使用现有数据集创建数据集 (SDK)

以下过程说明了如何使用 CreateDataset 操作从现有数据集创建数据集。

1. 安装并配置 AWS CLI 和 AWS SDK（如果尚未如此）。有关更多信息，请参阅步骤 4：设置 AWS CLI 和 AWS 软件开发工具包。

2. 使用以下示例代码通过复制另一个数据集来创建数据集。

   AWS CLI

   使用以下代码创建数据集。替换以下内容：

   • project_arn：替换为要添加数据集的项目的 ARN。

   • dataset_type：替换为要在项目中创建的数据集的类型（TRAIN 或 TEST）。

   • dataset_arn：替换为要复制的数据集的 ARN。

   aws rekognition create-dataset --project-arn project_arn \
     --dataset-type dataset_type \
     --dataset-source '{ "DatasetArn" : "dataset_arn" }' \
     --profile custom-labels-access

   Python

   以下示例使用现有的数据集创建数据集并显示其 ARN。

   要运行该程序，请提供以下命令行参数：

   • project_arn：要使用的项目的 ARN。

   • dataset_type：要创建的项目数据集的类型（train 或 test）。

   • dataset_arn：要从其创建数据集的数据集的 ARN。

   # Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   # PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-custom-labels-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   import argparse
   import logging
   import time
   import json
   import boto3
   
   from botocore.exceptions import ClientError
   
   logger = logging.getLogger(__name__)
   
   
   def create_dataset_from_existing_dataset(rek_client, project_arn, dataset_type, dataset_arn):
       """
       Creates an Amazon Rekognition Custom Labels dataset using an existing dataset.
       :param rek_client: The Amazon Rekognition Custom Labels Boto3 client.
       :param project_arn: The ARN of the project in which you want to create a dataset.
       :param dataset_type: The type of the dataset that you want to create (train or test).
       :param dataset_arn: The ARN of the existing dataset that you want to use.
       """
   
       try:
           # Create the dataset
   
           dataset_type=dataset_type.upper()
   
           logger.info(
               "Creating %s dataset for project %s from dataset %s.",
                   dataset_type,project_arn, dataset_arn)
   
           dataset_source = json.loads(
               '{ "DatasetArn": "' + dataset_arn + '"}'
           )
   
           response = rek_client.create_dataset(
               ProjectArn=project_arn, DatasetType=dataset_type, DatasetSource=dataset_source
           )
   
           dataset_arn = response['DatasetArn']
   
           logger.info("New dataset ARN: %s", dataset_arn)
   
           finished = False
           while finished is False:
   
               dataset = rek_client.describe_dataset(DatasetArn=dataset_arn)
   
               status = dataset['DatasetDescription']['Status']
   
               if status == "CREATE_IN_PROGRESS":
   
                   logger.info(("Creating dataset: %s ", dataset_arn))
                   time.sleep(5)
                   continue
   
               if status == "CREATE_COMPLETE":
                   logger.info("Dataset created: %s", dataset_arn)
                   finished = True
                   continue
   
               if status == "CREATE_FAILED":
                   error_message = f"Dataset creation failed: {status} : {dataset_arn}"
                   logger.exception(error_message)
                   raise Exception(error_message)
   
               error_message = f"Failed. Unexpected state for dataset creation: {status} : {dataset_arn}"
               logger.exception(error_message)
               raise Exception(error_message)
   
           return dataset_arn
   
       except ClientError as err:
           logger.exception(
               "Couldn't create dataset: %s",err.response['Error']['Message'] )
           raise
   
   
   def add_arguments(parser):
       """
       Adds command line arguments to the parser.
       :param parser: The command line parser.
       """
   
       parser.add_argument(
           "project_arn", help="The ARN of the project in which you want to create the dataset."
       )
   
       parser.add_argument(
           "dataset_type", help="The type of the dataset that you want to create (train or test)."
       )
   
       parser.add_argument(
           "dataset_arn", help="The ARN of the dataset that you want to copy from."
       )
   
   
   def main():
   
       logging.basicConfig(level=logging.INFO,
                           format="%(levelname)s: %(message)s")
   
       try:
   
           # Get command line arguments.
           parser = argparse.ArgumentParser(usage=argparse.SUPPRESS)
           add_arguments(parser)
           args = parser.parse_args()
   
           print(
               f"Creating {args.dataset_type} dataset for project {args.project_arn}")
   
           # Create the dataset.
           session = boto3.Session(profile_name='custom-labels-access')
           rekognition_client = session.client("rekognition")
   
           dataset_arn = create_dataset_from_existing_dataset(rekognition_client,
                                        args.project_arn,
                                        args.dataset_type,
                                        args.dataset_arn)
   
           print(f"Finished creating dataset: {dataset_arn}")
   
       except ClientError as err:
           logger.exception("Problem creating dataset: %s", err)
           print(f"Problem creating dataset: {err}")
       except Exception as err:
           logger.exception("Problem creating dataset: %s", err)
           print(f"Problem creating dataset: {err}")
   
   
   if __name__ == "__main__":
       main()
   

   Java V2

   以下示例使用现有的数据集创建数据集并显示其 ARN。

   要运行该程序，请提供以下命令行参数：

   • project_arn：要使用的项目的 ARN。

   • dataset_type：要创建的项目数据集的类型（train 或 test）。

   • dataset_arn：要从其创建数据集的数据集的 ARN。

   /*
      Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
      SPDX-License-Identifier: Apache-2.0
   */
   
   package com.example.rekognition;
   
   import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.CreateDatasetRequest;
   import software.amazon.awssdk.services.rekognition.model.CreateDatasetResponse;
   import software.amazon.awssdk.services.rekognition.model.DatasetDescription;
   import software.amazon.awssdk.services.rekognition.model.DatasetSource;
   import software.amazon.awssdk.services.rekognition.model.DatasetStatus;
   import software.amazon.awssdk.services.rekognition.model.DatasetType;
   import software.amazon.awssdk.services.rekognition.model.DescribeDatasetRequest;
   import software.amazon.awssdk.services.rekognition.model.DescribeDatasetResponse;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   
   import java.util.logging.Level;
   import java.util.logging.Logger;
   
   public class CreateDatasetExisting {
   
       public static final Logger logger = Logger.getLogger(CreateDatasetExisting.class.getName());
   
       public static String createMyDataset(RekognitionClient rekClient, String projectArn, String datasetType,
               String existingDatasetArn) throws Exception, RekognitionException {
   
           try {
   
               logger.log(Level.INFO, "Creating {0} dataset for project : {1} from dataset {2} ",
                       new Object[] { datasetType.toString(), projectArn, existingDatasetArn });
   
               DatasetType requestDatasetType = null;
   
               switch (datasetType) {
               case "train":
                   requestDatasetType = DatasetType.TRAIN;
                   break;
               case "test":
                   requestDatasetType = DatasetType.TEST;
                   break;
               default:
                   logger.log(Level.SEVERE, "Unrecognized dataset type: {0}", datasetType);
                   throw new Exception("Unrecognized dataset type: " + datasetType);
   
               }
   
               DatasetSource datasetSource = DatasetSource.builder().datasetArn(existingDatasetArn).build();
   
               CreateDatasetRequest createDatasetRequest = CreateDatasetRequest.builder().projectArn(projectArn)
                       .datasetType(requestDatasetType).datasetSource(datasetSource).build();
   
               CreateDatasetResponse response = rekClient.createDataset(createDatasetRequest);
   
               boolean created = false;
               
               //Wait until create finishes
   
               do {
   
                   DescribeDatasetRequest describeDatasetRequest = DescribeDatasetRequest.builder()
                           .datasetArn(response.datasetArn()).build();
                   DescribeDatasetResponse describeDatasetResponse = rekClient.describeDataset(describeDatasetRequest);
   
                   DatasetDescription datasetDescription = describeDatasetResponse.datasetDescription();
   
                   DatasetStatus status = datasetDescription.status();
   
                   logger.log(Level.INFO, "Creating dataset ARN: {0} ", response.datasetArn());
   
                   switch (status) {
   
                   case CREATE_COMPLETE:
                       logger.log(Level.INFO, "Dataset created");
                       created = true;
                       break;
   
                   case CREATE_IN_PROGRESS:
                       Thread.sleep(5000);
                       break;
   
                   case CREATE_FAILED:
                       String error = "Dataset creation failed: " + datasetDescription.statusAsString() + " "
                               + datasetDescription.statusMessage() + " " + response.datasetArn();
                       logger.log(Level.SEVERE, error);
                       throw new Exception(error);
   
                   default:
                       String unexpectedError = "Unexpected creation state: " + datasetDescription.statusAsString() + " "
                               + datasetDescription.statusMessage() + " " + response.datasetArn();
                       logger.log(Level.SEVERE, unexpectedError);
                       throw new Exception(unexpectedError);
                   }
   
               } while (created == false);
   
               return response.datasetArn();
   
           } catch (RekognitionException e) {
               logger.log(Level.SEVERE, "Could not create dataset: {0}", e.getMessage());
               throw e;
           }
   
       }
   
       public static void main(String[] args) {
   
           String datasetType = null;
           String datasetArn = null;
           String projectArn = null;
           String datasetSourceArn = null;
   
           final String USAGE = "\n" + "Usage: " + "<project_arn> <dataset_type> <dataset_arn>\n\n" + "Where:\n"
                   + "   project_arn - the ARN of the project that you want to add copy the datast to.\n\n"
                   + "   dataset_type - the type of the dataset that you want to create (train or test).\n\n"
                   + "   dataset_arn - the ARN of the dataset that you want to copy from.\n\n";
   
           if (args.length != 3) {
               System.out.println(USAGE);
               System.exit(1);
           }
   
           projectArn = args[0];
           datasetType = args[1];
           datasetSourceArn = args[2];
   
           try {
   
               // Get the Rekognition client
               RekognitionClient rekClient = RekognitionClient.builder()
                   .credentialsProvider(ProfileCredentialsProvider.create("custom-labels-access"))
                   .region(Region.US_WEST_2)
                   .build();
   
               // Create the dataset
               datasetArn = createMyDataset(rekClient, projectArn, datasetType, datasetSourceArn);
   
               System.out.println(String.format("Created dataset: %s", datasetArn));
   
               rekClient.close();
   
           } catch (RekognitionException rekError) {
               logger.log(Level.SEVERE, "Rekognition client error: {0}", rekError.getMessage());
               System.exit(1);
           } catch (Exception rekError) {
               logger.log(Level.SEVERE, "Error: {0}", rekError.getMessage());
               System.exit(1);
           }
   
       }
   
   }