Membuat dataset menggunakan dataset yang ada (SDK)

Prosedur berikut ini menunjukkan cara membuat set data dari set data yang ada dengan menggunakan CreateDatasetoperasi.

1. Jika Anda belum melakukannya, instal dan konfigurasikanAWS CLI danAWS SDK. Untuk informasi selengkapnya, lihat Langkah 4: Siapkan AWS CLI dan AWS SDK.

2. Gunakan contoh kode berikut untuk membuat dataset dengan menyalin dataset lain.

   AWS CLI

   Gunakan kode berikut untuk membuat set data. Ganti yang berikut:

   • project_arn- ARN proyek yang ingin Anda tambahkan set data.

   • dataset_type- dengan jenis dataset (TRAINatauTEST) yang ingin Anda buat dalam proyek.

   • dataset_arn- dengan ARN set data yang ingin Anda salin.

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

   Python

   Contoh berikut membuat set data menggunakan set data yang ada dan menampilkan ARN nya.

   Untuk menjalankan program, berikan argumen baris perintah berikut:

   • project_arn— ARN proyek yang ingin Anda gunakan.

   • dataset_type- jenis dataset proyek yang ingin Anda buat (trainatautest).

   • dataset_arn- ARN set data yang ingin Anda buat set data.

   # 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

   Contoh berikut membuat set data menggunakan set data yang ada dan menampilkan ARN nya.

   Untuk menjalankan program, berikan argumen baris perintah berikut:

   • project_arn— ARN proyek yang ingin Anda gunakan.

   • dataset_type- jenis dataset proyek yang ingin Anda buat (trainatautest).

   • dataset_arn- ARN set data yang ingin Anda buat set data.

   /*
      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);
           }
   
       }
   
   }