly describe your desired scene. It first profiles each piece of clothing, locks in the same character, and then sequentially generates final look images, storyboard keyframes, and video clips, finally providing an editing and transition list accurate to the second. Every step can be confirmed and redone individually without starting over from scratch.
Information
- Version
- v3
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
