# FLUX Virtual Try-On > Generate virtual try-on results from a person image plus one or more garment references. ## Overview - **Endpoint**: `https://fal.run/fal-ai/flux-pro/v1/vto` - **Model ID**: `fal-ai/flux-pro/v1/vto` - **Category**: image-to-image - **Kind**: inference **Tags**: image-to-image, vton ## Pricing Your request will cost **$0.0375** for the first input megapixel, plus **$0.005** per extra input megapixel and **$0.005** per output megapixel, rounded up to the nearest megapixel. Each input image is rounded up independently before being summed. For example, two 1024x1024 input images with a 1024x1024 output will cost **$0.0475** (**$0.0375** for the first input megapixel + **$0.005** for the second input megapixel + **$0.005** for the output megapixel). For more details, see [fal.ai pricing](https://fal.ai/pricing). ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`prompt`** (`string`, _required_): Natural-language styling instructions describing how the garment should be worn on the person (e.g. tucked in, layered, sleeves rolled up). - Examples: "A natural front-facing studio shot. The t-shirt is worn tucked in." - **`human_image_url`** (`string`, _required_): The URL of the person image that the garment will be applied onto. The output keeps this image's aspect ratio. Maximum 2 megapixels; recommended under 1 MP. - Examples: "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg" - **`garment_image_url`** (`string`, _required_): The URL of the garment reference image. Maximum 1 megapixel; recommended around 0.5 MP. Multiple garments must be merged into a single composite image before submission. - Examples: "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg" - **`num_inference_steps`** (`integer`, _optional_): The number of denoising steps to perform. Default value: `4` - Default: `4` - Range: `1` to `4` - **`seed`** (`integer`, _optional_): The same seed and the same input will output the same image every time. If not provided, a random seed is used. - **`sync_mode`** (`boolean`, _optional_): If `True`, the media will be returned as a data URI and the output data won't be available in the request history. - Default: `false` - **`output_format`** (`OutputFormatEnum`, _optional_): The format of the generated image. Default value: `"jpeg"` - Default: `"jpeg"` - Options: `"jpeg"`, `"png"` **Required Parameters Example**: ```json { "prompt": "A natural front-facing studio shot. The t-shirt is worn tucked in.", "human_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg", "garment_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg" } ``` **Full Example**: ```json { "prompt": "A natural front-facing studio shot. The t-shirt is worn tucked in.", "human_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg", "garment_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg", "num_inference_steps": 4, "output_format": "jpeg" } ``` ### Output Schema The API returns the following output format: - **`images`** (`list`, _required_): The generated image files info. - Array of registry__image__fast_sdxl__models__Image - **`timings`** (`Timings`, _required_) - **`seed`** (`integer`, _required_): Seed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed. - **`has_nsfw_concepts`** (`list`, _required_): Whether the generated images contain NSFW concepts. - Array of boolean - **`prompt`** (`string`, _required_): The prompt used for generating the image. **Example Response**: ```json { "images": [ { "url": "", "content_type": "image/jpeg" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/flux-pro/v1/vto \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A natural front-facing studio shot. The t-shirt is worn tucked in.", "human_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg", "garment_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg" }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/flux-pro/v1/vto", arguments={ "prompt": "A natural front-facing studio shot. The t-shirt is worn tucked in.", "human_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg", "garment_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/flux-pro/v1/vto", { input: { prompt: "A natural front-facing studio shot. The t-shirt is worn tucked in.", human_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg", garment_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/flux-pro/v1/vto) - [API Documentation](https://fal.ai/models/fal-ai/flux-pro/v1/vto/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/flux-pro/v1/vto) ### fal.ai Platform - [Platform Documentation](https://docs.fal.ai) - [Python Client](https://docs.fal.ai/clients/python) - [JavaScript Client](https://docs.fal.ai/clients/javascript)