Virtual clothing try-on (2 images: person + garment)

fal-ai/flux-2-lora-gallery/virtual-tryon

Virtual clothing try-on (2 images: person + garment)

Inference

Commercial use

Schema

LLMs

Playground API

About

Virtual clothing try-on.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png", "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"],
    prompt: "A person wearing a stylish jacket, virtual try-on"
  },
  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);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png", "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"],
    prompt: "A person wearing a stylish jacket, virtual try-on"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_urls list<string>* required

The URLs of the images for virtual try-on. Provide person image and clothing image.

prompt string* required

The prompt to generate a virtual try-on image.

image_size ImageSize | Enum

The size of the generated image. If not provided, the size of the input image will be used.

Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}

guidance_scale float

The CFG (Classifier Free Guidance) scale. Controls how closely the model follows the prompt. Default value: 2.5

num_inference_steps integer

The number of inference steps to perform. Default value: 40

acceleration AccelerationEnum

Acceleration level for image generation. 'regular' balances speed and quality. Default value: "regular"

Possible enum values: none, regular

seed integer

Random seed for reproducibility. Same seed with same prompt will produce same result.

sync_mode boolean

If True, the media will be returned as a data URI and won't be saved in history.

enable_safety_checker boolean

Whether to enable the safety checker for the generated image. Disabling it requires account authorization; unauthorized requests are always checked. Default value: true

output_format OutputFormatEnum

The format of the output image Default value: "png"

Possible enum values: png, jpeg, webp

num_images integer

Number of images to generate Default value: 1

lora_scale float

The strength of the virtual try-on effect. Default value: 1

{
  "image_urls": [
    "https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png",
    "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"
  ],
  "prompt": "A person wearing a stylish jacket, virtual try-on",
  "guidance_scale": 2.5,
  "num_inference_steps": 40,
  "acceleration": "regular",
  "enable_safety_checker": true,
  "output_format": "png",
  "num_images": 1,
  "lora_scale": 1
}

Output#

images list<Image>* required

The generated virtual try-on images

seed integer* required

The seed used for generation

prompt string* required

The prompt used for generation

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/zebra/oFnSZ-nBbPgM-gXT0ApXy.png"
    }
  ],
  "prompt": ""
}

Other types#

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

Image#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

Related Models

Loading API documentation…

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Virtual clothing try-on.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png", "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"],
    prompt: "A person wearing a stylish jacket, virtual try-on"
  },
  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);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png", "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"],
    prompt: "A person wearing a stylish jacket, virtual try-on"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/flux-2-lora-gallery/virtual-tryon", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_urls list<string>* required

The URLs of the images for virtual try-on. Provide person image and clothing image.

prompt string* required

The prompt to generate a virtual try-on image.

image_size ImageSize | Enum

The size of the generated image. If not provided, the size of the input image will be used.

Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}

guidance_scale float

The CFG (Classifier Free Guidance) scale. Controls how closely the model follows the prompt. Default value: 2.5

num_inference_steps integer

The number of inference steps to perform. Default value: 40

acceleration AccelerationEnum

Acceleration level for image generation. 'regular' balances speed and quality. Default value: "regular"

Possible enum values: none, regular

seed integer

Random seed for reproducibility. Same seed with same prompt will produce same result.

sync_mode boolean

If True, the media will be returned as a data URI and won't be saved in history.

enable_safety_checker boolean

Whether to enable the safety checker for the generated image. Disabling it requires account authorization; unauthorized requests are always checked. Default value: true

output_format OutputFormatEnum

The format of the output image Default value: "png"

Possible enum values: png, jpeg, webp

num_images integer

Number of images to generate Default value: 1

lora_scale float

The strength of the virtual try-on effect. Default value: 1

{
  "image_urls": [
    "https://v3b.fal.media/files/b/koala/YlOtn9SjXGGH274eN1G5R.png",
    "https://v3b.fal.media/files/b/penguin/sji5EHUvmFYOCVZsvvId-.png"
  ],
  "prompt": "A person wearing a stylish jacket, virtual try-on",
  "guidance_scale": 2.5,
  "num_inference_steps": 40,
  "acceleration": "regular",
  "enable_safety_checker": true,
  "output_format": "png",
  "num_images": 1,
  "lora_scale": 1
}

Output#

images list<Image>* required

The generated virtual try-on images

seed integer* required

The seed used for generation

prompt string* required

The prompt used for generation

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/zebra/oFnSZ-nBbPgM-gXT0ApXy.png"
    }
  ],
  "prompt": ""
}

Other types#

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

Image#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

fal-ai/flux-2-lora-gallery/virtual-tryon

fal-ai/flux-2-lora-gallery/virtual-tryon

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

ImageSize#

Image#

Related Models

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

ImageSize#

Image#

Related Models