Use StartDocumentTextDetection with an AWS SDK or CLI - AWS SDK Code Examples

There are more AWS SDK examples available in the AWS Doc SDK Examples GitHub repo.

Use StartDocumentTextDetection with an AWS SDK or CLI

The following code examples show how to use StartDocumentTextDetection.

CLI
AWS CLI

To start detecting text in a multi-page document

The following start-document-text-detection example shows how to start asynchronous detection of text in a multi-page document.

Linux/macOS:

aws textract start-document-text-detection \
        --document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
        --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleARN"

Windows:

aws textract start-document-text-detection \
    --document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
    --region region-name \
    --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"

Output:

{
    "JobId": "57849a3dc627d4df74123dca269d69f7b89329c870c65bb16c9fd63409d200b9"
}

For more information, see Detecting and Analyzing Text in Multi-Page Documents in the Amazon Textract Developers Guide

Python
SDK for Python (Boto3)
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Start an asynchronous job to detect text in a document.

class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def start_detection_job(
        self, bucket_name, document_file_name, sns_topic_arn, sns_role_arn
    ):
        """
        Starts an asynchronous job to detect text elements in an image stored in an
        Amazon S3 bucket. Textract publishes a notification to the specified Amazon SNS
        topic when the job completes.
        The image must be in PNG, JPG, or PDF format.

        :param bucket_name: The name of the Amazon S3 bucket that contains the image.
        :param document_file_name: The name of the document image stored in Amazon S3.
        :param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
                              where the job completion notification is published.
        :param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
                             role that can be assumed by Textract and grants permission
                             to publish to the Amazon SNS topic.
        :return: The ID of the job.
        """
        try:
            response = self.textract_client.start_document_text_detection(
                DocumentLocation={
                    "S3Object": {"Bucket": bucket_name, "Name": document_file_name}
                },
                NotificationChannel={
                    "SNSTopicArn": sns_topic_arn,
                    "RoleArn": sns_role_arn,
                },
            )
            job_id = response["JobId"]
            logger.info(
                "Started text detection job %s on %s.", job_id, document_file_name
            )
        except ClientError:
            logger.exception("Couldn't detect text in %s.", document_file_name)
            raise
        else:
            return job_id
SAP ABAP
SDK for SAP ABAP
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository. 


    "Starts the asynchronous detection of text in a document."
    "Amazon Textract can detect lines of text and the words that make up a line of text."

    "Create an ABAP object for the Amazon S3 object."
    DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
      iv_name   = iv_s3object ).
    "Create an ABAP object for the document."
    DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).
    "Start document analysis."
    TRY.
        oo_result = lo_tex->startdocumenttextdetection( io_documentlocation = lo_documentlocation ).
        DATA(lv_jobid) = oo_result->get_jobid( ).             "oo_result is returned for testing purposes."
        MESSAGE 'Document analysis started.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texbaddocumentex.
        MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
      CATCH /aws1/cx_texdocumenttoolargeex.
        MESSAGE 'The document is too large.' TYPE 'E'.
      CATCH /aws1/cx_texidempotentprmmis00.
        MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidkmskeyex.
        MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texlimitexceededex.
        MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
      CATCH /aws1/cx_texunsupporteddocex.
        MESSAGE 'The document is not supported.' TYPE 'E'.
    ENDTRY.