WEARFITS Virtual Try-On API

Virtual Try-On, 3D Asset Generation & Estimated Size Fitting for Developers

Integrate AI apparel and shoe try-on, reusable digital twins, 3D product generation, and estimated clothing size recommendations into your app or storefront.

REST API endpointsOpenAPI 3.1
POST /api/v1/virtual-fitting
POST /api/v1/digital-twin
POST /api/v1/shoe-3d
POST /api/v1/size-fitting
AICLOTHING
AI / 3DSHOES
3DBAGS

Complete endpoints for fashion e-commerce

Choose the workflow your product needs. Every card maps to a documented API operation.

CLOTHING & SHOESPOST

Twin-backed try-on

/api/v1/virtual-fitting

Create a digital twin from the body input or reuse a digitalTwinId, then apply clothing or shoes to it.

Output
Try-on image + reusable digital twin
Explore the workflow
CLOTHING & SHOESPOST

Photo-to-photo try-on

/api/v1/tryon/clothing

Use personImages and productImage for a direct product preview, including a shoe. This endpoint never creates a new twin. For multiple shoe angles, use /api/v1/tryon/shoes with shoeImages.

Output
Try-on image from a person photo
Explore the workflow
CLOTHING & SHOESPOST

Reusable digital twins

/api/v1/digital-twin

Pair a face photo with a full-body photo, silhouette, clothing size, or body measurements. Twins are cached for 30 days; reuse the digitalTwinId for later try-ons.

Output
Avatar image + digitalTwinId
Explore the workflow
CLOTHINGPOST

Estimated size fitting

/api/v1/size-fitting

Compare a measurements/clothing-size twin with body-range size charts. Synchronous and non-billable; photo/direct twins are not eligible. Recommendations are estimates.

Output
Availability, fit scores + size recommendations
Explore the workflow
SHOES & BAGSPOST

Shoe & bag 3D

/api/v1/shoe-3d

Turn product photos into GLB assets. Add optional AI texture enhancement and WEARFITS upload for an AR viewer link. For bags, set options.productType to other or auto.

Output
GLB model + optional AR viewer link
Explore the workflow
SHOES & BAGSPOST

Catalog digitization

/api/v1/digitization/batches

Submit up to 500 products per request, with up to 10 images per product. Track asynchronous processing for a whole catalog.

Output
Batch progress + product results
Explore the workflow

Built for your fashion application

01

Reusable digital twins

Digital twins are cached for 30 days and can be reused across virtual-fitting requests using digitalTwinId.

02

High-volume batch digitization

Submit up to 500 products per request with up to 10 images each, then track catalog processing through the batch API.

03

Asynchronous jobs

Submit image and 3D generation work, then poll GET /api/v1/jobs/{id} with the creating API key or receive a signed webhook. Size fitting is synchronous.

04

Signed webhooks

Webhooks use HMAC-SHA256. Ordinary API-key requests use SHA-256 of that key as the signing secret; account and storefront flows use account-derived ownership. Job and batch callbacks use different JSON signing formats; follow the integration playbook.

30 days
Digital twin cache for repeat try-ons
500 products
Maximum per digitization batch
10 images
Maximum per batch product
OpenAPI 3.1
Published API contract

Standard HTTP. Clear API contracts.

Start with direct photo-to-photo clothing try-on. This request creates a preview job without generating a digital twin.

Run on your backend. Replace example.com URLs with accessible images you are authorized to use, set WEARFITS_API_KEY, then use the returned jobId. The response below is an illustrative excerpt. Poll with the same API key that created the job.

View integration documentation ↗
WEARFITS API

01 · SUBMIT

curl https://api.wearfits.com/api/v1/tryon/clothing \
  -H "X-API-Key: $WEARFITS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "personImages": ["https://example.com/person.jpg"],
    "productImage": "https://example.com/shirt.jpg",
    "productCategory": "top"
  }'

02 · RESPONSE EXCERPT

{
  "jobId": "YOUR_JOB_ID",
  "statusUrl": "https://api.wearfits.com/api/v1/jobs/YOUR_JOB_ID"
}

03 · POLL WITH THE SAME KEY

curl https://api.wearfits.com/api/v1/jobs/YOUR_JOB_ID \
  -H "X-API-Key: $WEARFITS_API_KEY"
Example WEARFITS dashboard with a product catalog, account usage, and workspace tools.
Dashboard preview · Example account data

Your API and catalog in one workspace

  • API keys: Manage the credentials your backend uses to call WEARFITS services.
  • Product catalog: Organize product images and 3D assets in your account workspace.
  • Usage overview: Review account usage and allowances. Available features depend on your account.
Open dashboard ↗

Choose the right access as your catalog grows

API usage, AR storefront plans, and integration support serve different needs. Check current terms for your account.

AI workflows

AI API usage

Plan for the try-on, digital twin, and 3D generation operations your application uses. Check the current commercial terms for your account.

Your implementation

Integration support

Discuss your storefront, catalog size, and technical requirements with WEARFITS to choose an appropriate integration and access arrangement.

Hosted UI or your own experience

The hosted iframe is the recommended full UI and size-fitting path. Choose the direct API when you own the backend and interface.

Hosted iframe

WEARFITS hosts the complete try-on UI and size-fitting overlay. The storefront does not expose an API key. Follow READY/INIT and product handoff in the guide.

Direct API

Build a custom experience with documented REST endpoints. Keep your API key private on your server, submit jobs, then poll or receive a signed webhook.

Lightweight widget

Load /widget/tryon.js for an API-backed modal. It does not include the hosted size-fitting overlay. Use a server-side proxy to keep your API key private.

The widget is a lightweight API-backed modal without the hosted size-fitting overlay; for the complete UI use the hosted iframe.

Hosted size fitting: product contract and eligibility

Embed https://tryon.wearfits.com/?sizeFitting=true. Put the optional sizeChart sibling field on each WEARFITS_INIT.payload.products[] item; SET_PRODUCTS uses the same product shape. The chart requires version: 1, basis: "body", unit: "cm" or "in", and body ranges for height, chest, waist, hip, or inseam. Size guidance requires a measurements/clothing-size twin with a stored body profile. A full-body/photo input can still produce try-on results but does not produce size guidance. For a direct integration, call POST /api/v1/size-fitting with the eligible digitalTwinId and chart after the twin job completes.

Use a body basis and cm or in units, rather than garment dimensions. Read the hosted integration guide

How to add WEARFITS virtual try-on
  1. Choose an integration path

    Use the hosted iframe for a storefront and the complete try-on plus size-fitting UI; use the direct API when you own the backend and UI; choose the lightweight widget only when its API-backed modal is sufficient.

  2. Start with the hosted guide

    Follow https://tryon.wearfits.com/docs/integration.html for READY/INIT and base product handoff. Put the optional sizeChart sibling field on each WEARFITS_INIT.payload.products[] item; SET_PRODUCTS uses the same product shape. The chart requires version 1, basis "body", unit "cm" or "in", and body ranges for height, chest, waist, hip, or inseam. Test https://tryon.wearfits.com/demo_tryon.html. The hosted storefront integration does not expose a service API key.

  3. Authenticate a direct integration

    For a custom backend and UI, check each operation and its security overrides at https://api.wearfits.com/doc and keep required credentials server-side.

  4. Run and track direct jobs

    Submit the documented digital-twin or virtual-fitting operation, then poll GET /api/v1/jobs/{jobId} or use a signed webhook until completion.

WEARFITS API

Read the full FAQ ↗
Which endpoint should I use for virtual try-on?

POST /api/v1/virtual-fitting always creates or reuses a digital twin. POST /api/v1/tryon/clothing uses a person photo, or the image of an existing digitalTwinId, without generating a new twin. Both support productImage for a direct two-image try-on.

Which digital twin inputs are supported, and how long are twins cached?

For POST /api/v1/digital-twin, supply faceImage plus exactly one body input: bodyPhotoUrl, silhouetteImage, clothingSize, or bodyMeasurements. Inline POST /api/v1/virtual-fitting photo mode requires faceImage plus photoUrl for new generation. Digital twins are cached for 30 days; save the completed job’s digitalTwinId to reuse the avatar.

Does virtual try-on provide an exact size recommendation?

No. A try-on image is a visual preview. POST /api/v1/size-fitting separately returns estimated size guidance using an eligible measurements/clothing-size twin and merchant body-range charts. Photo/direct twins return available: false. This synchronous operation is non-billable.

How do I receive generated results?

Generation runs asynchronously; cache hits may already be completed. Poll GET /api/v1/jobs/{jobId} with the same authentication ownership. Merchant and bare service keys must use the submitting key and support private-key-derived HMAC webhook verification. Prefer authenticated polling for account-attributed and storefront requests; see /llms-full.txt for callback limitations and verification.

Can I generate 3D shoes and bags for AR?

POST /api/v1/shoe-3d generates GLB assets from product photos, with optional texture enhancement and WEARFITS AR upload. For bags, set options.productType to "other" or "auto". POST /api/v1/digitization/batches accepts up to 500 products and 10 images per product. Live AR is a separate viewer experience, not the photo try-on endpoint.

Should I use the hosted iframe, REST API, or widget?

For storefronts, use the hosted iframe for the complete try-on and size-fitting UI. Use the REST API from your backend when building your own UI. The lightweight /widget/tryon.js modal does not include the hosted size-fitting overlay. Keep merchant and service API keys server-side; use a storefront token or backend proxy for browser integrations.

Where is the machine-readable API specification?

The OpenAPI 3.1 specification is available at https://api.wearfits.com/doc, with an interactive reference at /reference. AI agents can start at /llms.txt, read /llms-full.txt, and use the Markdown guides under /docs/.

Virtual try-on, 3D assets & estimated size fitting for developers