# 멀티샷 비디오 생성 코드 예제 다음 예제에서는 다양한 멀티샷(6초 이상) 비디오 생성 태스크의 샘플 코드를 제공합니다. ------ #### [ Automated video generation ] 이 예제에서는 비디오의 모든 샷이 단일 프롬프트에서 생성되며 입력 이미지가 제공되지 않습니다. ``` import json import os import boto3 from dotenv import load_dotenv # Create the Bedrock Runtime client. bedrock_runtime = boto3.client(service_name="bedrock-runtime", region_name="us-east-1") # Configure Nova Reel model inputs. model_input = { "taskType": "MULTI_SHOT_AUTOMATED", "multiShotAutomatedParams": { "text": "Cinematic documentary showcasing the stunning beauty of the natural world. Drone footage flying over fantastical and varied natural wonders." }, "videoGenerationConfig": { "seed": 1234, "durationSeconds": 18, # Must be a multiple of 6 in range [12, 120] "fps": 24, # Must be 24 "dimension": "1280x720", # Must be "1280x720" }, } try: # Start the asynchronous video generation job. invocation = bedrock_runtime.start_async_invoke( modelId="amazon.nova-reel-v1:1", modelInput=model_input, outputDataConfig={"s3OutputDataConfig": {"s3Uri": "s3://your-s3-bucket"}}, ) # Print the response JSON. print(json.dumps(invocation, indent=2, default=str)) except Exception as err: print("Exception:") if hasattr(err, "response"): # Pretty print the response JSON. print(json.dumps(err.response, indent=2, default=str)) else: print(err) ``` ------ #### [ Manual video generation - Amazon S3 input image ] 이 예제에서는 2개의 샷 비디오가 생성됩니다. 각 샷은 Amazon S3 로케이션에 제공되는 별도의 프롬프트와 입력 이미지로 생성됩니다. ``` import json import os import boto3 from dotenv import load_dotenv # === Helper Function === def image_to_base64(image_path: str): """ Convert an image file to a base64 encoded string. """ import base64 with open(image_path, "rb") as image_file: encoded_string = base64.b64encode(image_file.read()) return encoded_string.decode("utf-8") # === Main Code === # Create the Bedrock Runtime client. bedrock_runtime = boto3.client(service_name="bedrock-runtime", region_name="us-east-1") # Configure Nova Reel model inputs. This example includes three shots, two of # which include images to use as starting frames. These images are stored in S3. model_input = { "taskType": "MULTI_SHOT_MANUAL", "multiShotManualParams": { "shots": [ {"text": "aerial view of a city with tall glass and metal skyscrapers"}, { "text": "closeup of a vehicle wheel in motion as the pavement speeds by with motion blur", "image": { "format": "png", # Must be "png" or "jpeg" "source": { "s3Location": { "uri": "s3://your-s3-bucket/images/SUV-wheel-closeup.png" } }, }, }, { "text": "tracking shot, the vehicle drives through the city, trees and buildings line the street", "image": { "format": "png", # Must be "png" or "jpeg" "source": { "s3Location": { "uri": "s3://your-s3-bucket/images/SUV-downtown-back.png" } }, }, }, ] }, "videoGenerationConfig": { "seed": 1234, "fps": 24, # Must be 24 "dimension": "1280x720", # Must be "1280x720" }, } try: # Start the asynchronous video generation job. invocation = bedrock_runtime.start_async_invoke( modelId="amazon.nova-reel-v1:1", modelInput=model_input, outputDataConfig={"s3OutputDataConfig": {"s3Uri": "s3://your-s3-bucket"}}, ) # Print the response JSON. print(json.dumps(invocation, indent=2, default=str)) except Exception as err: print("Exception:") if hasattr(err, "response"): # Pretty print the response JSON. print(json.dumps(err.response, indent=2, default=str)) else: print(err) ``` ------ #### [ Manual video generation - base64 input image ] 이 예제에서는 3개의 샷 비디오가 생성됩니다. 첫 번째 샷은 프롬프트만으로 생성되며, 다음 두 샷은 각각 새 프롬프트 및 입력 이미지로 생성됩니다. ``` import json import os import boto3 from dotenv import load_dotenv # === Helper Function === def image_to_base64(image_path: str): """ Convert an image file to a base64 encoded string. """ import base64 with open(image_path, "rb") as image_file: encoded_string = base64.b64encode(image_file.read()) return encoded_string.decode("utf-8") # === Main Code === # Create the Bedrock Runtime client. bedrock_runtime = boto3.client(service_name="bedrock-runtime", region_name="us-east-1") # Configure Nova Reel model inputs. This example includes three shots, two of # which include images to use as starting frames. model_input = { "taskType": "MULTI_SHOT_MANUAL", "multiShotManualParams": { "shots": [ { "text": "Drone footage of a Pacific Northwest forest with a meandering stream seen from a high altitude, top-down view" }, { "text": "camera arcs slowly around two SUV vehicles in a forest setting with a stream in the background", "image": { "format": "png", # Must be "png" or "jpeg" "source": {"bytes": image_to_base64("images/SUV-roadside.png")}, }, }, { "text": "tracking shot, a SUV vehicle drives toward the camera through a forest roadway, the SUV's ring-shaped headlights glow white", "image": { "format": "png", # Must be "png" or "jpeg" "source": {"bytes": image_to_base64("images/SUV-forest-front.png")}, }, }, ] }, "videoGenerationConfig": { "seed": 1234, "fps": 24, # Must be 24 "dimension": "1280x720", # Must be "1280x720" }, } try: # Start the asynchronous video generation job. invocation = bedrock_runtime.start_async_invoke( modelId="amazon.nova-reel-v1:1", modelInput=model_input, outputDataConfig={"s3OutputDataConfig": {"s3Uri": "s3://your-s3-bucket"}}, ) # Print the response JSON. print(json.dumps(invocation, indent=2, default=str)) except Exception as err: print("Exception:") if hasattr(err, "response"): # Pretty print the response JSON. print(json.dumps(err.response, indent=2, default=str)) else: print(err) ``` ------