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
Open the Amazon Rekognition console at
https://console.aws.amazon.com/rekognition/.
-
In the left pane, choose Use Custom Labels. The
Amazon Rekognition Custom Labels landing page is shown.
-
In the left navigation pane, choose Projects. The
Projects view is shown.
-
Choose the project that contains the dataset that you want to delete.
-
In the left navigation pane, under the project name, choose
Dataset
-
Choose Actions
-
To delete the training dataset, choose Delete training
dataset.
-
To delete the test dataset, choose Delete test
dataset.
-
In the Delete train or test
dataset dialog box, enter delete to
confirm that you want to delete the dataset.
-
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)
-
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 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:
# 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:
/*
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);
}
}
}
