CREATEDATASET()`¶

About 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.

Method Signature¶

METHODS /AWS1/IF_REK~CREATEDATASET
  IMPORTING
    !IO_DATASETSOURCE TYPE REF TO /AWS1/CL_REKDATASETSOURCE OPTIONAL
    !IV_DATASETTYPE TYPE /AWS1/REKDATASETTYPE OPTIONAL
    !IV_PROJECTARN TYPE /AWS1/REKPROJECTARN OPTIONAL
    !IT_TAGS TYPE /AWS1/CL_REKTAGMAP_W=>TT_TAGMAP OPTIONAL
  RETURNING
    VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_rekcreatedatasetrsp
  RAISING
    /AWS1/CX_REKACCESSDENIEDEX
    /AWS1/CX_REKINTERNALSERVERERR
    /AWS1/CX_REKINVALIDPARAMETEREX
    /AWS1/CX_REKINVALIDS3OBJECTEX
    /AWS1/CX_REKLIMITEXCEEDEDEX
    /AWS1/CX_REKPROVTHRUPUTEXCDEX
    /AWS1/CX_REKRESRCALRDYEXISTSEX
    /AWS1/CX_REKRESOURCENOTFOUNDEX
    /AWS1/CX_REKTHROTTLINGEX
    /AWS1/CX_REKCLIENTEXC
    /AWS1/CX_REKSERVEREXC
    /AWS1/CX_RT_TECHNICAL_GENERIC
    /AWS1/CX_RT_SERVICE_GENERIC.

IMPORTING¶

Required arguments:¶

`iv_datasettype` `TYPE /AWS1/REKDATASETTYPE` `/AWS1/REKDATASETTYPE`¶

The type of the dataset. Specify TRAIN to create a training dataset. Specify TEST to create a test dataset.

`iv_projectarn` `TYPE /AWS1/REKPROJECTARN` `/AWS1/REKPROJECTARN`¶

The ARN of the Amazon Rekognition Custom Labels project to which you want to asssign the dataset.

Optional arguments:¶

`io_datasetsource` `TYPE REF TO /AWS1/CL_REKDATASETSOURCE` `/AWS1/CL_REKDATASETSOURCE`¶

The source files for the dataset. You can specify the ARN of an existing dataset or specify the Amazon S3 bucket location of an Amazon Sagemaker format manifest file. If you don't specify datasetSource, an empty dataset is created. To add labeled images to the dataset, You can use the console or call UpdateDatasetEntries.

`it_tags` `TYPE /AWS1/CL_REKTAGMAP_W=>TT_TAGMAP` `TT_TAGMAP`¶

A set of tags (key-value pairs) that you want to attach to the dataset.

RETURNING¶

`oo_output` `TYPE REF TO /aws1/cl_rekcreatedatasetrsp` `/AWS1/CL_REKCREATEDATASETRSP`¶

Domain /AWS1/RT_ACCOUNT_ID

Primitive Type NUMC

Examples¶

Syntax Example¶

This is an example of the syntax for calling the method. It includes every possible argument and initializes every possible value. The data provided is not necessarily semantically accurate (for example the value "string" may be provided for something that is intended to be an instance ID, or in some cases two arguments may be mutually exclusive). The syntax shows the ABAP syntax for creating the various data structures.

DATA(lo_result) = lo_client->createdataset(
  io_datasetsource = new /aws1/cl_rekdatasetsource(
    io_groundtruthmanifest = new /aws1/cl_rekgroundtruthmanif00(
      io_s3object = new /aws1/cl_reks3object(
        iv_bucket = |string|
        iv_name = |string|
        iv_version = |string|
      )
    )
    iv_datasetarn = |string|
  )
  it_tags = VALUE /aws1/cl_rektagmap_w=>tt_tagmap(
    (
      VALUE /aws1/cl_rektagmap_w=>ts_tagmap_maprow(
        key = |string|
        value = new /aws1/cl_rektagmap_w( |string| )
      )
    )
  )
  iv_datasettype = |string|
  iv_projectarn = |string|
).

This is an example of reading all possible response values

lo_result = lo_result.
IF lo_result IS NOT INITIAL.
  lv_datasetarn = lo_result->get_datasetarn( ).
ENDIF.

To create an Amazon Rekognition Custom Labels dataset¶

Creates an Amazon Rekognition Custom Labels dataset with a manifest file stored in an Amazon S3 bucket.

DATA(lo_result) = lo_client->createdataset(
  io_datasetsource = new /aws1/cl_rekdatasetsource(
    io_groundtruthmanifest = new /aws1/cl_rekgroundtruthmanif00(
      io_s3object = new /aws1/cl_reks3object(
        iv_bucket = |my-bucket|
        iv_name = |datasets/flowers_training/manifests/output/output.manifest|
      )
    )
  )
  iv_datasettype = |TRAIN|
  iv_projectarn = |arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815|
).

/AWS1/IF_REK=>CREATEDATASET()¶