FASHN Virtual Try-On v1.6

Virtual Try-On v1.6 enables realistic garment visualization using just a single photo of a person and a garment. It’s our most advanced AI model for try-on experiences, designed to deliver high-quality, detailed results with minimal setup.

Model Specifications

Model Name: tryon-v1.6
Lifecycle: stable
Processing Resolution: 864×1296 pixels
Processing Time:
- Performance: 5 seconds
- Balanced: 8 seconds
- Quality: 12–17 seconds (variable depending on input resolution)
Credits: 1 per image

Request

Generate a virtual try-on by submitting your model and garment images to the universal /v1/run endpoint:

POST`https://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": "tryon-v1.6",
           "inputs": {
             "model_image": "http://example.com/path/to/model.jpg",
             "garment_image": "http://example.com/path/to/garment.jpg"
           }
         }'

Response

Returns a prediction ID for status polling:

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

Request Parameters

Required Parameters

`model_image`
Required
image URL | base64

Primary image of the person on whom the virtual try-on will be performed.

Models Studio users can use their saved models by passing saved:<model_name>.

`garment_image`
Required
image URL | base64

Reference image of the clothing item to be tried on the model_image.

Base64 Format

Base64 images must include the proper prefix (e.g., data:image/jpg;base64,<YOUR_BASE64>)

Optional Parameters

`category`'auto' | 'tops' | 'bottoms' | 'one-pieces'

Use auto to enable automatic classification of the garment type. For flat-lay or ghost mannequin images, the system detects the garment type automatically. For on-model images, full-body shots default to a full outfit swap. For focused shots (upper or lower body), the system selects the most likely garment type (tops or bottoms).

Default: auto

`segmentation_free`boolean

Direct garment fitting without clothing segmentation, enabling bulkier garment try-ons with improved preservation of body shape and skin texture. Set to false if original garments are not removed properly.

Default: true

`moderation_level`'conservative' | 'permissive' | 'none'

Sets the content moderation level for garment images.

-conservative enforces stricter modesty standards suitable for culturally sensitive contexts. Blocks underwear, swimwear, and revealing outfits.
-permissive allows swimwear, underwear, and revealing garments, while still blocking explicit nudity.
-none disables all content moderation

Default: permissive

Responsible Use Notice

This technology is designed for ethical virtual try-on applications. Misuse—such as generating inappropriate imagery without consent—violates our Terms of Service.

Setting moderation_level: none does not remove your responsibility for ethical and lawful use. Violations may result in service denial.

`garment_photo_type`auto | flat-lay | model

Specifies the type of garment photo to optimize internal parameters for better performance. 'model' is for photos of garments on a model, 'flat-lay' is for flat-lay or ghost mannequin images, and 'auto' attempts to automatically detect the photo type.

Default: auto

`mode`performance | balanced | quality

Specifies the mode of operation.

-performance mode is faster but may compromise quality
-balanced mode is a perfect middle ground between speed and quality
-quality mode is slower, but delivers the highest quality results.

Default: balanced

`seed`int

Sets random operations to a fixed state. Use the same seed to reproduce results with the same inputs, or different seed to force different results.

Default: 42
Min: 0
Max: 2^32 - 1

`num_samples`int

Number of images to generate in a single run. Image generation has a random element in it, so trying multiple images at once increases the chances of getting a good result.

Default: 1
Min: 1
Max: 4

`output_format`'png' | 'jpeg'

Specifies the desired output image format.

-png: Delivers the highest quality image, ideal for use cases such as content creation where quality is paramount.
-jpeg: Provides a faster response with a slightly compressed image, more suitable for real-time applications like consumer virtual try-on experiences.

Default: png

`return_base64`boolean

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 according to the output_format (e.g., data:image/png;base64,... or data:image/jpeg;base64,...).

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

Default: false

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 virtual try-on 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
}

The output array contains URLs to your generated try-on images showing the model wearing the specified garment. The number of images depends on the num_samples parameter (default: 1).

Runtime Errors

Try-On shares the common runtime errors in Error Handling. Additional endpoint-specific errors:

Name	Cause	Solution
`PoseError`	The pipeline was unable to detect a body pose in either the model image or the garment image (when `garment_photo_type: "model"`).	Improve model or garment photo quality following the model photo guidelines.

For detailed implementation guidance and best practices specific to Virtual Try-On:

Try-On Parameters Guide - Detailed parameter optimization for try-on models
Python Quickstart Guide - Complete Python implementation examples
JavaScript Quickstart Guide - Frontend integration patterns
Image Preprocessing Best Practices - Optimize your input images for better results
Data Retention & Privacy - Understand how FASHN handles your data

FASHN Virtual Try-On v1.6

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

Response

model_imageRequiredimage URL | base64

garment_imageRequiredimage URL | base64

category'auto' | 'tops' | 'bottoms' | 'one-pieces'

segmentation_freeboolean

moderation_level'conservative' | 'permissive' | 'none'

garment_photo_typeauto | flat-lay | model

modeperformance | balanced | quality

seedint

num_samplesint

output_format'png' | 'jpeg'

return_base64boolean

On this page