Deleting a dataset

You can delete the training and test datasets from a project.

Deleting a dataset (Console)

Use the following procedure to delete a dataset. Afterwards, if the project has one remaining dataset (train or test), the project details page is shown. If the project has no remaining datasets, the Create dataset page is shown.

If you delete the training dataset, you must create a new training dataset for the project before you can train a model. For more information, see Creating training and test datasets with images.

If you delete the test dataset, you can train a model without creating a new test dataset. During training, the training dataset is split to create a new test dataset for the project. Splitting the training dataset reduces the number of images available for training. To maintain quality, we recommend creating a new test dataset before training a model. For more information, see Adding a dataset to a project.

To delete a dataset

1. Open the Amazon Rekognition console at https://console.aws.amazon.com/rekognition/.

2. In the left pane, choose Use Custom Labels. The Amazon Rekognition Custom Labels landing page is shown.

3. In the left navigation pane, choose Projects. The Projects view is shown.

4. Choose the project that contains the dataset that you want to delete.

5. In the left navigation pane, under the project name, choose Dataset

6. Choose Actions

7. To delete the training dataset, choose Delete training dataset.

8. To delete the test dataset, choose Delete test dataset.

9. In the Delete train or test dataset dialog box, enter delete to confirm that you want to delete the dataset.

10. Choose Delete train or test dataset to delete the dataset.

Deleting an Amazon Rekognition Custom Labels dataset (SDK)

You delete an Amazon Rekognition Custom Labels dataset by calling DeleteDataset and supplying the Amazon Resource Name (ARN) of the dataset that you want to delete. To get the ARNs of the training and test datasets within a project, call DescribeProjects. The response includes an array of ProjectDescription objects. The dataset ARNs (DatasetArn) and dataset types (DatasetType) are in the Datasets list.

If you delete the training dataset, you need to create a new training dataset for the project before you can train a model. If you delete the test dataset, you need to create a new test dataset before you can train the model. For more information, see Adding a dataset to a project (SDK).

To delete a dataset (SDK)

1. 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.

2. Use the following code to delete a dataset.

   AWS CLI

   Change the value of dataset-arn with the ARN of the dataset that you want to delete.

   aws rekognition delete-dataset --dataset-arn dataset-arn \
     --profile custom-labels-access

   Python

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

   • dataset_arn — the ARN of the dataset that you want to delete.

   # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
   # SPDX-License-Identifier: Apache-2.0
   
   """
   Purpose
   Shows how to delete an Amazon Rekognition Custom Labels dataset.
   """
   import argparse
   import logging
   import time
   import boto3
   
   from botocore.exceptions import ClientError
   
   logger = logging.getLogger(__name__)
   
   
   def delete_dataset(rek_client, dataset_arn):
       """
       Deletes an Amazon Rekognition Custom Labels dataset.
       :param rek_client: The Amazon Rekognition Custom Labels Boto3 client.
       :param dataset_arn: The ARN of the dataset that you want to delete.
       """
   
       try:
           # Delete the dataset,
           logger.info("Deleting dataset: %s", dataset_arn)
   
           rek_client.delete_dataset(DatasetArn=dataset_arn)
   
           deleted = False
   
           logger.info("waiting for dataset deletion %s", dataset_arn)
   
           # Dataset might not be deleted yet, so wait.
           while deleted is False:
               try:
                   rek_client.describe_dataset(DatasetArn=dataset_arn)
                   time.sleep(5)
               except ClientError as err:
                   if err.response['Error']['Code'] == 'ResourceNotFoundException':
                       logger.info("dataset deleted: %s", dataset_arn)
                       deleted = True
                   else:
                       raise
   
           logger.info("dataset deleted: %s", dataset_arn)
   
           return True
   
       except ClientError as err:
           logger.exception("Couldn't delete dataset - %s: %s",
                            dataset_arn, 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(
           "dataset_arn", help="The ARN of the dataset that you want to delete."
       )
   
   
   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"Deleting dataset: {args.dataset_arn}")
   
           # Delete the dataset.
           session = boto3.Session(profile_name='custom-labels-access')
           rekognition_client = session.client("rekognition")
   
           delete_dataset(rekognition_client,
                          args.dataset_arn)
   
           print(f"Finished deleting dataset: {args.dataset_arn}")
   
       except ClientError as err:
           error_message = f"Problem deleting dataset: {err}"
           logger.exception(error_message)
           print(error_message)
   
   
   if __name__ == "__main__":
       main()
   

   Java V2

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

   • dataset_arn — the ARN of the dataset that you want to delete.

   /*
      Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
      SPDX-License-Identifier: Apache-2.0
   */
   package com.example.rekognition;
   
   import java.util.logging.Level;
   import java.util.logging.Logger;
   
   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.DeleteDatasetRequest;
   import software.amazon.awssdk.services.rekognition.model.DeleteDatasetResponse;
   import software.amazon.awssdk.services.rekognition.model.DescribeDatasetRequest;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   
   public class DeleteDataset {
   
       public static final Logger logger = Logger.getLogger(DeleteDataset.class.getName());
   
       public static void deleteMyDataset(RekognitionClient rekClient, String datasetArn) throws InterruptedException {
   
           try {
   
               logger.log(Level.INFO, "Deleting dataset: {0}", datasetArn);
   
               // Delete the dataset
   
               DeleteDatasetRequest deleteDatasetRequest = DeleteDatasetRequest.builder().datasetArn(datasetArn).build();
   
               DeleteDatasetResponse response = rekClient.deleteDataset(deleteDatasetRequest);
   
               // Wait until deletion finishes
   
               DescribeDatasetRequest describeDatasetRequest = DescribeDatasetRequest.builder().datasetArn(datasetArn)
                       .build();
   
               Boolean deleted = false;
   
               do {
   
                   try {
   
                       rekClient.describeDataset(describeDatasetRequest);
                       Thread.sleep(5000);
                   } catch (RekognitionException e) {
                       String errorCode = e.awsErrorDetails().errorCode();
                       if (errorCode.equals("ResourceNotFoundException")) {
                           logger.log(Level.INFO, "Dataset deleted: {0}", datasetArn);
                           deleted = true;
                       } else {
                           logger.log(Level.SEVERE, "Client error occurred: {0}", e.getMessage());
                           throw e;
                       }
   
                   }
   
               } while (Boolean.FALSE.equals(deleted));
   
               logger.log(Level.INFO, "Dataset deleted: {0} ", datasetArn);
   
           } catch (
   
           RekognitionException e) {
               logger.log(Level.SEVERE, "Client error occurred: {0}", e.getMessage());
               throw e;
           }
   
       }
   
       public static void main(String args[]) {
   
           final String USAGE = "\n" + "Usage: " + "<dataset_arn>\n\n" + "Where:\n"
                   + "   dataset_arn - The ARN of the dataset that you want to delete.\n\n";
   
           if (args.length != 1) {
               System.out.println(USAGE);
               System.exit(1);
           }
   
           String datasetArn = args[0];
   
           try {
   
               // Get the Rekognition client.
               RekognitionClient rekClient = RekognitionClient.builder()
                   .credentialsProvider(ProfileCredentialsProvider.create("custom-labels-access"))
                   .region(Region.US_WEST_2)
                   .build();
   
   
               // Delete the dataset
               deleteMyDataset(rekClient, datasetArn);
   
               System.out.println(String.format("Dataset deleted: %s", datasetArn));
   
               rekClient.close();
   
           } catch (RekognitionException rekError) {
               logger.log(Level.SEVERE, "Rekognition client error: {0}", rekError.getMessage());
               System.exit(1);
           }
   
           catch (InterruptedException intError) {
               logger.log(Level.SEVERE, "Exception while sleeping: {0}", intError.getMessage());
               System.exit(1);
           }
   
       }
   
   }