677 lines
48 KiB
C++
677 lines
48 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/textract/Textract_EXPORTS.h>
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#include <aws/textract/TextractErrors.h>
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#include <aws/core/client/AWSError.h>
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#include <aws/core/client/ClientConfiguration.h>
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#include <aws/core/client/AWSClient.h>
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#include <aws/core/utils/memory/stl/AWSString.h>
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#include <aws/core/utils/json/JsonSerializer.h>
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#include <aws/textract/model/AnalyzeDocumentResult.h>
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#include <aws/textract/model/DetectDocumentTextResult.h>
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#include <aws/textract/model/GetDocumentAnalysisResult.h>
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#include <aws/textract/model/GetDocumentTextDetectionResult.h>
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#include <aws/textract/model/StartDocumentAnalysisResult.h>
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#include <aws/textract/model/StartDocumentTextDetectionResult.h>
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#include <aws/core/client/AsyncCallerContext.h>
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#include <aws/core/http/HttpTypes.h>
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#include <future>
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#include <functional>
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namespace Aws
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{
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namespace Http
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{
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class HttpClient;
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class HttpClientFactory;
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} // namespace Http
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namespace Utils
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{
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template< typename R, typename E> class Outcome;
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namespace Threading
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{
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class Executor;
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} // namespace Threading
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} // namespace Utils
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namespace Auth
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{
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class AWSCredentials;
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class AWSCredentialsProvider;
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} // namespace Auth
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namespace Client
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{
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class RetryStrategy;
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} // namespace Client
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namespace Textract
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{
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namespace Model
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{
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class AnalyzeDocumentRequest;
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class DetectDocumentTextRequest;
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class GetDocumentAnalysisRequest;
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class GetDocumentTextDetectionRequest;
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class StartDocumentAnalysisRequest;
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class StartDocumentTextDetectionRequest;
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typedef Aws::Utils::Outcome<AnalyzeDocumentResult, TextractError> AnalyzeDocumentOutcome;
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typedef Aws::Utils::Outcome<DetectDocumentTextResult, TextractError> DetectDocumentTextOutcome;
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typedef Aws::Utils::Outcome<GetDocumentAnalysisResult, TextractError> GetDocumentAnalysisOutcome;
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typedef Aws::Utils::Outcome<GetDocumentTextDetectionResult, TextractError> GetDocumentTextDetectionOutcome;
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typedef Aws::Utils::Outcome<StartDocumentAnalysisResult, TextractError> StartDocumentAnalysisOutcome;
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typedef Aws::Utils::Outcome<StartDocumentTextDetectionResult, TextractError> StartDocumentTextDetectionOutcome;
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typedef std::future<AnalyzeDocumentOutcome> AnalyzeDocumentOutcomeCallable;
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typedef std::future<DetectDocumentTextOutcome> DetectDocumentTextOutcomeCallable;
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typedef std::future<GetDocumentAnalysisOutcome> GetDocumentAnalysisOutcomeCallable;
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typedef std::future<GetDocumentTextDetectionOutcome> GetDocumentTextDetectionOutcomeCallable;
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typedef std::future<StartDocumentAnalysisOutcome> StartDocumentAnalysisOutcomeCallable;
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typedef std::future<StartDocumentTextDetectionOutcome> StartDocumentTextDetectionOutcomeCallable;
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} // namespace Model
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class TextractClient;
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typedef std::function<void(const TextractClient*, const Model::AnalyzeDocumentRequest&, const Model::AnalyzeDocumentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > AnalyzeDocumentResponseReceivedHandler;
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typedef std::function<void(const TextractClient*, const Model::DetectDocumentTextRequest&, const Model::DetectDocumentTextOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectDocumentTextResponseReceivedHandler;
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typedef std::function<void(const TextractClient*, const Model::GetDocumentAnalysisRequest&, const Model::GetDocumentAnalysisOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetDocumentAnalysisResponseReceivedHandler;
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typedef std::function<void(const TextractClient*, const Model::GetDocumentTextDetectionRequest&, const Model::GetDocumentTextDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetDocumentTextDetectionResponseReceivedHandler;
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typedef std::function<void(const TextractClient*, const Model::StartDocumentAnalysisRequest&, const Model::StartDocumentAnalysisOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartDocumentAnalysisResponseReceivedHandler;
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typedef std::function<void(const TextractClient*, const Model::StartDocumentTextDetectionRequest&, const Model::StartDocumentTextDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartDocumentTextDetectionResponseReceivedHandler;
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/**
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* <p>Amazon Textract detects and analyzes text in documents and converts it into
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* machine-readable text. This is the API reference documentation for Amazon
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* Textract.</p>
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*/
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class AWS_TEXTRACT_API TextractClient : public Aws::Client::AWSJsonClient
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{
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public:
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typedef Aws::Client::AWSJsonClient BASECLASS;
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/**
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* Initializes client to use DefaultCredentialProviderChain, with default http client factory, and optional client config. If client config
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* is not specified, it will be initialized to default values.
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*/
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TextractClient(const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
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/**
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* Initializes client to use SimpleAWSCredentialsProvider, with default http client factory, and optional client config. If client config
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* is not specified, it will be initialized to default values.
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*/
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TextractClient(const Aws::Auth::AWSCredentials& credentials, const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
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/**
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* Initializes client to use specified credentials provider with specified client config. If http client factory is not supplied,
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* the default http client factory will be used
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*/
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TextractClient(const std::shared_ptr<Aws::Auth::AWSCredentialsProvider>& credentialsProvider,
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const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
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virtual ~TextractClient();
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/**
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* <p>Analyzes an input document for relationships between detected items. </p>
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* <p>The types of information returned are as follows: </p> <ul> <li> <p>Form data
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* (key-value pairs). The related information is returned in two <a>Block</a>
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* objects, each of type <code>KEY_VALUE_SET</code>: a KEY <code>Block</code>
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* object and a VALUE <code>Block</code> object. For example, <i>Name: Ana Silva
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* Carolina</i> contains a key and value. <i>Name:</i> is the key. <i>Ana Silva
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* Carolina</i> is the value.</p> </li> <li> <p>Table and table cell data. A TABLE
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* <code>Block</code> object contains information about a detected table. A CELL
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* <code>Block</code> object is returned for each cell in a table.</p> </li> <li>
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* <p>Lines and words of text. A LINE <code>Block</code> object contains one or
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* more WORD <code>Block</code> objects. All lines and words that are detected in
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* the document are returned (including text that doesn't have a relationship with
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* the value of <code>FeatureTypes</code>). </p> </li> </ul> <p>Selection elements
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* such as check boxes and option buttons (radio buttons) can be detected in form
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* data and in tables. A SELECTION_ELEMENT <code>Block</code> object contains
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* information about a selection element, including the selection status.</p>
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* <p>You can choose which type of analysis to perform by specifying the
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* <code>FeatureTypes</code> list. </p> <p>The output is returned in a list of
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* <code>Block</code> objects.</p> <p> <code>AnalyzeDocument</code> is a
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* synchronous operation. To analyze documents asynchronously, use
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* <a>StartDocumentAnalysis</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
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* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/AnalyzeDocument">AWS
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* API Reference</a></p>
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*/
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virtual Model::AnalyzeDocumentOutcome AnalyzeDocument(const Model::AnalyzeDocumentRequest& request) const;
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/**
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* <p>Analyzes an input document for relationships between detected items. </p>
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* <p>The types of information returned are as follows: </p> <ul> <li> <p>Form data
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* (key-value pairs). The related information is returned in two <a>Block</a>
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* objects, each of type <code>KEY_VALUE_SET</code>: a KEY <code>Block</code>
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* object and a VALUE <code>Block</code> object. For example, <i>Name: Ana Silva
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* Carolina</i> contains a key and value. <i>Name:</i> is the key. <i>Ana Silva
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* Carolina</i> is the value.</p> </li> <li> <p>Table and table cell data. A TABLE
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* <code>Block</code> object contains information about a detected table. A CELL
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* <code>Block</code> object is returned for each cell in a table.</p> </li> <li>
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* <p>Lines and words of text. A LINE <code>Block</code> object contains one or
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* more WORD <code>Block</code> objects. All lines and words that are detected in
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* the document are returned (including text that doesn't have a relationship with
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* the value of <code>FeatureTypes</code>). </p> </li> </ul> <p>Selection elements
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* such as check boxes and option buttons (radio buttons) can be detected in form
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* data and in tables. A SELECTION_ELEMENT <code>Block</code> object contains
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* information about a selection element, including the selection status.</p>
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* <p>You can choose which type of analysis to perform by specifying the
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* <code>FeatureTypes</code> list. </p> <p>The output is returned in a list of
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* <code>Block</code> objects.</p> <p> <code>AnalyzeDocument</code> is a
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* synchronous operation. To analyze documents asynchronously, use
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* <a>StartDocumentAnalysis</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
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* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/AnalyzeDocument">AWS
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* API Reference</a></p>
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*
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* returns a future to the operation so that it can be executed in parallel to other requests.
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*/
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virtual Model::AnalyzeDocumentOutcomeCallable AnalyzeDocumentCallable(const Model::AnalyzeDocumentRequest& request) const;
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/**
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* <p>Analyzes an input document for relationships between detected items. </p>
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* <p>The types of information returned are as follows: </p> <ul> <li> <p>Form data
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* (key-value pairs). The related information is returned in two <a>Block</a>
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* objects, each of type <code>KEY_VALUE_SET</code>: a KEY <code>Block</code>
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* object and a VALUE <code>Block</code> object. For example, <i>Name: Ana Silva
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* Carolina</i> contains a key and value. <i>Name:</i> is the key. <i>Ana Silva
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* Carolina</i> is the value.</p> </li> <li> <p>Table and table cell data. A TABLE
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* <code>Block</code> object contains information about a detected table. A CELL
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* <code>Block</code> object is returned for each cell in a table.</p> </li> <li>
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* <p>Lines and words of text. A LINE <code>Block</code> object contains one or
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* more WORD <code>Block</code> objects. All lines and words that are detected in
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* the document are returned (including text that doesn't have a relationship with
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* the value of <code>FeatureTypes</code>). </p> </li> </ul> <p>Selection elements
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* such as check boxes and option buttons (radio buttons) can be detected in form
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* data and in tables. A SELECTION_ELEMENT <code>Block</code> object contains
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* information about a selection element, including the selection status.</p>
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* <p>You can choose which type of analysis to perform by specifying the
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* <code>FeatureTypes</code> list. </p> <p>The output is returned in a list of
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* <code>Block</code> objects.</p> <p> <code>AnalyzeDocument</code> is a
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* synchronous operation. To analyze documents asynchronously, use
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* <a>StartDocumentAnalysis</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
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* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/AnalyzeDocument">AWS
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* API Reference</a></p>
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*
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* Queues the request into a thread executor and triggers associated callback when operation has finished.
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*/
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virtual void AnalyzeDocumentAsync(const Model::AnalyzeDocumentRequest& request, const AnalyzeDocumentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
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/**
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* <p>Detects text in the input document. Amazon Textract can detect lines of text
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* and the words that make up a line of text. The input document must be an image
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* in JPEG or PNG format. <code>DetectDocumentText</code> returns the detected text
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* in an array of <a>Block</a> objects. </p> <p>Each document page has as an
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* associated <code>Block</code> of type PAGE. Each PAGE <code>Block</code> object
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* is the parent of LINE <code>Block</code> objects that represent the lines of
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* detected text on a page. A LINE <code>Block</code> object is a parent for each
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* word that makes up the line. Words are represented by <code>Block</code> objects
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* of type WORD.</p> <p> <code>DetectDocumentText</code> is a synchronous
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* operation. To analyze documents asynchronously, use
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* <a>StartDocumentTextDetection</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
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* Text Detection</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/DetectDocumentText">AWS
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* API Reference</a></p>
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*/
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virtual Model::DetectDocumentTextOutcome DetectDocumentText(const Model::DetectDocumentTextRequest& request) const;
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/**
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* <p>Detects text in the input document. Amazon Textract can detect lines of text
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* and the words that make up a line of text. The input document must be an image
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* in JPEG or PNG format. <code>DetectDocumentText</code> returns the detected text
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* in an array of <a>Block</a> objects. </p> <p>Each document page has as an
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* associated <code>Block</code> of type PAGE. Each PAGE <code>Block</code> object
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* is the parent of LINE <code>Block</code> objects that represent the lines of
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* detected text on a page. A LINE <code>Block</code> object is a parent for each
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* word that makes up the line. Words are represented by <code>Block</code> objects
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* of type WORD.</p> <p> <code>DetectDocumentText</code> is a synchronous
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* operation. To analyze documents asynchronously, use
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* <a>StartDocumentTextDetection</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
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* Text Detection</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/DetectDocumentText">AWS
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* API Reference</a></p>
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*
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* returns a future to the operation so that it can be executed in parallel to other requests.
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*/
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virtual Model::DetectDocumentTextOutcomeCallable DetectDocumentTextCallable(const Model::DetectDocumentTextRequest& request) const;
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/**
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* <p>Detects text in the input document. Amazon Textract can detect lines of text
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* and the words that make up a line of text. The input document must be an image
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* in JPEG or PNG format. <code>DetectDocumentText</code> returns the detected text
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* in an array of <a>Block</a> objects. </p> <p>Each document page has as an
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* associated <code>Block</code> of type PAGE. Each PAGE <code>Block</code> object
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* is the parent of LINE <code>Block</code> objects that represent the lines of
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* detected text on a page. A LINE <code>Block</code> object is a parent for each
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* word that makes up the line. Words are represented by <code>Block</code> objects
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* of type WORD.</p> <p> <code>DetectDocumentText</code> is a synchronous
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* operation. To analyze documents asynchronously, use
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* <a>StartDocumentTextDetection</a>.</p> <p>For more information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
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* Text Detection</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/DetectDocumentText">AWS
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* API Reference</a></p>
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*
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* Queues the request into a thread executor and triggers associated callback when operation has finished.
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*/
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virtual void DetectDocumentTextAsync(const Model::DetectDocumentTextRequest& request, const DetectDocumentTextResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
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/**
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* <p>Gets the results for an Amazon Textract asynchronous operation that analyzes
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* text in a document.</p> <p>You start asynchronous text analysis by calling
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* <a>StartDocumentAnalysis</a>, which returns a job identifier
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* (<code>JobId</code>). When the text analysis operation finishes, Amazon Textract
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* publishes a completion status to the Amazon Simple Notification Service (Amazon
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* SNS) topic that's registered in the initial call to
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* <code>StartDocumentAnalysis</code>. To get the results of the text-detection
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* operation, first check that the status value published to the Amazon SNS topic
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* is <code>SUCCEEDED</code>. If so, call <code>GetDocumentAnalysis</code>, and
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* pass the job identifier (<code>JobId</code>) from the initial call to
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* <code>StartDocumentAnalysis</code>.</p> <p> <code>GetDocumentAnalysis</code>
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* returns an array of <a>Block</a> objects. The following types of information are
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* returned: </p> <ul> <li> <p>Form data (key-value pairs). The related information
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* is returned in two <a>Block</a> objects, each of type
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* <code>KEY_VALUE_SET</code>: a KEY <code>Block</code> object and a VALUE
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* <code>Block</code> object. For example, <i>Name: Ana Silva Carolina</i> contains
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* a key and value. <i>Name:</i> is the key. <i>Ana Silva Carolina</i> is the
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* value.</p> </li> <li> <p>Table and table cell data. A TABLE <code>Block</code>
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* object contains information about a detected table. A CELL <code>Block</code>
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* object is returned for each cell in a table.</p> </li> <li> <p>Lines and words
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* of text. A LINE <code>Block</code> object contains one or more WORD
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* <code>Block</code> objects. All lines and words that are detected in the
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* document are returned (including text that doesn't have a relationship with the
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* value of the <code>StartDocumentAnalysis</code> <code>FeatureTypes</code> input
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* parameter). </p> </li> </ul> <p>Selection elements such as check boxes and
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* option buttons (radio buttons) can be detected in form data and in tables. A
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* SELECTION_ELEMENT <code>Block</code> object contains information about a
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* selection element, including the selection status.</p> <p>Use the
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* <code>MaxResults</code> parameter to limit the number of blocks that are
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* returned. If there are more results than specified in <code>MaxResults</code>,
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* the value of <code>NextToken</code> in the operation response contains a
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* pagination token for getting the next set of results. To get the next page of
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* results, call <code>GetDocumentAnalysis</code>, and populate the
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* <code>NextToken</code> request parameter with the token value that's returned
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* from the previous call to <code>GetDocumentAnalysis</code>.</p> <p>For more
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* information, see <a
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* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
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* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentAnalysis">AWS
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* API Reference</a></p>
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*/
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virtual Model::GetDocumentAnalysisOutcome GetDocumentAnalysis(const Model::GetDocumentAnalysisRequest& request) const;
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/**
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* <p>Gets the results for an Amazon Textract asynchronous operation that analyzes
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* text in a document.</p> <p>You start asynchronous text analysis by calling
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* <a>StartDocumentAnalysis</a>, which returns a job identifier
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* (<code>JobId</code>). When the text analysis operation finishes, Amazon Textract
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* publishes a completion status to the Amazon Simple Notification Service (Amazon
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* SNS) topic that's registered in the initial call to
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* <code>StartDocumentAnalysis</code>. To get the results of the text-detection
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* operation, first check that the status value published to the Amazon SNS topic
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* is <code>SUCCEEDED</code>. If so, call <code>GetDocumentAnalysis</code>, and
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* pass the job identifier (<code>JobId</code>) from the initial call to
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* <code>StartDocumentAnalysis</code>.</p> <p> <code>GetDocumentAnalysis</code>
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* returns an array of <a>Block</a> objects. The following types of information are
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* returned: </p> <ul> <li> <p>Form data (key-value pairs). The related information
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* is returned in two <a>Block</a> objects, each of type
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* <code>KEY_VALUE_SET</code>: a KEY <code>Block</code> object and a VALUE
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* <code>Block</code> object. For example, <i>Name: Ana Silva Carolina</i> contains
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* a key and value. <i>Name:</i> is the key. <i>Ana Silva Carolina</i> is the
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* value.</p> </li> <li> <p>Table and table cell data. A TABLE <code>Block</code>
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* object contains information about a detected table. A CELL <code>Block</code>
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* object is returned for each cell in a table.</p> </li> <li> <p>Lines and words
|
|
* of text. A LINE <code>Block</code> object contains one or more WORD
|
|
* <code>Block</code> 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 <code>StartDocumentAnalysis</code> <code>FeatureTypes</code> input
|
|
* parameter). </p> </li> </ul> <p>Selection elements such as check boxes and
|
|
* option buttons (radio buttons) can be detected in form data and in tables. A
|
|
* SELECTION_ELEMENT <code>Block</code> object contains information about a
|
|
* selection element, including the selection status.</p> <p>Use the
|
|
* <code>MaxResults</code> parameter to limit the number of blocks that are
|
|
* returned. If there are more results than specified in <code>MaxResults</code>,
|
|
* the value of <code>NextToken</code> in the operation response contains a
|
|
* pagination token for getting the next set of results. To get the next page of
|
|
* results, call <code>GetDocumentAnalysis</code>, and populate the
|
|
* <code>NextToken</code> request parameter with the token value that's returned
|
|
* from the previous call to <code>GetDocumentAnalysis</code>.</p> <p>For more
|
|
* information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
|
|
* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentAnalysis">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* returns a future to the operation so that it can be executed in parallel to other requests.
|
|
*/
|
|
virtual Model::GetDocumentAnalysisOutcomeCallable GetDocumentAnalysisCallable(const Model::GetDocumentAnalysisRequest& request) const;
|
|
|
|
/**
|
|
* <p>Gets the results for an Amazon Textract asynchronous operation that analyzes
|
|
* text in a document.</p> <p>You start asynchronous text analysis by calling
|
|
* <a>StartDocumentAnalysis</a>, which returns a job identifier
|
|
* (<code>JobId</code>). 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
|
|
* <code>StartDocumentAnalysis</code>. To get the results of the text-detection
|
|
* operation, first check that the status value published to the Amazon SNS topic
|
|
* is <code>SUCCEEDED</code>. If so, call <code>GetDocumentAnalysis</code>, and
|
|
* pass the job identifier (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentAnalysis</code>.</p> <p> <code>GetDocumentAnalysis</code>
|
|
* returns an array of <a>Block</a> objects. The following types of information are
|
|
* returned: </p> <ul> <li> <p>Form data (key-value pairs). The related information
|
|
* is returned in two <a>Block</a> objects, each of type
|
|
* <code>KEY_VALUE_SET</code>: a KEY <code>Block</code> object and a VALUE
|
|
* <code>Block</code> object. For example, <i>Name: Ana Silva Carolina</i> contains
|
|
* a key and value. <i>Name:</i> is the key. <i>Ana Silva Carolina</i> is the
|
|
* value.</p> </li> <li> <p>Table and table cell data. A TABLE <code>Block</code>
|
|
* object contains information about a detected table. A CELL <code>Block</code>
|
|
* object is returned for each cell in a table.</p> </li> <li> <p>Lines and words
|
|
* of text. A LINE <code>Block</code> object contains one or more WORD
|
|
* <code>Block</code> 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 <code>StartDocumentAnalysis</code> <code>FeatureTypes</code> input
|
|
* parameter). </p> </li> </ul> <p>Selection elements such as check boxes and
|
|
* option buttons (radio buttons) can be detected in form data and in tables. A
|
|
* SELECTION_ELEMENT <code>Block</code> object contains information about a
|
|
* selection element, including the selection status.</p> <p>Use the
|
|
* <code>MaxResults</code> parameter to limit the number of blocks that are
|
|
* returned. If there are more results than specified in <code>MaxResults</code>,
|
|
* the value of <code>NextToken</code> in the operation response contains a
|
|
* pagination token for getting the next set of results. To get the next page of
|
|
* results, call <code>GetDocumentAnalysis</code>, and populate the
|
|
* <code>NextToken</code> request parameter with the token value that's returned
|
|
* from the previous call to <code>GetDocumentAnalysis</code>.</p> <p>For more
|
|
* information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
|
|
* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentAnalysis">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* Queues the request into a thread executor and triggers associated callback when operation has finished.
|
|
*/
|
|
virtual void GetDocumentAnalysisAsync(const Model::GetDocumentAnalysisRequest& request, const GetDocumentAnalysisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>You start asynchronous text detection by calling
|
|
* <a>StartDocumentTextDetection</a>, which returns a job identifier
|
|
* (<code>JobId</code>). 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
|
|
* <code>StartDocumentTextDetection</code>. To get the results of the
|
|
* text-detection operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <code>GetDocumentTextDetection</code>, and pass the job identifier
|
|
* (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>
|
|
* <code>GetDocumentTextDetection</code> returns an array of <a>Block</a> objects.
|
|
* </p> <p>Each document page has as an associated <code>Block</code> of type PAGE.
|
|
* Each PAGE <code>Block</code> object is the parent of LINE <code>Block</code>
|
|
* objects that represent the lines of detected text on a page. A LINE
|
|
* <code>Block</code> object is a parent for each word that makes up the line.
|
|
* Words are represented by <code>Block</code> objects of type WORD.</p> <p>Use the
|
|
* MaxResults parameter to limit the number of blocks that are returned. If there
|
|
* are more results than specified in <code>MaxResults</code>, the value of
|
|
* <code>NextToken</code> in the operation response contains a pagination token for
|
|
* getting the next set of results. To get the next page of results, call
|
|
* <code>GetDocumentTextDetection</code>, and populate the <code>NextToken</code>
|
|
* request parameter with the token value that's returned from the previous call to
|
|
* <code>GetDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentTextDetection">AWS
|
|
* API Reference</a></p>
|
|
*/
|
|
virtual Model::GetDocumentTextDetectionOutcome GetDocumentTextDetection(const Model::GetDocumentTextDetectionRequest& request) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>You start asynchronous text detection by calling
|
|
* <a>StartDocumentTextDetection</a>, which returns a job identifier
|
|
* (<code>JobId</code>). 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
|
|
* <code>StartDocumentTextDetection</code>. To get the results of the
|
|
* text-detection operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <code>GetDocumentTextDetection</code>, and pass the job identifier
|
|
* (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>
|
|
* <code>GetDocumentTextDetection</code> returns an array of <a>Block</a> objects.
|
|
* </p> <p>Each document page has as an associated <code>Block</code> of type PAGE.
|
|
* Each PAGE <code>Block</code> object is the parent of LINE <code>Block</code>
|
|
* objects that represent the lines of detected text on a page. A LINE
|
|
* <code>Block</code> object is a parent for each word that makes up the line.
|
|
* Words are represented by <code>Block</code> objects of type WORD.</p> <p>Use the
|
|
* MaxResults parameter to limit the number of blocks that are returned. If there
|
|
* are more results than specified in <code>MaxResults</code>, the value of
|
|
* <code>NextToken</code> in the operation response contains a pagination token for
|
|
* getting the next set of results. To get the next page of results, call
|
|
* <code>GetDocumentTextDetection</code>, and populate the <code>NextToken</code>
|
|
* request parameter with the token value that's returned from the previous call to
|
|
* <code>GetDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentTextDetection">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* returns a future to the operation so that it can be executed in parallel to other requests.
|
|
*/
|
|
virtual Model::GetDocumentTextDetectionOutcomeCallable GetDocumentTextDetectionCallable(const Model::GetDocumentTextDetectionRequest& request) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>You start asynchronous text detection by calling
|
|
* <a>StartDocumentTextDetection</a>, which returns a job identifier
|
|
* (<code>JobId</code>). 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
|
|
* <code>StartDocumentTextDetection</code>. To get the results of the
|
|
* text-detection operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <code>GetDocumentTextDetection</code>, and pass the job identifier
|
|
* (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>
|
|
* <code>GetDocumentTextDetection</code> returns an array of <a>Block</a> objects.
|
|
* </p> <p>Each document page has as an associated <code>Block</code> of type PAGE.
|
|
* Each PAGE <code>Block</code> object is the parent of LINE <code>Block</code>
|
|
* objects that represent the lines of detected text on a page. A LINE
|
|
* <code>Block</code> object is a parent for each word that makes up the line.
|
|
* Words are represented by <code>Block</code> objects of type WORD.</p> <p>Use the
|
|
* MaxResults parameter to limit the number of blocks that are returned. If there
|
|
* are more results than specified in <code>MaxResults</code>, the value of
|
|
* <code>NextToken</code> in the operation response contains a pagination token for
|
|
* getting the next set of results. To get the next page of results, call
|
|
* <code>GetDocumentTextDetection</code>, and populate the <code>NextToken</code>
|
|
* request parameter with the token value that's returned from the previous call to
|
|
* <code>GetDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/GetDocumentTextDetection">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* Queues the request into a thread executor and triggers associated callback when operation has finished.
|
|
*/
|
|
virtual void GetDocumentTextDetectionAsync(const Model::GetDocumentTextDetectionRequest& request, const GetDocumentTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
|
|
|
|
/**
|
|
* <p>Starts the asynchronous analysis of an input document for relationships
|
|
* between detected items such as key-value pairs, tables, and selection
|
|
* elements.</p> <p> <code>StartDocumentAnalysis</code> can analyze text in
|
|
* documents that are in JPEG, PNG, and PDF format. The documents are stored in an
|
|
* Amazon S3 bucket. Use <a>DocumentLocation</a> to specify the bucket name and
|
|
* file name of the document. </p> <p> <code>StartDocumentAnalysis</code> returns a
|
|
* job identifier (<code>JobId</code>) 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 <code>NotificationChannel</code>. To get the results of the
|
|
* text analysis operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <a>GetDocumentAnalysis</a>, and pass the job identifier (<code>JobId</code>)
|
|
* from the initial call to <code>StartDocumentAnalysis</code>.</p> <p>For more
|
|
* information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
|
|
* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentAnalysis">AWS
|
|
* API Reference</a></p>
|
|
*/
|
|
virtual Model::StartDocumentAnalysisOutcome StartDocumentAnalysis(const Model::StartDocumentAnalysisRequest& request) const;
|
|
|
|
/**
|
|
* <p>Starts the asynchronous analysis of an input document for relationships
|
|
* between detected items such as key-value pairs, tables, and selection
|
|
* elements.</p> <p> <code>StartDocumentAnalysis</code> can analyze text in
|
|
* documents that are in JPEG, PNG, and PDF format. The documents are stored in an
|
|
* Amazon S3 bucket. Use <a>DocumentLocation</a> to specify the bucket name and
|
|
* file name of the document. </p> <p> <code>StartDocumentAnalysis</code> returns a
|
|
* job identifier (<code>JobId</code>) 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 <code>NotificationChannel</code>. To get the results of the
|
|
* text analysis operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <a>GetDocumentAnalysis</a>, and pass the job identifier (<code>JobId</code>)
|
|
* from the initial call to <code>StartDocumentAnalysis</code>.</p> <p>For more
|
|
* information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
|
|
* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentAnalysis">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* returns a future to the operation so that it can be executed in parallel to other requests.
|
|
*/
|
|
virtual Model::StartDocumentAnalysisOutcomeCallable StartDocumentAnalysisCallable(const Model::StartDocumentAnalysisRequest& request) const;
|
|
|
|
/**
|
|
* <p>Starts the asynchronous analysis of an input document for relationships
|
|
* between detected items such as key-value pairs, tables, and selection
|
|
* elements.</p> <p> <code>StartDocumentAnalysis</code> can analyze text in
|
|
* documents that are in JPEG, PNG, and PDF format. The documents are stored in an
|
|
* Amazon S3 bucket. Use <a>DocumentLocation</a> to specify the bucket name and
|
|
* file name of the document. </p> <p> <code>StartDocumentAnalysis</code> returns a
|
|
* job identifier (<code>JobId</code>) 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 <code>NotificationChannel</code>. To get the results of the
|
|
* text analysis operation, first check that the status value published to the
|
|
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
|
|
* <a>GetDocumentAnalysis</a>, and pass the job identifier (<code>JobId</code>)
|
|
* from the initial call to <code>StartDocumentAnalysis</code>.</p> <p>For more
|
|
* information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document
|
|
* Text Analysis</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentAnalysis">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* Queues the request into a thread executor and triggers associated callback when operation has finished.
|
|
*/
|
|
virtual void StartDocumentAnalysisAsync(const Model::StartDocumentAnalysisRequest& request, const StartDocumentAnalysisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>
|
|
* <code>StartDocumentTextDetection</code> can analyze text in documents that are
|
|
* in JPEG, PNG, and PDF format. The documents are stored in an Amazon S3 bucket.
|
|
* Use <a>DocumentLocation</a> to specify the bucket name and file name of the
|
|
* document. </p> <p> <code>StartTextDetection</code> returns a job identifier
|
|
* (<code>JobId</code>) 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
|
|
* <code>NotificationChannel</code>. To get the results of the text detection
|
|
* operation, first check that the status value published to the Amazon SNS topic
|
|
* is <code>SUCCEEDED</code>. If so, call <a>GetDocumentTextDetection</a>, and pass
|
|
* the job identifier (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentTextDetection">AWS
|
|
* API Reference</a></p>
|
|
*/
|
|
virtual Model::StartDocumentTextDetectionOutcome StartDocumentTextDetection(const Model::StartDocumentTextDetectionRequest& request) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>
|
|
* <code>StartDocumentTextDetection</code> can analyze text in documents that are
|
|
* in JPEG, PNG, and PDF format. The documents are stored in an Amazon S3 bucket.
|
|
* Use <a>DocumentLocation</a> to specify the bucket name and file name of the
|
|
* document. </p> <p> <code>StartTextDetection</code> returns a job identifier
|
|
* (<code>JobId</code>) 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
|
|
* <code>NotificationChannel</code>. To get the results of the text detection
|
|
* operation, first check that the status value published to the Amazon SNS topic
|
|
* is <code>SUCCEEDED</code>. If so, call <a>GetDocumentTextDetection</a>, and pass
|
|
* the job identifier (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
|
|
* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentTextDetection">AWS
|
|
* API Reference</a></p>
|
|
*
|
|
* returns a future to the operation so that it can be executed in parallel to other requests.
|
|
*/
|
|
virtual Model::StartDocumentTextDetectionOutcomeCallable StartDocumentTextDetectionCallable(const Model::StartDocumentTextDetectionRequest& request) const;
|
|
|
|
/**
|
|
* <p>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.</p> <p>
|
|
* <code>StartDocumentTextDetection</code> can analyze text in documents that are
|
|
* in JPEG, PNG, and PDF format. The documents are stored in an Amazon S3 bucket.
|
|
* Use <a>DocumentLocation</a> to specify the bucket name and file name of the
|
|
* document. </p> <p> <code>StartTextDetection</code> returns a job identifier
|
|
* (<code>JobId</code>) 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
|
|
* <code>NotificationChannel</code>. To get the results of the text detection
|
|
* operation, first check that the status value published to the Amazon SNS topic
|
|
* is <code>SUCCEEDED</code>. If so, call <a>GetDocumentTextDetection</a>, and pass
|
|
* the job identifier (<code>JobId</code>) from the initial call to
|
|
* <code>StartDocumentTextDetection</code>.</p> <p>For more information, see <a
|
|
* href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-detecting.html">Document
|
|
* Text Detection</a>.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/textract-2018-06-27/StartDocumentTextDetection">AWS
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* API Reference</a></p>
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*
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* Queues the request into a thread executor and triggers associated callback when operation has finished.
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*/
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virtual void StartDocumentTextDetectionAsync(const Model::StartDocumentTextDetectionRequest& request, const StartDocumentTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
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void OverrideEndpoint(const Aws::String& endpoint);
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private:
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void init(const Aws::Client::ClientConfiguration& clientConfiguration);
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void AnalyzeDocumentAsyncHelper(const Model::AnalyzeDocumentRequest& request, const AnalyzeDocumentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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void DetectDocumentTextAsyncHelper(const Model::DetectDocumentTextRequest& request, const DetectDocumentTextResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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void GetDocumentAnalysisAsyncHelper(const Model::GetDocumentAnalysisRequest& request, const GetDocumentAnalysisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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void GetDocumentTextDetectionAsyncHelper(const Model::GetDocumentTextDetectionRequest& request, const GetDocumentTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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void StartDocumentAnalysisAsyncHelper(const Model::StartDocumentAnalysisRequest& request, const StartDocumentAnalysisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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void StartDocumentTextDetectionAsyncHelper(const Model::StartDocumentTextDetectionRequest& request, const StartDocumentTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
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Aws::String m_uri;
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Aws::String m_configScheme;
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std::shared_ptr<Aws::Utils::Threading::Executor> m_executor;
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};
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} // namespace Textract
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} // namespace Aws
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