

Virtual Fashion Model
Generative output can vary; review the full result before publishing
Between a flat-lay and a booked shoot there is a gap where decisions get made — which pieces make the range, how a silhouette reads, what the styling should be. This direction fills that gap by visualising a supplied garment on a virtual figure, and is deliberate that the result belongs in the decision, not in the shop window.
- Prepared Virtual Fashion Model direction
- Editable prompt and explicit output controls
- Full-result review required
Generative output can vary; review the full result before publishing
Choose a source image for Virtual Fashion Model
JPG, PNG, WebP, HEIC, and other supported formats. Free up to 20 MB; Premium and higher up to 50 MB for this tool.
Set up for Virtual Fashion Model
Prepared settings
- Starting point
- Upload one source image
- The page opens on the correct edit workflow; upload is the only required setup step.
- Prepared workflow
- Prepared Virtual Fashion Model workflow
- Virtual Fashion Model opens with the Virtual Fashion Model direction preselected, so there is no need to find the operation manually.
- Output shape
- 4:3
- The recommended composition is selected automatically and can be changed before processing.
- Review rule
- Review the complete generated result before use
- Generated imagery can vary; the final result stays under the user's approval before download.
Best-fit uses
- Range reviews before committing to production
- Styling direction ahead of a booked shoot
- Internal presentations of a collection in progress
Frequently asked questions
- How is this different from the model generator?
- They overlap heavily and are aimed at the same concept stage from different starting points — one leads with the model presentation, the other with the garment. Use whichever framing matches how you are thinking about the problem; the honesty limits are identical.
- Can virtual models replace fit models?
- No. A fit model exists to tell you the garment is wrong — where it pulls, rides or gapes on a real body. A virtual figure cannot report any of that, and treating it as fit validation is how sizing problems reach customers.
- Is it appropriate for diverse body representation?
- Be careful here. Generating diverse figures rather than working with real people of those bodies has been widely criticised as representation without inclusion, and it produces images that are frequently anatomically wrong. If representation is the goal, cast real models.
- What must be verified before publishing?
- Garment accuracy first — color, cut, print placement, trims — then anatomy, especially hands and how fabric meets the body. Then check the disclosure rules for the market you are publishing into, several of which now specifically cover synthetic fashion models.
- Is the model in the result a real person?
- No. The model is an AI-generated person who does not exist, created for this image — no real individual is photographed, represented, or endorsing anything. That is why there is no model release to collect. Many markets, including the EU, expect you to make clear that an image of a person was AI-generated when you publish or advertise it, so keep that disclosure with the image and check the rules for your own market and platform.
What you can do with AI Product Scene Generator
Review the main capabilities before you begin.
- Detect and protect the product automatically
- Create editorial, ecommerce, and social campaign concepts
- Generate coherent props, surfaces, lighting, and shadows
- Copy protected product pixels from the prepared source
Settings reference
5 settings
Available controls for AI Product Scene Generator.
Workflow
- Single image or Batch imagesPresets
- Process one image, or use Premium Batch images to apply the same automatic recipe to a set and download one ZIP.Options: Single imageBatch images
Scenes
- One-tap presetsPresets
- Pick a ready-made direction with one tap; generation uses the selected preset automatically.Options: Bathroom counterKitchen lifestyleOutdoor lifestyleEditorial podiumSocial ad
- Custom instructions (optional)Text input
- Describe the requested change, relevant materials, lighting, perspective, and details that must remain unchanged.
Selection
- Selection brush sizeSliderRange: 4–160px · Default: 32px
- Automatic selection is the default. Open Refine area manually and set this brush width only when the image needs a tighter edit boundary.
Output
- Ask AI to preserve subject identity and product detailsOn / Off
- Adds an explicit instruction to retain the main subject, shape, branding, labels, and readable text unless the request changes them.
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