Creazione di un set di dati utilizzando un set di dati esistente (SDK)

La procedura seguente mostra come creare un set di dati da un set di dati esistente utilizzando l'CreateDatasetoperazione.

Se non l'hai ancora fatto, installa e configura ilAWS CLI e gliAWS SDK. Per ulteriori informazioni, consulta Passaggio 4: configura il AWS CLI e AWS SDKs.

Usa il seguente codice di esempio per creare un set di dati copiando un altro set di dati.

AWS CLI

Usa il codice seguente per creare il set di dati. Sostituire quanto segue:

project_arn— l'ARN del progetto a cui aggiungere il dati.
dataset_type— con il tipo di set di dati (TRAINoTEST) che si desidera creare nel progetto.
dataset_arn— con l'ARN del dati che si desidera copiare.


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

Python

L'esempio seguente crea un set di dati utilizzando un set di dati esistente e ne visualizza l'ARN.

Per eseguire il programma, fornisci i seguenti argomenti della riga di comando:

project_arn— l'ARN del progetto che si desidera utilizzare.
dataset_type— il tipo di set di dati del progetto che desideri creare (trainotest).
dataset_arn— l'ARN del dati da cui creare il dati.


# 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

L'esempio seguente crea un set di dati utilizzando un set di dati esistente e ne visualizza l'ARN.

Per eseguire il programma, fornisci i seguenti argomenti della riga di comando:

project_arn— l'ARN del progetto che si desidera utilizzare.
dataset_type— il tipo di set di dati del progetto che desideri creare (trainotest).
dataset_arn— l'ARN del dati da cui creare il dati.


/*
   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);
        }

    }

}

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Descrizione di un set di dati (SDK)