Generate Videos from Images using Veo

Create videos from images, using Veo , a generative AI model for video generation.

Explore further

For detailed documentation that includes this code sample, see the following:

Generate videos with Veo on Vertex AI from an image

Code sample

Java

Before trying this sample, follow the Java setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Java API reference documentation .

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  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-3.0-generate-preview" 
 ; 
  
 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 
 ; 
  
 } 
  
 } 
 }

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Python API reference documentation .