sandbase-ai/cat-vton

Name: try-on
Author: sandbase-ai

Cat Vton by sandbase-ai - AI-powered image editing, style transfer, and transformation. Edit photos with natural language instructions, remove backgrounds, change styles, and enhance images effortlessly.

Input

Aspect Ratio(string)

The aspect ratio of the generated image. Allowed values: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.

Guidance scale (CFG)(number)

020

The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. Range: 0 to 20.

Num Inference Steps(integer)

150

The number of inference steps to perform. Range: 1 to 50.

Seed(integer)

The same seed and the same input given to the same version of the model will output the same image every time.

Cloth Type(string)

Type of the Cloth to be tried on. Options: upper: Upper body cloth lower: Lower body cloth overall: Full body cloth inner: Inner cloth, like T-shirt inside a jacket outer: Outer cloth, like a jacket over a T-shirt Allowed values: upper, lower, overall, inner, outer.

Image URL or upload(string)

Upload

PNG, JPEG, WebP, or GIF · 20 MiB maximum

Url to the garment image.

Image URL or upload(string)

Upload

PNG, JPEG, WebP, or GIF · 20 MiB maximum

Url for the human image.

Idle

Example output — click Run to generate your own

Production endpoint

Send your first request

OpenAI-compatible endpoint with unified authentication and usage tracking.

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

Model IDsandbase-ai/cat-vton

Input Schema

7 parameters · 0 required · 7 optional

Parameter	Type	Required	Description
`seed`	integer	Optional	The same seed and the same input given to the same version of the model will output the same image every time.
`cloth_type`	string	Optional	Type of the Cloth to be tried on. Options: upper: Upper body cloth lower: Lower body cloth overall: Full body cloth inner: Inner cloth, like T-shirt inside a jacket outer: Outer cloth, like a jacket over a T-shirt · Options: upper, lower, overall, inner, outer upperloweroverallinnerouter
`aspect_ratio`	string	Optional	The aspect ratio of the generated image. · Options: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16 21:916:93:24:35:41:14:53:42:39:16
`guidance_scale`	number	Optional	The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. · Min: 0 · Max: 20 · Default: 2.5
`human_image_url`	string	Optional	Url for the human image.
`garment_image_url`	string	Optional	Url to the garment image.
`num_inference_steps`	integer	Optional	The number of inference steps to perform. · Min: 1 · Max: 50 · Default: 30

Output Schema

Field	Type	Description
`id`	string	Unique identifier for the generation task
`status`	string	Task status: pending, running, completed, failed, timeout
`model`	string	Model used for the generation
`outputs`	array	Array of output items
`outputs[].url`	string	URL of the generated artifact
`outputs[].content_type`	string	MIME type (e.g. image/png, video/mp4)
`error`	object \| null	Error details if failed, null on success
`error.type`	string	Machine-readable error type code
`error.message`	string	Human-readable error description

Async Workflow

This model uses asynchronous execution. Submit a request and poll for the result.

Submit — POST to /v1/run, receive an id
Poll — GET /v1/run/{id} until status is completed, failed, or timeout
Retrieve — Read outputs from the completed response

Code Examples

Ready-to-run snippets

# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
  "model": "sandbase-ai/cat-vton",
  "cloth_type": "upper",
  "guidance_scale": 2.5,
  "human_image_url": "https://static.sandbase.ai/examples/bfl/flux-2/virtual-tryon/input_images_0.png",
  "garment_image_url": "https://static.sandbase.ai/examples/bfl/flux-2/virtual-tryon/input_images_1.png",
  "num_inference_steps": 30,
  "prompt": "a beautiful sunset over mountains"
}'

# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
  -H "Authorization: Bearer YOUR_API_KEY"

← Back to try-on

API README

CatVTON

CatVTON occupies the generated-image role in the model catalog for design-system owners. Its practical value is to make endpoint selection explicit before implementation begins: an upstream service can confirm that it has no mandatory payload beyond the declared contract, submit one well-scoped job, and receive a generated image asset for downstream approval. This positioning explains when the exact sandbase-ai/cat-vton route belongs in an architecture without borrowing promises from another version, tier, or task variant.

A low-risk adoption path begins by checking the creative brief, policy constraints, and destination format. The caller records required values separately from optional choices such as seed, cloth_type, aspect_ratio, guidance_scale, human_image_url, garment_image_url, runs a small representative sample, and stores the route name with the resulting artifact. Reviewers then compare that artifact with the agreed acceptance criteria, document any rejected setup, and promote only a successful request shape into larger batches. This workflow gives sandbase-ai/cat-vton measurable business context while leaving the Highlights section to explain model behavior.

Highlights

Prompt-responsive composition. try-on turns detailed natural-language art direction into a complete visual with a defined subject, setting, and treatment.
Style range. The route can interpret photographic, illustrative, graphic, or conceptual direction when those choices are stated clearly in the prompt.
Layout control. Supported framing and composition controls help try-on prepare imagery for landscape, square, portrait, or design-specific placements.
Iteration-ready output. Seed and other declared creative controls make it practical to compare focused variations while retaining the core brief.

Pricing

Billing option	Price
Per request	`$0.001250`

When to Use

Scenario	Why it fits
Choose CatVTON	Use it when the job specifically calls for cat vton and the route’s documented input contract matches assets already available in your workflow.
Keep the request reproducible	Use the required inputs explicitly, then record optional choices alongside the prompt for repeatable reruns.
Build controlled creative variations	Change one declared control at a time when comparing framing, format, duration, resolution, style, or other route-supported output decisions.
Integrate asynchronous delivery	Use this endpoint when an application can submit work, track completion, and collect the returned media URL instead of requiring an immediate inline artifact.
Validate before a large batch	Run representative prompts and source assets first, confirm the visual or audio behavior, then lock the successful request shape for scaled production.

Prompt Guide

Lead with the subject or transformation, then add the composition, environment, style, lighting, motion, voice, or fidelity details relevant to this route. Keep every parameter inside the documented schema; the example below uses only fields declared for sandbase-ai/cat-vton.

{
  "cloth_type": "upper",
  "aspect_ratio": "21:9"
}

Technical Specs

Specification	Details
Model ID	`sandbase-ai/cat-vton`
Execution mode	`async`
Task type	`image`
`seed`	`integer` · optional
`cloth_type`	`string` · optional · choices: `upper`, `lower`, `overall`, `inner`, `outer`
`aspect_ratio`	`string` · optional · choices: `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16`
`guidance_scale`	`number` · optional · min `0` · max `20`
`human_image_url`	`string` · optional
`garment_image_url`	`string` · optional
`num_inference_steps`	`integer` · optional · min `1` · max `50`