Generate Virtual Try-On Images

Virtual Try-On lets you generate images of people to virtually try-on clothing products. You provide an image of a person and an image of a clothing product, and then Virtual Try-On generates an image of the person wearing that product.

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Verify that billing is enabled for your Google Cloud project.

  4. Enable the Vertex AI API.

    Enable the API

  5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  6. Verify that billing is enabled for your Google Cloud project.

  7. Enable the Vertex AI API.

    Enable the API

    8.

  8. Set up authentication for your environment.

    Select the tab for how you plan to use the samples on this page:

    Console

    When you use the Google Cloud console to access Google Cloud services and APIs, you don't need to set up authentication.

    Python

    To use the Python samples on this page in a local development environment, install and initialize the gcloud CLI, and then set up Application Default Credentials with your user credentials.

    1. Install the Google Cloud CLI.

    2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

    3. If you're using a local shell, then create local authentication credentials for your user account: 

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

    For more information, see Set up ADC for a local development environment in the Google Cloud authentication documentation.

    REST

    To use the REST API samples on this page in a local development environment, you use the credentials you provide to the gcloud CLI.

      Install the Google Cloud CLI.

      If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

    For more information, see Authenticate for using REST in the Google Cloud authentication documentation.

Generate images

REST

Before using any of the request data, make the following replacements:

  • REGION: The region that your project is located in. For more information about supported regions, see Generative AI on Vertex AI locations.
  • PROJECT_ID: Your Google Cloud project ID.
  • BASE64_PERSON_IMAGE: The Base64-encoded image of the person image.
  • BASE64_PRODUCT_IMAGE: The Base64-encoded image of the product image.
  • IMAGE_COUNT: The number of images to generate. The accepted range of values is 1 to 4.
  • GCS_OUTPUT_PATH: The Cloud Storage path to store the virtual try-on output to.

HTTP method and URL: 

POST https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict

Request JSON body: 

{
  "instances": [
    {
      "personImage": {
        "image": {
          "bytesBase64Encoded": "BASE64_PERSON_IMAGE"
        }
      },
      "productImages": [
        {
          "image": {
            "bytesBase64Encoded": "BASE64_PRODUCT_IMAGE"
          }
        }
      ]
    }
  ],
  "parameters": {
    "sampleCount": IMAGE_COUNT,
    "storageUri": "GCS_OUTPUT_PATH"
  }
}

To send your request, choose one of these options:

curl

Save the request body in a file named request.json, and execute the following command: 

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict"

PowerShell

Save the request body in a file named request.json, and execute the following command: 

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://REGION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/publishers/google/models/virtual-try-on-preview-08-04:predict" | Select-Object -Expand Content
The request returns image objects. In this example, two image objects are returned, with two prediction objects as base64-encoded images. 
{
  "predictions": [
    {
      "mimeType": "image/png",
      "bytesBase64Encoded": "BASE64_IMG_BYTES"
    },
    {
      "bytesBase64Encoded": "BASE64_IMG_BYTES",
      "mimeType": "image/png"
    }
  ]
}