Module aws_sdk_textract::types

Data structures used by operation inputs/outputs.

Modules

• builders
  Builders
• error
  Error types that Amazon Textract can respond with.

Structs

• Adapter

  An adapter selected for use when analyzing documents. Contains an adapter ID and a version number. Contains information on pages selected for analysis when analyzing documents asychronously.

• AdapterOverview

  Contains information on the adapter, including the adapter ID, Name, Creation time, and feature types.

• AdapterVersionDatasetConfig

  The dataset configuration options for a given version of an adapter. Can include an Amazon S3 bucket if specified.

• AdapterVersionEvaluationMetric

  Contains information on the metrics used to evalute the peformance of a given adapter version. Includes data for baseline model performance and individual adapter version perfromance.

• AdapterVersionOverview

  Summary info for an adapter version. Contains information on the AdapterId, AdapterVersion, CreationTime, FeatureTypes, and Status.

• AdaptersConfig

  Contains information about adapters used when analyzing a document, with each adapter specified using an AdapterId and version

• AnalyzeIdDetections

  Used to contain the information detected by an AnalyzeID operation.

• Block

  A Block represents items that are recognized in a document within a group of pixels close to each other. The information returned in a Block object depends on the type of operation. In text detection for documents (for example DetectDocumentText), you get information about the detected words and lines of text. In text analysis (for example AnalyzeDocument), you can also get information about the fields, tables, and selection elements that are detected in the document.

• BoundingBox

  The bounding box around the detected page, text, key-value pair, table, table cell, or selection element on a document page. The left (x-coordinate) and top (y-coordinate) are coordinates that represent the top and left sides of the bounding box. Note that the upper-left corner of the image is the origin (0,0).

• DetectedSignature

  A structure that holds information regarding a detected signature on a page.

• Document

  The input document, either as bytes or as an S3 object.

• DocumentGroup

  Summary information about documents grouped by the same document type.

• DocumentLocation

  The Amazon S3 bucket that contains the document to be processed. It's used by asynchronous operations.

• DocumentMetadata

  Information about the input document.

• EvaluationMetric

  The evaluation metrics (F1 score, Precision, and Recall) for an adapter version.

• ExpenseCurrency

  Returns the kind of currency detected.

• ExpenseDetection

  An object used to store information about the Value or Label detected by Amazon Textract.

• ExpenseDocument

  The structure holding all the information returned by AnalyzeExpense

• ExpenseField

  Breakdown of detected information, seperated into the catagories Type, LabelDetection, and ValueDetection

• ExpenseGroupProperty

  Shows the group that a certain key belongs to. This helps differentiate between names and addresses for different organizations, that can be hard to determine via JSON response.

• ExpenseType

  An object used to store information about the Type detected by Amazon Textract.

• Extraction

  Contains information extracted by an analysis operation after using StartLendingAnalysis.

• Geometry

  Information about where the following items are located on a document page: detected page, text, key-value pairs, tables, table cells, and selection elements.

• HumanLoopActivationOutput

  Shows the results of the human in the loop evaluation. If there is no HumanLoopArn, the input did not trigger human review.

• HumanLoopConfig

  Sets up the human review workflow the document will be sent to if one of the conditions is met. You can also set certain attributes of the image before review.

• HumanLoopDataAttributes

  Allows you to set attributes of the image. Currently, you can declare an image as free of personally identifiable information and adult content.

• IdentityDocument

  The structure that lists each document processed in an AnalyzeID operation.

• IdentityDocumentField

  Structure containing both the normalized type of the extracted information and the text associated with it. These are extracted as Type and Value respectively.

• LendingDetection

  The results extracted for a lending document.

• LendingDocument

  Holds the structured data returned by AnalyzeDocument for lending documents.

• LendingField

  Holds the normalized key-value pairs returned by AnalyzeDocument, including the document type, detected text, and geometry.

• LendingResult

  Contains the detections for each page analyzed through the Analyze Lending API.

• LendingSummary

  Contains information regarding DocumentGroups and UndetectedDocumentTypes.

• LineItemFields

  A structure that holds information about the different lines found in a document's tables.

• LineItemGroup

  A grouping of tables which contain LineItems, with each table identified by the table's LineItemGroupIndex.

• NormalizedValue

  Contains information relating to dates in a document, including the type of value, and the value.

• NotificationChannel

  The Amazon Simple Notification Service (Amazon SNS) topic to which Amazon Textract publishes the completion status of an asynchronous document operation.

• OutputConfig

  Sets whether or not your output will go to a user created bucket. Used to set the name of the bucket, and the prefix on the output file.

• PageClassification

  The class assigned to a Page object detected in an input document. Contains information regarding the predicted type/class of a document's page and the page number that the Page object was detected on.

• Point

  The X and Y coordinates of a point on a document page. The X and Y values that are returned are ratios of the overall document page size. For example, if the input document is 700 x 200 and the operation returns X=0.5 and Y=0.25, then the point is at the (350,50) pixel coordinate on the document page.

• Prediction

  Contains information regarding predicted values returned by Amazon Textract operations, including the predicted value and the confidence in the predicted value.

• QueriesConfig

• Query

  Each query contains the question you want to ask in the Text and the alias you want to associate.

• Relationship

  Information about how blocks are related to each other. A Block object contains 0 or more Relation objects in a list, Relationships. For more information, see Block.

• S3Object

  The S3 bucket name and file name that identifies the document.

• SignatureDetection

  Information regarding a detected signature on a page.

• SplitDocument

  Contains information about the pages of a document, defined by logical boundary.

• UndetectedSignature

  A structure containing information about an undetected signature on a page where it was expected but not found.

• Warning

  A warning about an issue that occurred during asynchronous text analysis (StartDocumentAnalysis) or asynchronous document text detection (StartDocumentTextDetection).

Enums

• AdapterVersionStatus
  When writing a match expression against AdapterVersionStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• AutoUpdate
  When writing a match expression against AutoUpdate, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• BlockType
  When writing a match expression against BlockType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• ContentClassifier
  When writing a match expression against ContentClassifier, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• EntityType
  When writing a match expression against EntityType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• FeatureType
  When writing a match expression against FeatureType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• JobStatus
  When writing a match expression against JobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• RelationshipType
  When writing a match expression against RelationshipType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• SelectionStatus
  When writing a match expression against SelectionStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• TextType
  When writing a match expression against TextType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
• ValueType
  When writing a match expression against ValueType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.