createDataset

This operation applies only to Amazon Rekognition Custom Labels.

Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using an Amazon Sagemaker format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.

To create a training dataset for a project, specify TRAIN for the value of DatasetType. To create the test dataset for a project, specify TEST for the value of DatasetType.

The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset. Creating a dataset takes a while to complete. Use DescribeDataset to check the current status. The dataset created successfully if the value of Status is CREATE_COMPLETE.

To check if any non-terminal errors occurred, call ListDatasetEntries and check for the presence of errors lists in the JSON Lines.

Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). Currently, you can't access the terminal error information.

For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide.

This operation requires permissions to perform the rekognition:CreateDataset action. If you want to copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries action.

Samples

fun main() { 
   //sampleStart 
   // Creates an Amazon Rekognition Custom Labels dataset with a manifest file stored in an Amazon S3
// bucket.
val resp = rekognitionClient.createDataset {
    datasetSource = DatasetSource {
        groundTruthManifest = GroundTruthManifest {
            s3Object = S3Object {
                bucket = "my-bucket"
                name = "datasets/flowers_training/manifests/output/output.manifest"
            }
        }
    }
    datasetType = DatasetType.fromValue("TRAIN")
    projectArn = "arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815"
} 
   //sampleEnd
}