Beschreibung eines Modells (SDK)

Sie können dieDescribeProjectVersions API verwenden, um Informationen über eine Version eines Modells abzurufen. Wenn Sie nichts angebenVersionName, werden Beschreibungen für alle Modellversionen im ProjektDescribeProjectVersions zurückgegeben.

Um ein Modell zu beschreiben (SDK)

1. Falls noch nicht getan haben, installieren und konfigurieren Sie dieAWS CLIAWS SDKs. Weitere Informationen finden Sie unter Schritt 4: Richten Sie die AWS CLI und SDKs ein AWS.

2. Verwenden Sie den folgenden Beispielcode, um eine Version eines Modells zu beschreiben.

   AWS CLI

   Ändern Sie den Wert vonproject-arn in den ARN des Projekts, das Sie beschreiben möchten. Ändern Sieversion-name den Wert von auf die Sie beschreiben möchten.

   aws rekognition describe-project-versions --project-arn project_arn \
     --version-names version_name \
     --profile custom-labels-access

   Python

   Verwenden Sie auch Sie folgenden Code Sie folgenden Code. Geben Sie die folgenden Befehlszeilenparameter an:

   • project_arn — der ARN des Modells, das Sie beschreiben möchten.

   • model_version — die Version des Modells, das Sie beschreiben möchten.

   Beispiel: python describe_model.py project_arn model_version

   # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
   # SPDX-License-Identifier: Apache-2.0
   
   """
   Purpose
   Shows how to describe an Amazon Rekognition Custom Labels model.
   """
   import argparse
   import logging
   import boto3
   
   from botocore.exceptions import ClientError
   
   logger = logging.getLogger(__name__)
   
   
   def describe_model(rek_client, project_arn, version_name):
       """
       Describes an Amazon Rekognition Custom Labels model.
       :param rek_client: The Amazon Rekognition Custom Labels Boto3 client.
       :param project_arn: The ARN of the prject that contains the model.
       :param version_name: The version name of the model that you want to describe.
       """
   
       try:
           # Describe the model
           logger.info("Describing model: %s for project %s",
                       version_name, project_arn)
   
           describe_response = rek_client.describe_project_versions(ProjectArn=project_arn,
                                                                    VersionNames=[version_name])
           for model in describe_response['ProjectVersionDescriptions']:
               print(f"Created: {str(model['CreationTimestamp'])} ")
               print(f"ARN: {str(model['ProjectVersionArn'])} ")
               if 'BillableTrainingTimeInSeconds' in model:
                   print(
                       f"Billing training time (minutes): {str(model['BillableTrainingTimeInSeconds']/60)} ")
               print("Evaluation results: ")
               if 'EvaluationResult' in model:
                   evaluation_results = model['EvaluationResult']
                   print(f"\tF1 score: {str(evaluation_results['F1Score'])}")
                   print(
                       f"\tSummary location: s3://{evaluation_results['Summary']['S3Object']['Bucket']}/{evaluation_results['Summary']['S3Object']['Name']}")
   
               if 'ManifestSummary' in model:
                   print(
                       f"Manifest summary location: s3://{model['ManifestSummary']['S3Object']['Bucket']}/{model['ManifestSummary']['S3Object']['Name']}")
               if 'OutputConfig' in model:
                   print(
                       f"Training output location: s3://{model['OutputConfig']['S3Bucket']}/{model['OutputConfig']['S3KeyPrefix']}")
               if 'MinInferenceUnits' in model:
                   print(
                       f"Minimum inference units: {str(model['MinInferenceUnits'])}")
               if 'MaxInferenceUnits' in model:
                   print(
                       f"Maximum Inference units: {str(model['MaxInferenceUnits'])}")
   
               print("Status: " + model['Status'])
               print("Message: " + model['StatusMessage'])
   
       except ClientError as err:
           logger.exception(
               "Couldn't describe model: %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 the model resides."
       )
       parser.add_argument(
           "version_name", help="The version of the model that you want to describe."
       )
   
   
   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"Describing model: {args.version_name} for project {args.project_arn}.")
   
           # Describe the model.
           session = boto3.Session(profile_name='custom-labels-access')
           rekognition_client = session.client("rekognition")
   
           describe_model(rekognition_client, args.project_arn,
                          args.version_name)
   
           print(
               f"Finished describing model: {args.version_name} for project {args.project_arn}.")
   
       except ClientError as err:
           error_message = f"Problem describing model: {err}"
           logger.exception(error_message)
           print(error_message)
       except Exception as err:
           error_message = f"Problem describing model: {err}"
           logger.exception(error_message)
           print(error_message)
   
   
   if __name__ == "__main__":
       main()
   

   Java V2

   Verwenden Sie auch Sie folgenden Code Sie folgenden Code. Geben Sie die folgenden Befehlszeilenparameter an:

   • project_arn — der ARN des Modells, das Sie beschreiben möchten.

   • model_version — die Version des Modells, das Sie beschreiben möchten.

   /*
      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.DescribeProjectVersionsRequest;
   import software.amazon.awssdk.services.rekognition.model.DescribeProjectVersionsResponse;
   import software.amazon.awssdk.services.rekognition.model.EvaluationResult;
   import software.amazon.awssdk.services.rekognition.model.GroundTruthManifest;
   import software.amazon.awssdk.services.rekognition.model.OutputConfig;
   import software.amazon.awssdk.services.rekognition.model.ProjectVersionDescription;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   
   import java.util.logging.Level;
   import java.util.logging.Logger;
   
   public class DescribeModel {
   
       public static final Logger logger = Logger.getLogger(DescribeModel.class.getName());
   
       public static void describeMyModel(RekognitionClient rekClient, String projectArn, String versionName) {
   
           try {
   
               // If a single version name is supplied, build request argument
   
               DescribeProjectVersionsRequest describeProjectVersionsRequest = null;
   
               if (versionName == null) {
                   describeProjectVersionsRequest = DescribeProjectVersionsRequest.builder().projectArn(projectArn)
                           .build();
               } else {
                   describeProjectVersionsRequest = DescribeProjectVersionsRequest.builder().projectArn(projectArn)
                           .versionNames(versionName).build();
               }
   
               DescribeProjectVersionsResponse describeProjectVersionsResponse = rekClient
                       .describeProjectVersions(describeProjectVersionsRequest);
   
               for (ProjectVersionDescription projectVersionDescription : describeProjectVersionsResponse
                       .projectVersionDescriptions()) {
   
                   System.out.println("ARN: " + projectVersionDescription.projectVersionArn());
                   System.out.println("Status: " + projectVersionDescription.statusAsString());
                   System.out.println("Message: " + projectVersionDescription.statusMessage());
   
                   if (projectVersionDescription.billableTrainingTimeInSeconds() != null) {
                       System.out.println(
                               "Billable minutes: " + (projectVersionDescription.billableTrainingTimeInSeconds() / 60));
                   }
   
                   if (projectVersionDescription.evaluationResult() != null) {
                       EvaluationResult evaluationResult = projectVersionDescription.evaluationResult();
   
                       System.out.println("F1 Score: " + evaluationResult.f1Score());
                       System.out.println("Summary location: s3://" + evaluationResult.summary().s3Object().bucket() + "/"
                               + evaluationResult.summary().s3Object().name());
                   }
   
                   if (projectVersionDescription.manifestSummary() != null) {
                       GroundTruthManifest manifestSummary = projectVersionDescription.manifestSummary();
                       System.out.println("Manifest summary location: s3://" + manifestSummary.s3Object().bucket() + "/"
                               + manifestSummary.s3Object().name());
   
                   }
   
                   if (projectVersionDescription.outputConfig() != null) {
                       OutputConfig outputConfig = projectVersionDescription.outputConfig();
                       System.out.println(
                               "Training output: s3://" + outputConfig.s3Bucket() + "/" + outputConfig.s3KeyPrefix());
                   }
   
                   if (projectVersionDescription.minInferenceUnits() != null) {
                       System.out.println("Min inference units: " + projectVersionDescription.minInferenceUnits());
                   }
   
                   System.out.println();
   
               }
   
           } catch (RekognitionException rekError) {
               logger.log(Level.SEVERE, "Rekognition client error: {0}", rekError.getMessage());
               throw rekError;
           }
   
       }
   
       public static void main(String args[]) {
   
           String projectArn = null;
           String versionName = null;
   
           final String USAGE = "\n" + "Usage: " + "<project_arn> <version_name>\n\n" + "Where:\n"
                   + "   project_arn - The ARN of the project that contains the models you want to describe.\n\n"
                   + "   version_name - (optional) The version name of the model that you want to describe. \n\n"
                   + "                  If you don't specify a value, all model versions are described.\n\n";
   
           if (args.length > 2 || args.length == 0) {
               System.out.println(USAGE);
               System.exit(1);
           }
   
           projectArn = args[0];
   
           if (args.length == 2) {
               versionName = args[1];
           }
   
           try {
   
               // Get the Rekognition client.
               RekognitionClient rekClient = RekognitionClient.builder()
               .credentialsProvider(ProfileCredentialsProvider.create("custom-labels-access"))
               .region(Region.US_WEST_2)
               .build();
   
                // Describe the model
               describeMyModel(rekClient, projectArn, versionName);
   
               rekClient.close();
   
           } catch (RekognitionException rekError) {
               logger.log(Level.SEVERE, "Rekognition client error: {0}", rekError.getMessage());
               System.exit(1);
           }
   
       }
   
   }