Upscale a generated, edited, or existing image

Console

1. Follow the generate image with text instructions to generate images.

2. Select the image to upscale.

3. Click download Upscale/export.

4. Select Upscale images.

5. Choose a value from the Scale factor( 2x or 4x ).

6. Click download Exportto save the upscaled image.

REST

For more information about imagegeneration model requests, see the imagegeneration model API reference .

Upscaling mode is an optional field in the parameters object of a JSON request body. When you upscale an image using the API, specify "mode": "upscale" and upscaleConfig .

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

• LOCATION : Your project's region. For example, us-central1 , europe-west2 , or asia-northeast3 . For a list of available regions, see Generative AI on Vertex AI locations .
• PROJECT_ID : Your Google Cloud project ID .
• B64_BASE_IMAGE : The base image to edit or upscale. The image must be specified as a base64-encoded byte string. Size limit: 10 MB.
• IMAGE_SOURCE : The Cloud Storage location of the image you want to edit or upscale. For example: gs://output-bucket/source-photos/photo.png .
• UPSCALE_FACTOR : Optional. The factor to which the image will be upscaled. If not specified, the upscale factor will be determined from the longer side of the input image and sampleImageSize . Available values: x2 or x4 .

HTTP method and URL:

POST https:// LOCATION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ LOCATION 
/publishers/google/models/imagegeneration@002:predict

Request JSON body:

{
  "instances": [
    {
      "prompt": "",
      "image": {
        // use one of the following to specify the image to upscale
        "bytesBase64Encoded": " B64_BASE_IMAGE 
"
        "gcsUri": " IMAGE_SOURCE 
"
        // end of base image input options
      },
    }
  ],
  "parameters": {
    "sampleCount": 1,
    "mode": " upscale 
",
    "upscaleConfig": {
      "upscaleFactor": " UPSCALE_FACTOR 
"
    }
  }
}

To send your request, choose one of these options:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https:// LOCATION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ LOCATION 
/publishers/google/models/imagegeneration@002:predict"

$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:// LOCATION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ LOCATION 
/publishers/google/models/imagegeneration@002:predict" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "predictions": [
    {
      "mimeType": "image/png",
      "bytesBase64Encoded": " iVBOR..[base64-encoded-upscaled-image]...YII= 
"
    }
  ]
}