Set output resolution

Console

1. In the Google Cloud console, go to the Vertex AI > Media Studiopage.

   Go to Media Studio

2. Click Imagen. The Imagen Media Studio image generation page is displayed.

3. In the Settingspanel, adjust the following options:

   • Model: Choose a model from the available options.

     For more information about available models, see Imagen models .

   • Output resolution: Choose an output resolution from the available options.

4. In the Write your promptbox, enter your text prompt that describes the images to generate. For example, "small boat on water in the morning watercolor illustration" .

5. Click send Generate.

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 .
• TEXT_PROMPT : The text prompt to use to generate images.
• PROJECT_ID : Your Google Cloud project ID.
• MODEL_VERSION : The Imagen model version to use. The following are accepted values when using sampleImageSize :
  • imagen-4.0-generate-001
  • imagen-4.0-ultra-generate-001
• IMAGE_RESOLUTION : The output image resolution. The following are accepted:
  • "1K"
  • "2K"

  The default setting is "1K" .

• IMAGE_COUNT : The number of images to generate. The accepted range of values is 1 to 4 .

HTTP method and URL:

POST https:// REGION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ REGION 
/publishers/google/models/ MODEL_VERSION 
:predict

Request JSON body:

{
  "instances": [
    {
      "prompt": " TEXT_PROMPT 
"
    }
  ],
  "parameters": {
    "sampleImageSize": " IMAGE_RESOLUTION 
",
    "sampleCount": IMAGE_COUNT 
}
}

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:// REGION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ REGION 
/publishers/google/models/ MODEL_VERSION 
: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:// REGION 
-aiplatform.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ REGION 
/publishers/google/models/ MODEL_VERSION 
:predict" | Select-Object -Expand Content

{
  "predictions": [
    {
      "mimeType": "image/png",
      "bytesBase64Encoded": " BASE64_IMG_BYTES 
"
    },
    {
      "bytesBase64Encoded": " BASE64_IMG_BYTES 
",
      "mimeType": "image/png"
    }
  ]
}