Describing a model (SDK)

You can use the DescribeProjectVersions API to get information about a version of a model. If you don't specify VersionName, DescribeProjectVersions returns descriptions for all model versions in the project.

To describe a model (SDK)

If you haven't already done so, install and configure the AWS CLI and the AWS SDKs. For more information, see Step 4: Set up the AWS CLI and AWS SDKs.

Use the following example code to describe a version of a model.

AWS CLI

Change the value of project-arn to the ARN of the project that you want to describe. Change the value of version-name to the version of the model that you want to describe.


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

Python

Use the following code. Supply the following command line parameters:

project_arn — the ARN of the model that you want to describe.
model_version — the version of the model that you want to describe.

For example: 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

Use the following code. Supply the following command line parameters:

project_arn — the ARN of the model that you want to describe.
model_version — the version of the model that you want to describe.


/*
   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);
        }

    }

}

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Document Conventions

Tagging a model

Copying a model (SDK)