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# Beschreibung eines Modells (SDK)
Sie können die `DescribeProjectVersions`-API verwenden, um Informationen über eine Version eines Modells abzurufen. Wenn Sie `VersionName` nicht angeben, gibt `DescribeProjectVersions` Beschreibungen für alle Modellversionen im Projekt zurück.
**So beschreiben Sie ein Modell (SDK)**
1. Falls Sie dies noch nicht getan haben, installieren und konfigurieren Sie den AWS CLI und den AWS SDKs. Weitere Informationen finden Sie unter [Schritt 4: Richten Sie das und ein AWS CLI AWS SDKs](su-awscli-sdk.md).
1. Verwenden Sie den folgenden Beispielcode, um eine Version eines Modells zu beschreiben.
------
#### [ AWS CLI ]
Ändern Sie den Wert von `project-arn` in den ARN des Projekts, das Sie beschreiben möchten. Ändern Sie den Wert von `version-name` in die Version des Modells, das Sie beschreiben möchten.
```
aws rekognition describe-project-versions --project-arn project_arn \
--version-names version_name \
--profile custom-labels-access
```
------
#### [ Python ]
Verwenden Sie folgenden Code. Geben Sie die folgenden Befehlszeilenparameter an:
+ project\$1arn — der ARN des Modells, das Sie beschreiben möchten.
+ model\$1version — 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 folgenden Code. Geben Sie die folgenden Befehlszeilenparameter an:
+ project\$1arn — der ARN des Modells, das Sie beschreiben möchten.
+ model\$1version — 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: " + " \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);
}
}
}
```
------