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Start Document Analysis

textract_start_document_analysis R Documentation

Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements

Description

Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements.

start_document_analysis can analyze text in documents that are in JPEG, PNG, TIFF, and PDF format. The documents are stored in an Amazon S3 bucket. Use DocumentLocation to specify the bucket name and file name of the document.

start_document_analysis returns a job identifier (JobId) that you use to get the results of the operation. When text analysis is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you specify in NotificationChannel. To get the results of the text analysis operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call get_document_analysis, and pass the job identifier (JobId) from the initial call to start_document_analysis.

For more information, see Document Text Analysis.

Usage

textract_start_document_analysis(DocumentLocation, FeatureTypes,
  ClientRequestToken, JobTag, NotificationChannel, OutputConfig, KMSKeyId,
  QueriesConfig, AdaptersConfig)

Arguments

DocumentLocation

[required] The location of the document to be processed.

FeatureTypes

[required] A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to FeatureTypes. All lines and words detected in the document are included in the response (including text that isn't related to the value of FeatureTypes).

ClientRequestToken

The idempotent token that you use to identify the start request. If you use the same token with multiple start_document_analysis requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations.

JobTag

An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).

NotificationChannel

The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.

OutputConfig

Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.

KMSKeyId

The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.

QueriesConfig
AdaptersConfig

Specifies the adapter to be used when analyzing a document.

Value

A list with the following syntax: 

list(
  JobId = "string"
)

Request syntax

svc$start_document_analysis(
  DocumentLocation = list(
    S3Object = list(
      Bucket = "string",
      Name = "string",
      Version = "string"
    )
  ),
  FeatureTypes = list(
    "TABLES"|"FORMS"|"QUERIES"|"SIGNATURES"|"LAYOUT"
  ),
  ClientRequestToken = "string",
  JobTag = "string",
  NotificationChannel = list(
    SNSTopicArn = "string",
    RoleArn = "string"
  ),
  OutputConfig = list(
    S3Bucket = "string",
    S3Prefix = "string"
  ),
  KMSKeyId = "string",
  QueriesConfig = list(
    Queries = list(
      list(
        Text = "string",
        Alias = "string",
        Pages = list(
          "string"
        )
      )
    )
  ),
  AdaptersConfig = list(
    Adapters = list(
      list(
        AdapterId = "string",
        Pages = list(
          "string"
        ),
        Version = "string"
      )
    )
  )
)