Deleting a dataset

You can delete a dataset from a project by using the console or the DeleteDataset operation. The images referenced by a dataset aren't deleted. If you delete the test dataset from a project that has a training and a test dataset, the project reverts to a single dataset project—the remaining dataset is split during training to create a training and test dataset. If you delete the training dataset, you can't train a model in the project until you create a new training dataset.

Deleting a dataset (console)

Perform the steps in the following procedure to delete a dataset. If you delete all of the datasets in a project, the Create dataset page is displayed.

To delete a dataset (console)

1. Open the Amazon Lookout for Vision console at https://console.aws.amazon.com/lookoutvision/.

2. Choose Get started.

3. In the left navigation pane, choose Projects.

4. On the Projects page, select the project that contains the dataset that you want to delete.

5. In the left navigation pane, choose Dataset.

6. Choose Actions and then select the dataset that you want to delete.

7. In the Delete dialog box, enter delete to confirm that you want to delete the dataset.

8. Choose Delete training dataset or Delete test dataset to delete the dataset.

Deleting a dataset (SDK)

Use the DeleteDataset operation to delete a dataset.

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 example code to delete a model.

   CLI

   Change the value of the following

   • project-name to the name of the project that contains the model that you want to delete.

   • dataset-type to either train or test, depending on which dataset you want to delete. If you have a single dataset project, specify train to delete the dataset.

   aws lookoutvision delete-dataset --project-name project name\
     --dataset-type dataset type \
     --profile lookoutvision-access
   

   Python

   This code is taken from the AWS Documentation SDK examples GitHub repository. See the full example here.

       @staticmethod
       def delete_dataset(lookoutvision_client, project_name, dataset_type):
           """
           Deletes a Lookout for Vision dataset
   
           :param lookoutvision_client: A Boto3 Lookout for Vision client.
           :param project_name: The name of the project that contains the dataset that
                                you want to delete.
           :param dataset_type: The type (train or test) of the dataset that you
                                want to delete.
           """
           try:
               logger.info(
                   "Deleting the %s dataset for project %s.", dataset_type, project_name
               )
               lookoutvision_client.delete_dataset(
                   ProjectName=project_name, DatasetType=dataset_type
               )
               logger.info("Dataset deleted.")
           except ClientError:
               logger.exception("Service error: Couldn't delete dataset.")
               raise
   
   

   Java V2

   This code is taken from the AWS Documentation SDK examples GitHub repository. See the full example here.

   /**
    * Deletes the train or test dataset in an Amazon Lookout for Vision project.
    * 
    * @param lfvClient   An Amazon Lookout for Vision client.
    * @param projectName The name of the project in which you want to delete a
    *                    dataset.
    * @param datasetType The type of the dataset that you want to delete (train or
    *                    test).
    * @return Nothing.
    */
   public static void deleteDataset(LookoutVisionClient lfvClient, String projectName, String datasetType)
                   throws LookoutVisionException {
   
           logger.log(Level.INFO, "Deleting {0} dataset for project {1}",
                           new Object[] { datasetType, projectName });
   
           DeleteDatasetRequest deleteDatasetRequest = DeleteDatasetRequest.builder()
                           .projectName(projectName)
                           .datasetType(datasetType)
                           .build();
   
           lfvClient.deleteDataset(deleteDatasetRequest);
   
           logger.log(Level.INFO, "Deleted {0} dataset for project {1}",
                           new Object[] { datasetType, projectName });
   
   }