Google Virtual Try-On 1.0
Google Virtual Try-On 1.0 generates a realistic try-on image from a person photo and a clothing product image. The model preserves the person's pose and identity while applying the garment, so fashion and product teams can preview outfits without a photoshoot. Ideal for e-commerce try-on, character wardrobe changes, and game costume visualization.
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Google Virtual Try-On 1.0 generates a realistic try-on image from a person photo and a clothing product image. The model preserves the person's pose and identity while applying the garment, so fashion and product teams can preview outfits without a photoshoot. Ideal for e-commerce try-on, character wardrobe changes, and game costume visualization.
Connect Claude, Cursor, VS Code, or Codex to Layer’s MCP server and Google Virtual Try-On 1.0 becomes a tool your agent can reach for — it picks the parameters, runs the generation, and shows you the result in the conversation.
https://mcp.app.layer.ai/mcpAsk your agent
“Use Google Virtual Try-On 1.0 to generate 4 variations of a crystal sword icon on a transparent background.”
execute_forge({
"base_model_id": "google-virtual-try-on",
"prompt": "A crystal sword icon on a transparent background, game UI art",
"batch_size": 4,
"width": 1024,
"height": 1024
})Authenticate with a personal access token, post the model’s own form, and poll the inference until it completes. Every field below is accepted by this endpoint.
# Start the generation — returns an inference id straight away.
curl -X POST https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/base-models/google-virtual-try-on/inferences \
-H "Authorization: Bearer $LAYER_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"guidance_file_init_image": [
{
"url": "https://example.com/input.png"
}
]
}'
# Poll until status is "complete" — the response then carries the asset URLs.
curl https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/inferences/$INFERENCE_ID \
-H "Authorization: Bearer $LAYER_TOKEN"- seed integer
- The starting point for the model's randomness. The same seed and settings give the same result.
- guidance_file_init_image file[]required
- The image to modify
- guidance_file_reference_image file[]required
- Guides the edit
- output_fit any
- Trim the transparent margin, and place the image on a canvas of a fixed size.
Why use Google Virtual Try-On 1.0 for image?
High-quality image generation
Google Virtual Try-On 1.0 delivers production-ready outputs with clean structure, sharp detail, and strong prompt adherence. Ideal for character art, environments, and marketing assets.
Strong prompt control
The model interprets creative instructions with high accuracy, even when switching between different styles, lighting setups, or character directions.
Clean compositions for UA
Maintains stable framing, clear silhouettes, and high focal clarity. Assets read well at mobile sizes, making it strong for UA experiments and ad creatives.
Rapid character and cosmetic ideation with strong structure
Quickly explore character poses, cosmetic ideas, and early art directions. Clean silhouettes and expressive results help teams evaluate concepts before moving to heavier models.
Fast UA creative exploration and thumbnail testing
Generate clear, high-readability frames that work well for quick A/B testing across networks. Test multiple creative angles and iterate quickly based on results.
Lightweight environment and item exploration for LiveOps
Draft environments, themed content, shop items, and event visuals in a rapid loop. Ideal for early-stage direction setting before committing to final polish.
FAQ
How much does Google Virtual Try-On 1.0 cost? Is it free?+
How does Layer's pricing work?+
There are no seat fees, feature gates, or plans on Layer. Instead, our platform uses a consumption based system with Creative Units (CUs) with a flexible monthly subscription. Every generation on Layer (image, video, 3D, or audio) consumes a Creative Unit, and you only pay for what you create.
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