Generate videos with Veo on Gemini Enterprise Agent Platform from an image

You can use Veo on Gemini Enterprise Agent Platform to generate new videos using an existing image as the first frame. Image first frame to video available through Gemini Enterprise Agent Platform Media Studio or using the Gemini Enterprise Agent Platform video generation API .

The following models support generating videos from an image:

For more information about writing effective text prompts for video generation, see the Veo prompt guide .

Try Veo in a Colab

Before you begin

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.

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

Roles required to select or create a project

Select a project : Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
Create a project : To create a project, you need the Project Creator role ( roles/resourcemanager.projectCreator ), which contains the resourcemanager.projects.create permission. Learn how to grant roles .

Go to project selector

Enable the Agent Platform API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role ( roles/serviceusage.serviceUsageAdmin ), which contains the serviceusage.services.enable permission. Learn how to grant roles .

Enable the API

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

Roles required to select or create a project

Select a project : Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
Create a project : To create a project, you need the Project Creator role ( roles/resourcemanager.projectCreator ), which contains the resourcemanager.projects.create permission. Learn how to grant roles .

Go to project selector

Enable the Agent Platform API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role ( roles/serviceusage.serviceUsageAdmin ), which contains the serviceusage.services.enable permission. Learn how to grant roles .

Enable the API

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

Generate videos from an image

Sample input

Sample output

Input image ¹
Text prompt: the elephant moves around naturally

¹ Image generated using Imagen on Gemini Enterprise Agent Platform from the prompt: A Crochet elephant in intricate patterns walking on the savanna

You can generate novel videos using only an image as an input, or and image and descriptive text as the inputs. The following samples show you basic instructions to generate videos from image and text.

Console

In the Google Cloud console, go to the Agent Platform > Media Studiopage.

Media Studio
Click Video.
In the Taskmenu, select Image-to-video.
From the Modelmenu, select a model from the displayed options.
In the Promptbox, enter a text prompt that describes the videos to generate.
In the Input imagessection, click Startto upload an image for the first frame.
Optional: click Endto upload an image for the last frame.
Optional: Adjust the following Parameters:
- Aspect ratio: choose either 16:9or 9:16.
- Number of results: adjust the slider or enter a value between 1and 4.
- Video length: select a video length from the menu.
- Output directory: click Browseto create or select a Cloud Storage bucket to store the generated files.
Click Run.

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values # with appropriate values for your project. export GOOGLE_CLOUD_PROJECT = GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION = global export GOOGLE_GENAI_USE_VERTEXAI = True

import time from google import genai from google.genai.types import GenerateVideosConfig , Image client = genai . Client () # TODO(developer): Update and un-comment below line # output_gcs_uri = "gs://your-bucket/your-prefix" operation = client . models . generate_videos ( model = "veo-3.1-generate-001" , prompt = "Extreme close-up of a cluster of vibrant wildflowers swaying gently in a sun-drenched meadow." , image = Image ( gcs_uri = "gs://cloud-samples-data/generative-ai/image/flowers.png" , mime_type = "image/png" , ), config = GenerateVideosConfig ( aspect_ratio = "16:9" , output_gcs_uri = output_gcs_uri , ), ) while not operation . done : time . sleep ( 15 ) operation = client . operations . get ( operation ) print ( operation ) if operation . response : print ( operation . result . generated_videos [ 0 ] . video . uri ) # Example response: # gs://your-bucket/your-prefix

import ( "context" "fmt" "io" "time" "google.golang.org/genai" ) // generateVideoFromImage shows how to gen video from img. func generateVideoFromImage ( w io . Writer , outputGCSURI string ) error { // outputGCSURI = "gs://your-bucket/your-prefix" ctx := context . Background () client , err := genai . NewClient ( ctx , & genai . ClientConfig { HTTPOptions : genai . HTTPOptions { APIVersion : "v1" }, }) if err != nil { return fmt . Errorf ( "failed to create genai client: %w" , err ) } image := & genai . Image { GCSURI : "gs://cloud-samples-data/generative-ai/image/flowers.png" , MIMEType : "image/png" , } config := & genai . GenerateVideosConfig { AspectRatio : "16:9" , OutputGCSURI : outputGCSURI , } modelName := "veo-3.0-generate-preview" prompt := "Extreme close-up of a cluster of vibrant wildflowers swaying gently in a sun-drenched meadow." operation , err := client . Models . GenerateVideos ( ctx , modelName , prompt , image , config ) if err != nil { return fmt . Errorf ( "failed to start video generation: %w" , err ) } // Polling until the operation is done for ! operation . Done { time . Sleep ( 15 * time . Second ) operation , err = client . Operations . GetVideosOperation ( ctx , operation , nil ) if err != nil { return fmt . Errorf ( "failed to get operation status: %w" , err ) } } if operation . Response != nil && len ( operation . Response . GeneratedVideos ) > 0 { videoURI := operation . Response . GeneratedVideos [ 0 ] . Video . URI fmt . Fprintln ( w , videoURI ) return nil } // Example response : // gs : // your - bucket / your - prefix / videoURI return fmt . Errorf ( "video generation failed or returned no results" ) }

const { GoogleGenAI } = require ( '@google/genai' ); const GOOGLE_CLOUD_PROJECT = process . env . GOOGLE_CLOUD_PROJECT ; const GOOGLE_CLOUD_LOCATION = process . env . GOOGLE_CLOUD_LOCATION || 'global' ; async function generateVideo ( outputGcsUri , projectId = GOOGLE_CLOUD_PROJECT , location = GOOGLE_CLOUD_LOCATION ) { const client = new GoogleGenAI ({ vertexai : true , project : projectId , location : location , }); let operation = await client . models . generateVideos ({ model : 'veo-3.1-fast-generate-001' , prompt : 'Extreme close-up of a cluster of vibrant wildflowers swaying gently in a sun-drenched meadow' , image : { gcsUri : 'gs://cloud-samples-data/generative-ai/image/flowers.png' , mimeType : 'image/png' , }, config : { aspectRatio : '16:9' , outputGcsUri : outputGcsUri , }, }); while ( ! operation . done ) { await new Promise ( resolve = > setTimeout ( resolve , 15000 )); operation = await client . operations . get ({ operation : operation }); console . log ( operation ); } if ( operation . response ) { console . log ( operation . response . generatedVideos [ 0 ] . video . uri ); } return operation ; }

import com.google.genai.Client ; import com.google.genai.types.GenerateVideosConfig ; import com.google.genai.types.GenerateVideosOperation ; import com.google.genai.types.GenerateVideosResponse ; import com.google.genai.types.GeneratedVideo ; import com.google.genai.types.GetOperationConfig ; import com.google.genai.types.Image ; import com.google.genai.types.Video ; import java.util.concurrent.TimeUnit ; public class VideoGenWithImg { public static void main ( String [] args ) throws InterruptedException { // TODO ( developer ): Replace these variables before running the sample . String modelId = "veo-3.1-generate-001" ; String outputGcsUri = "gs://your-bucket/your-prefix" ; generateContent ( modelId , outputGcsUri ); } // Generates a video with an image and a text prompt . public static String generateContent ( String modelId , String outputGcsUri ) throws InterruptedException { // Client Initialization . Once created , it can be reused for multiple requests . try ( Client client = Client . builder () . location ( "global" ) . vertexAI ( true ) . build ()) { GenerateVideosOperation operation = client . models . generateVideos ( modelId , "Extreme close-up of a cluster of vibrant wildflowers" + " swaying gently in a sun-drenched meadow." , Image . builder () . gcsUri ( "gs://cloud-samples-data/generative-ai/image/flowers.png" ) . mimeType ( "image/png" ) . build (), GenerateVideosConfig . builder () . aspectRatio ( "16:9" ) . outputGcsUri ( outputGcsUri ) . build ()); while ( ! operation . done () . orElse ( false )) { TimeUnit . SECONDS . sleep ( 15 ); operation = client . operations . getVideosOperation ( operation , GetOperationConfig . builder () . build ()); } String generatedVideoUri = operation . response () . flatMap ( GenerateVideosResponse :: generatedVideos ) . flatMap ( videos - > videos . stream () . findFirst ()) . flatMap ( GeneratedVideo :: video ) . flatMap ( Video :: uri ) . orElseThrow ( () - > new IllegalStateException ( "Could not get the URI from the generated video" )); System . out . println ( "Generated video URI: " + generatedVideoUri ); // Example response : // Generated video URI : gs : // your - bucket / your - prefix / generated - video - 123. mp4 return generatedVideoUri ; } } }

"parameters": { "aspectRatio": " ASPECT_RATIO ", "negativePrompt": " NEGATIVE_PROMPT ", "personGeneration": " PERSON_SAFETY_SETTING ", // "resolution": RESOLUTION , // Veo 3 models only "sampleCount": RESPONSE_COUNT , "seed": SEED_NUMBER }

{ "instances": [ { "prompt": " TEXT_PROMPT ", "image": { "bytesBase64Encoded": " INPUT_IMAGE ", "mimeType": " MIME_TYPE " } } ], "parameters": { "storageUri": " OUTPUT_STORAGE_URI ", "sampleCount": RESPONSE_COUNT "resizeMode": " RESIZE_MODE " } }

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://us-central1-aiplatform.googleapis.com/v1/projects/ PROJECT_ID /locations/us-central1/publishers/google/models/ MODEL_ID :predictLongRunning"

$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://us-central1-aiplatform.googleapis.com/v1/projects/ PROJECT_ID /locations/us-central1/publishers/google/models/ MODEL_ID :predictLongRunning" | Select-Object -Expand Content

$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://us-central1-aiplatform.googleapis.com/v1/projects/ PROJECT_ID /locations/us-central1/publishers/google/models/ MODEL_ID :fetchPredictOperation" | Select-Object -Expand Content

{ "name": "projects/ PROJECT_ID /locations/us-central1/publishers/google/models/ MODEL_ID /operations/ OPERATION_ID ", "done": true,"response": { "raiMediaFilteredCount": 0, "@type": "type.googleapis.com/cloud.ai.large_models.vision.GenerateVideoResponse", "videos": [ { "gcsUri":"gs://BUCKET_NAME/TIMESTAMPED_FOLDER/sample_0.mp4", "mimeType": "video/mp4" } ] } }

Generate videos with Veo on Gemini Enterprise Agent Platform from an image

Before you begin

Console

REST

Generate videos from an image

Console

Python

Install

Go

Node.js

Install

Java

REST

curl

PowerShell

curl

PowerShell

Response

What's next

Generate videos with Veo on Gemini Enterprise Agent Platform from an image Stay organized with collections Save and categorize content based on your preferences.

Before you begin

Console

REST

Generate videos from an image

Console

Python

Install

Go

Node.js

Install

Java

REST

curl

PowerShell

curl

PowerShell

Response

What's next

Generate videos with Veo on Gemini Enterprise Agent Platform from an image