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FASHNAI

Product to Model

Powered by best-in-class image editing AI, the Product to Model endpoint transforms product images into people wearing those products, with optional guidance from an inspiration image, background, or face reference.

This endpoint is designed specifically for wearable fashion items such as clothing, shoes, hats, jewelry, bags, and accessories.

Model Specifications
  • Model Name: product-to-model
  • Lifecycle: preview
  • Processing Time: 10s–55s (+20s with face_reference, see below)
  • Output Formats: PNG, JPEG
  • Delivery Methods: URL or Base64 encoding
  • Credits: 1-5 per output image depending on resolution and generation_mode (+3 per output image with face_reference)
Combining a product with an existing model image

To place a product on an existing person image while preserving that image's pose and background, use the tryon-max endpoint with model_image. On Product to Model, a model's identity is passed via face_reference instead, and the endpoint generates a new image of that person wearing the product; it does not replace the clothing or keep the pose and background of the reference photo.

Request

Generate product-to-model images by submitting your product image to the universal /v1/run endpoint:

POSThttps://api.fashn.ai/v1/run

Request Examples

curl -X POST https://api.fashn.ai/v1/run \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer YOUR_API_KEY" \
     -d '{
           "model_name": "product-to-model",
           "inputs": {
             "product_image": "http://example.com/path/to/product.jpg",
             "prompt": "professional office setting",
             "output_format": "png",
             "return_base64": false
           }
         }'

Response

Returns a prediction ID for status polling:

{
  "id": "123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1",
  "error": null
}

Request Parameters

product_image
Required
image URL | base64

URL or base64 encoded image of the product to be worn. Supports clothing, accessories, shoes, and other wearable fashion items.

image_promptimage URL | base64

Optional URL or base64 encoded inspiration image that guides pose, environment, and lighting while keeping the product centered in the final output.

Default: None

face_referenceimage URL | base64

Optional face identity reference to guide who the generated person should look like. When provided, the pipeline refines identity to match the reference while keeping product fidelity. Using a face reference typically adds around 20 seconds to the processing time.

Default: None

face_reference_mode'match_base' | 'match_reference'

Controls how the identity from face_reference influences pose and expression.

-match_reference favors the reference face’s pose and expression for maximum resemblance.

-match_base gives more weight to the prompt (or system default prompt if omitted) when generating the person's pose and expression.

Default: match_reference

promptstring

Additional instructions for person appearance, styling preferences, or background.

Examples: "man with tattoos", "tucked-in", "open jacket", "rolled-up sleeves", "studio background".

Default: None

aspect_ratiostring

Desired aspect ratio for the output image. If omitted, the generation inherits the aspect ratio from the most specific image supplied (background_referenceimage_promptproduct_image). Provide an explicit ratio to override that default even when using these image references.

Supported ratios: "1:1", "3:4", "4:3", "9:16", "16:9", "2:3", "3:2", "4:5", "5:4"

Default: Aspect ratio of the most specific image supplied

resolution'1k' | '2k' | '4k'

Output resolution tier. '1k' produces ~1 megapixel output, '2k' ~4 megapixels, and '4k' ~16 megapixels. Exact output dimensions depend on this tier and the image aspect ratio.

Default: '1k'

generation_mode'fast' | 'balanced' | 'quality'

Sets the generation quality level. 'quality' produces the most detailed and realistic output but takes longer to process and costs more credits. 'fast' prioritizes speed and lower cost. If omitted, FASHN selects generation_mode automatically. For product-to-model, omitted generation_mode is currently billed as 'fast' at 1k and as 'balanced' at 2k or 4k.

background_referenceimage URL | base64

Background image used as the backdrop for generation. Ensures location consistency across generations. If a person appears in the image, they will be ignored and only the background will be used.

When provided alongside image_prompt, image_prompt governs the model's appearance, pose, and styling, while background_reference anchors the scene.

Default: None

seedinteger

Seed for reproducible results. Must be between 0 and 2^32-1.

Default: 42

num_imagesinteger

Number of images to generate in a single request. Must be between 1 and 4. Additional images consume more compute (and credits) and can increase processing time.

Default: 1

output_formatstring

Output image format.

  • "png" - PNG format, original quality
  • "jpeg" - JPEG format, smaller file size

Default: "png"

return_base64boolean

When set to true, the API will return the generated image as a base64-encoded string instead of a CDN URL. The base64 string will be prefixed data:image/png;base64,....

This option offers enhanced privacy as user-generated outputs are not stored on our servers when return_base64 is enabled.

Default: false

Credit Cost

generation_mode \ resolution1k2k4k
fast123
balanced234
quality345

Additional pricing rules:

  • face_reference adds +3 credits per output image.
  • num_images multiplies the total cost by the number of outputs requested.
  • If generation_mode is omitted, automatic pricing applies.

Processing Time

Processing time depends on both resolution and generation_mode. The fastest configuration (fast + 1k) typically completes in around 10 seconds, balanced at 2k finishes in around 25 seconds, and the most intensive combination (quality + 4k) typically takes around 55 seconds. Using face_reference typically adds around 20 seconds on top of any configuration. Actual latency may vary with current server load.

Response Polling

After submitting your request, poll the status endpoint using the returned prediction ID. See API Fundamentals for complete polling details.

Successful Response

When your product-to-model generation completes successfully, the status endpoint will return:

{
  "id": "123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1",
  "status": "completed",
  "output": [
    "https://cdn.fashn.ai/123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1/output_0.png"
  ],
  "error": null
}

Runtime Errors

Runtime errors for Product to Model use the shared set in Error Handling.

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