discord-bot-cdk-construct/node_modules/aws-sdk/clients/textract.d.ts

A quick CDK Construct for creating a serverless Discord bot in AWS!

import {Request} from '../lib/request';
import {Response} from '../lib/response';
import {AWSError} from '../lib/error';
import {Service} from '../lib/service';
import {ServiceConfigurationOptions} from '../lib/service';
import {ConfigBase as Config} from '../lib/config-base';
interface Blob {}
declare class Textract extends Service {
  /**
   * Constructs a service object. This object has one method for each API operation.
   */
  constructor(options?: Textract.Types.ClientConfiguration)
  config: Config & Textract.Types.ClientConfiguration;
  /**
   * Analyzes an input document for relationships between detected items.  The types of information returned are as follows:    Form data (key-value pairs). The related information is returned in two Block objects, each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.   Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.   Lines and words of text. A LINE Block object contains one or more WORD Block objects. All lines and words that are detected in the document are returned (including text that doesn't have a relationship with the value of FeatureTypes).    Signatures. A SIGNATURE Block object contains the location information of a signature in a document. If used in conjunction with forms or tables, a signature can be given a Key-Value pairing or be detected in the cell of a table.   Query. A QUERY Block object contains the query text, alias and link to the associated Query results block object.   Query Result. A QUERY_RESULT Block object contains the answer to the query and an ID that connects it to the query asked. This Block also contains a confidence score.   Selection elements such as check boxes and option buttons (radio buttons) can be detected in form data and in tables. A SELECTION_ELEMENT Block object contains information about a selection element, including the selection status. You can choose which type of analysis to perform by specifying the FeatureTypes list.  The output is returned in a list of Block objects.  AnalyzeDocument is a synchronous operation. To analyze documents asynchronously, use StartDocumentAnalysis. For more information, see Document Text Analysis.
   */
  analyzeDocument(params: Textract.Types.AnalyzeDocumentRequest, callback?: (err: AWSError, data: Textract.Types.AnalyzeDocumentResponse) => void): Request<Textract.Types.AnalyzeDocumentResponse, AWSError>;
  /**
   * Analyzes an input document for relationships between detected items.  The types of information returned are as follows:    Form data (key-value pairs). The related information is returned in two Block objects, each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.   Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.   Lines and words of text. A LINE Block object contains one or more WORD Block objects. All lines and words that are detected in the document are returned (including text that doesn't have a relationship with the value of FeatureTypes).    Signatures. A SIGNATURE Block object contains the location information of a signature in a document. If used in conjunction with forms or tables, a signature can be given a Key-Value pairing or be detected in the cell of a table.   Query. A QUERY Block object contains the query text, alias and link to the associated Query results block object.   Query Result. A QUERY_RESULT Block object contains the answer to the query and an ID that connects it to the query asked. This Block also contains a confidence score.   Selection elements such as check boxes and option buttons (radio buttons) can be detected in form data and in tables. A SELECTION_ELEMENT Block object contains information about a selection element, including the selection status. You can choose which type of analysis to perform by specifying the FeatureTypes list.  The output is returned in a list of Block objects.  AnalyzeDocument is a synchronous operation. To analyze documents asynchronously, use StartDocumentAnalysis. For more information, see Document Text Analysis.
   */
  analyzeDocument(callback?: (err: AWSError, data: Textract.Types.AnalyzeDocumentResponse) => void): Request<Textract.Types.AnalyzeDocumentResponse, AWSError>;
  /**
   *  AnalyzeExpense synchronously analyzes an input document for financially related relationships between text. Information is returned as ExpenseDocuments and seperated as follows:    LineItemGroups- A data set containing LineItems which store information about the lines of text, such as an item purchased and its price on a receipt.    SummaryFields- Contains all other information a receipt, such as header information or the vendors name.  
   */
  analyzeExpense(params: Textract.Types.AnalyzeExpenseRequest, callback?: (err: AWSError, data: Textract.Types.AnalyzeExpenseResponse) => void): Request<Textract.Types.AnalyzeExpenseResponse, AWSError>;
  /**
   *  AnalyzeExpense synchronously analyzes an input document for financially related relationships between text. Information is returned as ExpenseDocuments and seperated as follows:    LineItemGroups- A data set containing LineItems which store information about the lines of text, such as an item purchased and its price on a receipt.    SummaryFields- Contains all other information a receipt, such as header information or the vendors name.  
   */
  analyzeExpense(callback?: (err: AWSError, data: Textract.Types.AnalyzeExpenseResponse) => void): Request<Textract.Types.AnalyzeExpenseResponse, AWSError>;
  /**
   * Analyzes identity documents for relevant information. This information is extracted and returned as IdentityDocumentFields, which records both the normalized field and value of the extracted text. Unlike other Amazon Textract operations, AnalyzeID doesn't return any Geometry data.
   */
  analyzeID(params: Textract.Types.AnalyzeIDRequest, callback?: (err: AWSError, data: Textract.Types.AnalyzeIDResponse) => void): Request<Textract.Types.AnalyzeIDResponse, AWSError>;
  /**
   * Analyzes identity documents for relevant information. This information is extracted and returned as IdentityDocumentFields, which records both the normalized field and value of the extracted text. Unlike other Amazon Textract operations, AnalyzeID doesn't return any Geometry data.
   */
  analyzeID(callback?: (err: AWSError, data: Textract.Types.AnalyzeIDResponse) => void): Request<Textract.Types.AnalyzeIDResponse, AWSError>;
  /**
   * Detects text in the input document. Amazon Textract can detect lines of text and the words that make up a line of text. The input document must be in one of the following image formats: JPEG, PNG, PDF, or TIFF. DetectDocumentText returns the detected text in an array of Block objects.  Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD.  DetectDocumentText is a synchronous operation. To analyze documents asynchronously, use StartDocumentTextDetection. For more information, see Document Text Detection.
   */
  detectDocumentText(params: Textract.Types.DetectDocumentTextRequest, callback?: (err: AWSError, data: Textract.Types.DetectDocumentTextResponse) => void): Request<Textract.Types.DetectDocumentTextResponse, AWSError>;
  /**
   * Detects text in the input document. Amazon Textract can detect lines of text and the words that make up a line of text. The input document must be in one of the following image formats: JPEG, PNG, PDF, or TIFF. DetectDocumentText returns the detected text in an array of Block objects.  Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD.  DetectDocumentText is a synchronous operation. To analyze documents asynchronously, use StartDocumentTextDetection. For more information, see Document Text Detection.
   */
  detectDocumentText(callback?: (err: AWSError, data: Textract.Types.DetectDocumentTextResponse) => void): Request<Textract.Types.DetectDocumentTextResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes text in a document. You start asynchronous text analysis by calling StartDocumentAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentAnalysis. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis.  GetDocumentAnalysis returns an array of Block objects. The following types of information are returned:    Form data (key-value pairs). The related information is returned in two Block objects, each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.   Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.   Lines and words of text. A LINE Block object contains one or more WORD Block objects. All lines and words that are detected in the document are returned (including text that doesn't have a relationship with the value of the StartDocumentAnalysis FeatureTypes input parameter).    Query. A QUERY Block object contains the query text, alias and link to the associated Query results block object.   Query Results. A QUERY_RESULT Block object contains the answer to the query and an ID that connects it to the query asked. This Block also contains a confidence score.    While processing a document with queries, look out for INVALID_REQUEST_PARAMETERS output. This indicates that either the per page query limit has been exceeded or that the operation is trying to query a page in the document which doesn’t exist.   Selection elements such as check boxes and option buttons (radio buttons) can be detected in form data and in tables. A SELECTION_ELEMENT Block object contains information about a selection element, including the selection status. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentAnalysis, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentAnalysis. For more information, see Document Text Analysis.
   */
  getDocumentAnalysis(params: Textract.Types.GetDocumentAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.GetDocumentAnalysisResponse) => void): Request<Textract.Types.GetDocumentAnalysisResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes text in a document. You start asynchronous text analysis by calling StartDocumentAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentAnalysis. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis.  GetDocumentAnalysis returns an array of Block objects. The following types of information are returned:    Form data (key-value pairs). The related information is returned in two Block objects, each of type KEY_VALUE_SET: a KEY Block object and a VALUE Block object. For example, Name: Ana Silva Carolina contains a key and value. Name: is the key. Ana Silva Carolina is the value.   Table and table cell data. A TABLE Block object contains information about a detected table. A CELL Block object is returned for each cell in a table.   Lines and words of text. A LINE Block object contains one or more WORD Block objects. All lines and words that are detected in the document are returned (including text that doesn't have a relationship with the value of the StartDocumentAnalysis FeatureTypes input parameter).    Query. A QUERY Block object contains the query text, alias and link to the associated Query results block object.   Query Results. A QUERY_RESULT Block object contains the answer to the query and an ID that connects it to the query asked. This Block also contains a confidence score.    While processing a document with queries, look out for INVALID_REQUEST_PARAMETERS output. This indicates that either the per page query limit has been exceeded or that the operation is trying to query a page in the document which doesn’t exist.   Selection elements such as check boxes and option buttons (radio buttons) can be detected in form data and in tables. A SELECTION_ELEMENT Block object contains information about a selection element, including the selection status. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentAnalysis, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentAnalysis. For more information, see Document Text Analysis.
   */
  getDocumentAnalysis(callback?: (err: AWSError, data: Textract.Types.GetDocumentAnalysisResponse) => void): Request<Textract.Types.GetDocumentAnalysisResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that detects text in a document. Amazon Textract can detect lines of text and the words that make up a line of text. You start asynchronous text detection by calling StartDocumentTextDetection, which returns a job identifier (JobId). When the text detection operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentTextDetection. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection.  GetDocumentTextDetection returns an array of Block objects.  Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentTextDetection, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentTextDetection. For more information, see Document Text Detection.
   */
  getDocumentTextDetection(params: Textract.Types.GetDocumentTextDetectionRequest, callback?: (err: AWSError, data: Textract.Types.GetDocumentTextDetectionResponse) => void): Request<Textract.Types.GetDocumentTextDetectionResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that detects text in a document. Amazon Textract can detect lines of text and the words that make up a line of text. You start asynchronous text detection by calling StartDocumentTextDetection, which returns a job identifier (JobId). When the text detection operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartDocumentTextDetection. To get the results of the text-detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection.  GetDocumentTextDetection returns an array of Block objects.  Each document page has as an associated Block of type PAGE. Each PAGE Block object is the parent of LINE Block objects that represent the lines of detected text on a page. A LINE Block object is a parent for each word that makes up the line. Words are represented by Block objects of type WORD. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetDocumentTextDetection, and populate the NextToken request parameter with the token value that's returned from the previous call to GetDocumentTextDetection. For more information, see Document Text Detection.
   */
  getDocumentTextDetection(callback?: (err: AWSError, data: Textract.Types.GetDocumentTextDetectionResponse) => void): Request<Textract.Types.GetDocumentTextDetectionResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes invoices and receipts. Amazon Textract finds contact information, items purchased, and vendor name, from input invoices and receipts. You start asynchronous invoice/receipt analysis by calling StartExpenseAnalysis, which returns a job identifier (JobId). Upon completion of the invoice/receipt analysis, Amazon Textract publishes the completion status to the Amazon Simple Notification Service (Amazon SNS) topic. This topic must be registered in the initial call to StartExpenseAnalysis. To get the results of the invoice/receipt analysis operation, first ensure that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetExpenseAnalysis, and pass the job identifier (JobId) from the initial call to StartExpenseAnalysis. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetExpenseAnalysis, and populate the NextToken request parameter with the token value that's returned from the previous call to GetExpenseAnalysis. For more information, see Analyzing Invoices and Receipts.
   */
  getExpenseAnalysis(params: Textract.Types.GetExpenseAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.GetExpenseAnalysisResponse) => void): Request<Textract.Types.GetExpenseAnalysisResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes invoices and receipts. Amazon Textract finds contact information, items purchased, and vendor name, from input invoices and receipts. You start asynchronous invoice/receipt analysis by calling StartExpenseAnalysis, which returns a job identifier (JobId). Upon completion of the invoice/receipt analysis, Amazon Textract publishes the completion status to the Amazon Simple Notification Service (Amazon SNS) topic. This topic must be registered in the initial call to StartExpenseAnalysis. To get the results of the invoice/receipt analysis operation, first ensure that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetExpenseAnalysis, and pass the job identifier (JobId) from the initial call to StartExpenseAnalysis. Use the MaxResults parameter to limit the number of blocks that are returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetExpenseAnalysis, and populate the NextToken request parameter with the token value that's returned from the previous call to GetExpenseAnalysis. For more information, see Analyzing Invoices and Receipts.
   */
  getExpenseAnalysis(callback?: (err: AWSError, data: Textract.Types.GetExpenseAnalysisResponse) => void): Request<Textract.Types.GetExpenseAnalysisResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes text in a lending document.  You start asynchronous text analysis by calling StartLendingAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartLendingAnalysis.  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 GetLendingAnalysis, and pass the job identifier (JobId) from the initial call to StartLendingAnalysis.
   */
  getLendingAnalysis(params: Textract.Types.GetLendingAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.GetLendingAnalysisResponse) => void): Request<Textract.Types.GetLendingAnalysisResponse, AWSError>;
  /**
   * Gets the results for an Amazon Textract asynchronous operation that analyzes text in a lending document.  You start asynchronous text analysis by calling StartLendingAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartLendingAnalysis.  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 GetLendingAnalysis, and pass the job identifier (JobId) from the initial call to StartLendingAnalysis.
   */
  getLendingAnalysis(callback?: (err: AWSError, data: Textract.Types.GetLendingAnalysisResponse) => void): Request<Textract.Types.GetLendingAnalysisResponse, AWSError>;
  /**
   * Gets summarized results for the StartLendingAnalysis operation, which analyzes text in a lending document. The returned summary consists of information about documents grouped together by a common document type. Information like detected signatures, page numbers, and split documents is returned with respect to the type of grouped document.  You start asynchronous text analysis by calling StartLendingAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartLendingAnalysis.  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 GetLendingAnalysisSummary, and pass the job identifier (JobId) from the initial call to StartLendingAnalysis.
   */
  getLendingAnalysisSummary(params: Textract.Types.GetLendingAnalysisSummaryRequest, callback?: (err: AWSError, data: Textract.Types.GetLendingAnalysisSummaryResponse) => void): Request<Textract.Types.GetLendingAnalysisSummaryResponse, AWSError>;
  /**
   * Gets summarized results for the StartLendingAnalysis operation, which analyzes text in a lending document. The returned summary consists of information about documents grouped together by a common document type. Information like detected signatures, page numbers, and split documents is returned with respect to the type of grouped document.  You start asynchronous text analysis by calling StartLendingAnalysis, which returns a job identifier (JobId). When the text analysis operation finishes, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that's registered in the initial call to StartLendingAnalysis.  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 GetLendingAnalysisSummary, and pass the job identifier (JobId) from the initial call to StartLendingAnalysis.
   */
  getLendingAnalysisSummary(callback?: (err: AWSError, data: Textract.Types.GetLendingAnalysisSummaryResponse) => void): Request<Textract.Types.GetLendingAnalysisSummaryResponse, AWSError>;
  /**
   * Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements.  StartDocumentAnalysis 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.   StartDocumentAnalysis 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 GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis. For more information, see Document Text Analysis.
   */
  startDocumentAnalysis(params: Textract.Types.StartDocumentAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.StartDocumentAnalysisResponse) => void): Request<Textract.Types.StartDocumentAnalysisResponse, AWSError>;
  /**
   * Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements.  StartDocumentAnalysis 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.   StartDocumentAnalysis 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 GetDocumentAnalysis, and pass the job identifier (JobId) from the initial call to StartDocumentAnalysis. For more information, see Document Text Analysis.
   */
  startDocumentAnalysis(callback?: (err: AWSError, data: Textract.Types.StartDocumentAnalysisResponse) => void): Request<Textract.Types.StartDocumentAnalysisResponse, AWSError>;
  /**
   * 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.  StartDocumentTextDetection 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.   StartTextDetection returns a job identifier (JobId) that you use to get the results of the operation. When text detection 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 detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection. For more information, see Document Text Detection.
   */
  startDocumentTextDetection(params: Textract.Types.StartDocumentTextDetectionRequest, callback?: (err: AWSError, data: Textract.Types.StartDocumentTextDetectionResponse) => void): Request<Textract.Types.StartDocumentTextDetectionResponse, AWSError>;
  /**
   * 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.  StartDocumentTextDetection 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.   StartTextDetection returns a job identifier (JobId) that you use to get the results of the operation. When text detection 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 detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetDocumentTextDetection, and pass the job identifier (JobId) from the initial call to StartDocumentTextDetection. For more information, see Document Text Detection.
   */
  startDocumentTextDetection(callback?: (err: AWSError, data: Textract.Types.StartDocumentTextDetectionResponse) => void): Request<Textract.Types.StartDocumentTextDetectionResponse, AWSError>;
  /**
   * Starts the asynchronous analysis of invoices or receipts for data like contact information, items purchased, and vendor names.  StartExpenseAnalysis can analyze text in documents that are in JPEG, PNG, and PDF format. The documents must be stored in an Amazon S3 bucket. Use the DocumentLocation parameter to specify the name of your S3 bucket and the name of the document in that bucket.   StartExpenseAnalysis returns a job identifier (JobId) that you will provide to GetExpenseAnalysis to retrieve the results of the operation. When the analysis of the input invoices/receipts is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you provide to the NotificationChannel. To obtain the results of the invoice and receipt analysis operation, ensure that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetExpenseAnalysis, and pass the job identifier (JobId) that was returned by your call to StartExpenseAnalysis. For more information, see Analyzing Invoices and Receipts.
   */
  startExpenseAnalysis(params: Textract.Types.StartExpenseAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.StartExpenseAnalysisResponse) => void): Request<Textract.Types.StartExpenseAnalysisResponse, AWSError>;
  /**
   * Starts the asynchronous analysis of invoices or receipts for data like contact information, items purchased, and vendor names.  StartExpenseAnalysis can analyze text in documents that are in JPEG, PNG, and PDF format. The documents must be stored in an Amazon S3 bucket. Use the DocumentLocation parameter to specify the name of your S3 bucket and the name of the document in that bucket.   StartExpenseAnalysis returns a job identifier (JobId) that you will provide to GetExpenseAnalysis to retrieve the results of the operation. When the analysis of the input invoices/receipts is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you provide to the NotificationChannel. To obtain the results of the invoice and receipt analysis operation, ensure that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetExpenseAnalysis, and pass the job identifier (JobId) that was returned by your call to StartExpenseAnalysis. For more information, see Analyzing Invoices and Receipts.
   */
  startExpenseAnalysis(callback?: (err: AWSError, data: Textract.Types.StartExpenseAnalysisResponse) => void): Request<Textract.Types.StartExpenseAnalysisResponse, AWSError>;
  /**
   * Starts the classification and analysis of an input document. StartLendingAnalysis initiates the classification and analysis of a packet of lending documents. StartLendingAnalysis operates on a document file located in an Amazon S3 bucket.  StartLendingAnalysis can analyze text in documents that are in one of the following formats: JPEG, PNG, TIFF, PDF. Use DocumentLocation to specify the bucket name and the file name of the document.   StartLendingAnalysis returns a job identifier (JobId) that you use to get the results of the operation. When the 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 the status is SUCCEEDED you can call either GetLendingAnalysis or GetLendingAnalysisSummary and provide the JobId to obtain the results of the analysis. If using OutputConfig to specify an Amazon S3 bucket, the output will be contained within the specified prefix in a directory labeled with the job-id. In the directory there are 3 sub-directories:    detailedResponse (contains the GetLendingAnalysis response)   summaryResponse (for the GetLendingAnalysisSummary response)   splitDocuments (documents split across logical boundaries)  
   */
  startLendingAnalysis(params: Textract.Types.StartLendingAnalysisRequest, callback?: (err: AWSError, data: Textract.Types.StartLendingAnalysisResponse) => void): Request<Textract.Types.StartLendingAnalysisResponse, AWSError>;
  /**
   * Starts the classification and analysis of an input document. StartLendingAnalysis initiates the classification and analysis of a packet of lending documents. StartLendingAnalysis operates on a document file located in an Amazon S3 bucket.  StartLendingAnalysis can analyze text in documents that are in one of the following formats: JPEG, PNG, TIFF, PDF. Use DocumentLocation to specify the bucket name and the file name of the document.   StartLendingAnalysis returns a job identifier (JobId) that you use to get the results of the operation. When the 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 the status is SUCCEEDED you can call either GetLendingAnalysis or GetLendingAnalysisSummary and provide the JobId to obtain the results of the analysis. If using OutputConfig to specify an Amazon S3 bucket, the output will be contained within the specified prefix in a directory labeled with the job-id. In the directory there are 3 sub-directories:    detailedResponse (contains the GetLendingAnalysis response)   summaryResponse (for the GetLendingAnalysisSummary response)   splitDocuments (documents split across logical boundaries)  
   */
  startLendingAnalysis(callback?: (err: AWSError, data: Textract.Types.StartLendingAnalysisResponse) => void): Request<Textract.Types.StartLendingAnalysisResponse, AWSError>;
}
declare namespace Textract {
  export interface AnalyzeDocumentRequest {
    /**
     * The input document as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Textract operations, you can't pass image bytes. The document must be an image in JPEG, PNG, PDF, or TIFF format. If you're using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes that are passed using the Bytes field. 
     */
    Document: Document;
    /**
     * 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. Add SIGNATURES to return the locations of detected signatures. Add LAYOUT to the list to return information about the layout of the document. To perform both forms and table analysis, add TABLES and FORMS to FeatureTypes. To detect signatures within the document and within form data and table data, add SIGNATURES to either TABLES or FORMS. All lines and words detected in the document are included in the response (including text that isn't related to the value of FeatureTypes). 
     */
    FeatureTypes: FeatureTypes;
    /**
     * Sets the configuration for the human in the loop workflow for analyzing documents.
     */
    HumanLoopConfig?: HumanLoopConfig;
    /**
     * Contains Queries and the alias for those Queries, as determined by the input. 
     */
    QueriesConfig?: QueriesConfig;
  }
  export interface AnalyzeDocumentResponse {
    /**
     * Metadata about the analyzed document. An example is the number of pages.
     */
    DocumentMetadata?: DocumentMetadata;
    /**
     * The items that are detected and analyzed by AnalyzeDocument.
     */
    Blocks?: BlockList;
    /**
     * Shows the results of the human in the loop evaluation.
     */
    HumanLoopActivationOutput?: HumanLoopActivationOutput;
    /**
     * The version of the model used to analyze the document.
     */
    AnalyzeDocumentModelVersion?: String;
  }
  export interface AnalyzeExpenseRequest {
    Document: Document;
  }
  export interface AnalyzeExpenseResponse {
    DocumentMetadata?: DocumentMetadata;
    /**
     * The expenses detected by Amazon Textract.
     */
    ExpenseDocuments?: ExpenseDocumentList;
  }
  export interface AnalyzeIDDetections {
    /**
     * Text of either the normalized field or value associated with it.
     */
    Text: String;
    /**
     * Only returned for dates, returns the type of value detected and the date written in a more machine readable way.
     */
    NormalizedValue?: NormalizedValue;
    /**
     * The confidence score of the detected text.
     */
    Confidence?: Percent;
  }
  export interface AnalyzeIDRequest {
    /**
     * The document being passed to AnalyzeID.
     */
    DocumentPages: DocumentPages;
  }
  export interface AnalyzeIDResponse {
    /**
     * The list of documents processed by AnalyzeID. Includes a number denoting their place in the list and the response structure for the document.
     */
    IdentityDocuments?: IdentityDocumentList;
    DocumentMetadata?: DocumentMetadata;
    /**
     * The version of the AnalyzeIdentity API being used to process documents.
     */
    AnalyzeIDModelVersion?: String;
  }
  export interface Block {
    /**
     * The type of text item that's recognized. In operations for text detection, the following types are returned:    PAGE - Contains a list of the LINE Block objects that are detected on a document page.    WORD - A word detected on a document page. A word is one or more ISO basic Latin script characters that aren't separated by spaces.    LINE - A string of tab-delimited, contiguous words that are detected on a document page.   In text analysis operations, the following types are returned:    PAGE - Contains a list of child Block objects that are detected on a document page.    KEY_VALUE_SET - Stores the KEY and VALUE Block objects for linked text that's detected on a document page. Use the EntityType field to determine if a KEY_VALUE_SET object is a KEY Block object or a VALUE Block object.     WORD - A word that's detected on a document page. A word is one or more ISO basic Latin script characters that aren't separated by spaces.    LINE - A string of tab-delimited, contiguous words that are detected on a document page.    TABLE - A table that's detected on a document page. A table is grid-based information with two or more rows or columns, with a cell span of one row and one column each.     TABLE_TITLE - The title of a table. A title is typically a line of text above or below a table, or embedded as the first row of a table.     TABLE_FOOTER - The footer associated with a table. A footer is typically a line or lines of text below a table or embedded as the last row of a table.     CELL - A cell within a detected table. The cell is the parent of the block that contains the text in the cell.    MERGED_CELL - A cell in a table whose content spans more than one row or column. The Relationships array for this cell contain data from individual cells.    SELECTION_ELEMENT - A selection element such as an option button (radio button) or a check box that's detected on a document page. Use the value of SelectionStatus to determine the status of the selection element.    SIGNATURE - The location and confidence score of a signature detected on a document page. Can be returned as part of a Key-Value pair or a detected cell.    QUERY - A question asked during the call of AnalyzeDocument. Contains an alias and an ID that attaches it to its answer.    QUERY_RESULT - A response to a question asked during the call of analyze document. Comes with an alias and ID for ease of locating in a response. Also contains location and confidence score.  
     */
    BlockType?: BlockType;
    /**
     * The confidence score that Amazon Textract has in the accuracy of the recognized text and the accuracy of the geometry points around the recognized text.
     */
    Confidence?: Percent;
    /**
     * The word or line of text that's recognized by Amazon Textract. 
     */
    Text?: String;
    /**
     * The kind of text that Amazon Textract has detected. Can check for handwritten text and printed text.
     */
    TextType?: TextType;
    /**
     * The row in which a table cell is located. The first row position is 1. RowIndex isn't returned by DetectDocumentText and GetDocumentTextDetection.
     */
    RowIndex?: UInteger;
    /**
     * The column in which a table cell appears. The first column position is 1. ColumnIndex isn't returned by DetectDocumentText and GetDocumentTextDetection.
     */
    ColumnIndex?: UInteger;
    /**
     * The number of rows that a table cell spans. RowSpan isn't returned by DetectDocumentText and GetDocumentTextDetection.
     */
    RowSpan?: UInteger;
    /**
     * The number of columns that a table cell spans. ColumnSpan isn't returned by DetectDocumentText and GetDocumentTextDetection. 
     */
    ColumnSpan?: UInteger;
    /**
     * The location of the recognized text on the image. It includes an axis-aligned, coarse bounding box that surrounds the text, and a finer-grain polygon for more accurate spatial information. 
     */
    Geometry?: Geometry;
    /**
     * The identifier for the recognized text. The identifier is only unique for a single operation. 
     */
    Id?: NonEmptyString;
    /**
     * A list of relationship objects that describe how blocks are related to each other. For example, a LINE block object contains a CHILD relationship type with the WORD blocks that make up the line of text. There aren't Relationship objects in the list for relationships that don't exist, such as when the current block has no child blocks.
     */
    Relationships?: RelationshipList;
    /**
     * The type of entity.  The following entity types can be returned by FORMS analysis:    KEY - An identifier for a field on the document.    VALUE - The field text.   The following entity types can be returned by TABLES analysis:    COLUMN_HEADER - Identifies a cell that is a header of a column.     TABLE_TITLE - Identifies a cell that is a title within the table.     TABLE_SECTION_TITLE - Identifies a cell that is a title of a section within a table. A section title is a cell that typically spans an entire row above a section.     TABLE_FOOTER - Identifies a cell that is a footer of a table.     TABLE_SUMMARY - Identifies a summary cell of a table. A summary cell can be a row of a table or an additional, smaller table that contains summary information for another table.     STRUCTURED_TABLE  - Identifies a table with column headers where the content of each row corresponds to the headers.     SEMI_STRUCTURED_TABLE - Identifies a non-structured table.     EntityTypes isn't returned by DetectDocumentText and GetDocumentTextDetection.
     */
    EntityTypes?: EntityTypes;
    /**
     * The selection status of a selection element, such as an option button or check box. 
     */
    SelectionStatus?: SelectionStatus;
    /**
     * The page on which a block was detected. Page is returned by synchronous and asynchronous operations. Page values greater than 1 are only returned for multipage documents that are in PDF or TIFF format. A scanned image (JPEG/PNG) provided to an asynchronous operation, even if it contains multiple document pages, is considered a single-page document. This means that for scanned images the value of Page is always 1. 
     */
    Page?: UInteger;
    /**
     * 
     */
    Query?: Query;
  }
  export type BlockList = Block[];
  export type BlockType = "KEY_VALUE_SET"|"PAGE"|"LINE"|"WORD"|"TABLE"|"CELL"|"SELECTION_ELEMENT"|"MERGED_CELL"|"TITLE"|"QUERY"|"QUERY_RESULT"|"SIGNATURE"|"TABLE_TITLE"|"TABLE_FOOTER"|"LAYOUT_TEXT"|"LAYOUT_TITLE"|"LAYOUT_HEADER"|"LAYOUT_FOOTER"|"LAYOUT_SECTION_HEADER"|"LAYOUT_PAGE_NUMBER"|"LAYOUT_LIST"|"LAYOUT_FIGURE"|"LAYOUT_TABLE"|"LAYOUT_KEY_VALUE"|string;
  export interface BoundingBox {
    /**
     * The width of the bounding box as a ratio of the overall document page width.
     */
    Width?: Float;
    /**
     * The height of the bounding box as a ratio of the overall document page height.
     */
    Height?: Float;
    /**
     * The left coordinate of the bounding box as a ratio of overall document page width.
     */
    Left?: Float;
    /**
     * The top coordinate of the bounding box as a ratio of overall document page height.
     */
    Top?: Float;
  }
  export type ClientRequestToken = string;
  export type ContentClassifier = "FreeOfPersonallyIdentifiableInformation"|"FreeOfAdultContent"|string;
  export type ContentClassifiers = ContentClassifier[];
  export interface DetectDocumentTextRequest {
    /**
     * The input document as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Textract operations, you can't pass image bytes. The document must be an image in JPEG or PNG format. If you're using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes that are passed using the Bytes field. 
     */
    Document: Document;
  }
  export interface DetectDocumentTextResponse {
    /**
     * Metadata about the document. It contains the number of pages that are detected in the document.
     */
    DocumentMetadata?: DocumentMetadata;
    /**
     * An array of Block objects that contain the text that's detected in the document.
     */
    Blocks?: BlockList;
    /**
     * 
     */
    DetectDocumentTextModelVersion?: String;
  }
  export interface DetectedSignature {
    /**
     * The page a detected signature was found on.
     */
    Page?: UInteger;
  }
  export type DetectedSignatureList = DetectedSignature[];
  export interface Document {
    /**
     * A blob of base64-encoded document bytes. The maximum size of a document that's provided in a blob of bytes is 5 MB. The document bytes must be in PNG or JPEG format. If you're using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes passed using the Bytes field. 
     */
    Bytes?: ImageBlob;
    /**
     * Identifies an S3 object as the document source. The maximum size of a document that's stored in an S3 bucket is 5 MB.
     */
    S3Object?: S3Object;
  }
  export interface DocumentGroup {
    /**
     * The type of document that Amazon Textract has detected. See Analyze Lending Response Objects for a list of all types returned by Textract.
     */
    Type?: NonEmptyString;
    /**
     * An array that contains information about the pages of a document, defined by logical boundary.
     */
    SplitDocuments?: SplitDocumentList;
    /**
     * A list of the detected signatures found in a document group.
     */
    DetectedSignatures?: DetectedSignatureList;
    /**
     * A list of any expected signatures not found in a document group.
     */
    UndetectedSignatures?: UndetectedSignatureList;
  }
  export type DocumentGroupList = DocumentGroup[];
  export interface DocumentLocation {
    /**
     * The Amazon S3 bucket that contains the input document.
     */
    S3Object?: S3Object;
  }
  export interface DocumentMetadata {
    /**
     * The number of pages that are detected in the document.
     */
    Pages?: UInteger;
  }
  export type DocumentPages = Document[];
  export type EntityType = "KEY"|"VALUE"|"COLUMN_HEADER"|"TABLE_TITLE"|"TABLE_FOOTER"|"TABLE_SECTION_TITLE"|"TABLE_SUMMARY"|"STRUCTURED_TABLE"|"SEMI_STRUCTURED_TABLE"|string;
  export type EntityTypes = EntityType[];
  export type ErrorCode = string;
  export interface ExpenseCurrency {
    /**
     * Currency code for detected currency. the current supported codes are:   USD   EUR   GBP   CAD   INR   JPY   CHF   AUD   CNY   BZR   SEK   HKD  
     */
    Code?: String;
    /**
     * Percentage confideence in the