AIClothSwap is an online AI clothes swap and virtual try-on tool, positioned as a free AI clothes swap and virtual try-on studio for stylists, e-commerce, and content creators.
Use Users upload a photo of a person and one or more clothing reference images to preview or replace an entire outfit on the photo. The official description emphasizes that the tool does more than change a single garment; it completes a full head-to-toe outfit change in one go, including tops, bottoms, shoes, hats, and bags, while keeping skin tone texture, lighting, and proportions as natural and consistent as possible.
Main capabilities
- Full outfit change: Replace multiple garments at once, combining tops, bottoms, footwear, and accessories into one coordinated new look.
- Background and pose editing (Studio Quality): Use the optional instruction box to describe in natural language a clean studio background, a minimalist beige wall, or a specified pose (such as arms crossed, glancing sideways, hands in pockets, a look back over the shoulder), while also changing the outfit. You can also lock the person and pose, changing only the clothing and scene.
- Smart body and clothing detection: Automatically recognizes the human silhouette and clothing areas, fits clothing according to natural proportions, aligns texture, folds, and lighting, and preserves the look of the original photo.
- No clothing image mode: Under Studio Quality, you can skip uploading a clothing photo and directly describe the desired look, occasion, or scene (such as "beach vacation outfit," "black-tie dinner gown," or "cozy winter street style"), and the AI generates the outfit on the user's own photo.
- Presets and popular try-ons: Provides capabilities such as editing garment drape (turning a flat-lay photo into a model image from any angle) and handling complex textures, as well as popular entry points such as virtual dress try-on, wedding dress try-on, graduation outfit try-on, prom dress try-on, clothes color change, dress color change, AI outfit generator, and men's outfit generator.
How to use
- Upload a photo: Drag and drop or upload a clear portrait to the online clothes swap tool.
- Start AI clothes swap: Choose a style (top, dress, full outfit) and click Start.
- Get a new look: Instantly preview the virtual try-on result, fine-tune it, and download. Free account results carry a watermark, the first day's free quota is added automatically, and 10 credits can be claimed again the next day; login is required before generation (each eligible user can claim 10 credits daily). Paid plans include monthly (750 credits per month, about 75 outfit changes, no watermark for that account after purchase, includes Studio Quality, priority generation queue, and commercial license) and annual (first year $89.90, original price $179.80, billed annually, one-time 10,000 credits, approximately 1,000 outfit swaps per year, renewal price $179.80/year) as well as one-time credit packs (credits never expire, applicable to all quality tiers, approximately 15/40/100/200 outfit swaps, prices in USD, annual plans renew annually, credit packs are one-time, can be canceled at any time through the billing portal). Studio Quality supports image editing, up to 6 images, and preserves faces, clothing, and details more precisely; Priority Generation places each outfit swap into a priority queue when a paid account has credits.
Use cases and limitations Suitable for online sellers to have the same model cover an entire catalog, content creators to test looks before a shoot, shoppers to see how a jacket looks on themselves, designers to create colorways before mass production, and small brands to fill a lookbook without a second shoot. The official recommendation is to start with photos that are clear, well lit, with the person facing the camera and the current outfit visible from shoulder to hip, avoiding heavy shadows, motion blur, and busy patterns that obscure body lines; for garment reference images, it is recommended to use flat-lay or ghost mannequin images on a solid background so the AI can read seams, necklines, and fabric weight. Output quality depends on input quality, and the first result can be treated as a draft and regenerated repeatedly.
Regarding data processing security, mobile support, outfit swap duration, specific rules for sharing or selling results, the difference from virtual try-on, how e-commerce teams use it, and other common questions, the official text only lists the question titles and does not yet provide specific answer content.
