Module 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.

An array of Block objects is returned by both synchronous and asynchronous operations. In synchronous operations, such as DetectDocumentText, the array of Block objects is the entire set of results. In asynchronous operations, such as GetDocumentAnalysis, the array is returned over one or more responses.

For more information, see How Amazon Textract Works.

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).

The top and left values returned are ratios of the overall document page size. For example, if the input image is 700 x 200 pixels, and the top-left coordinate of the bounding box is 350 x 50 pixels, the API returns a left value of 0.5 (350/700) and a top value of 0.25 (50/200).

The width and height values represent the dimensions of the bounding box as a ratio of the overall document page dimension. For example, if the document page size is 700 x 200 pixels, and the bounding box width is 70 pixels, the width returned is 0.1.

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.

You pass image bytes to an Amazon Textract API operation by using the Bytes property. For example, you would use the Bytes property to pass a document loaded from a local file system. Image bytes passed by using the Bytes property must be base64 encoded. Your code might not need to encode document file bytes if you're using an AWS SDK to call Amazon Textract API operations.

You pass images stored in an S3 bucket to an Amazon Textract API operation by using the S3Object property. Documents stored in an S3 bucket don't need to be base64 encoded.

The AWS Region for the S3 bucket that contains the S3 object must match the AWS Region that you use for Amazon Textract operations.

If you use the AWS CLI to call Amazon Textract operations, passing image bytes using the Bytes property isn't supported. You must first upload the document to an Amazon S3 bucket, and then call the operation using the S3Object property.

For Amazon Textract to process an S3 object, the user must have permission to access the 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.

The input document can be an image file in JPEG or PNG format. It can also be a file in PDF format.

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.

OutputConfig is an optional parameter which lets you adjust where your output will be placed. By default, Amazon Textract will store the results internally and can only be accessed by the Get API operations. With OutputConfig enabled, you can set the name of the bucket the output will be sent to the file prefix of the results where you can download your results. Additionally, you can set the KMSKeyID parameter to a customer master key (CMK) to encrypt your output. Without this parameter set Amazon Textract will encrypt server-side using the AWS managed CMK for Amazon S3.

Decryption of Customer Content is necessary for processing of the documents by Amazon Textract. If your account is opted out under an AI services opt out policy then all unencrypted Customer Content is immediately and permanently deleted after the Customer Content has been processed by the service. No copy of of the output is retained by Amazon Textract. For information about how to opt out, see Managing AI services opt-out policy.

For more information on data privacy, see the Data Privacy FAQ.

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.

An array of Point objects, Polygon, is returned by DetectDocumentText. Polygon represents a fine-grained polygon around detected text. For more information, see Geometry in the Amazon Textract Developer Guide.

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.

The Type element provides the type of the relationship for all blocks in the IDs array.

S3Object

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

The AWS Region for the S3 bucket that contains the document must match the Region that you use for Amazon Textract operations.

For Amazon Textract to process a file in an S3 bucket, the user must have permission to access the S3 bucket and file.

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.