# This file is auto-generated by AWSMetadata.jl
using AWS
using AWS.AWSServices: textract
using AWS.Compat
using AWS.UUIDs

"""
    AnalyzeDocument()

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).    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.

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

# Optional Parameters
- `HumanLoopConfig`: Sets the configuration for the human in the loop workflow for analyzing documents.
"""
analyze_document(Document, FeatureTypes; aws_config::AWSConfig=global_aws_config()) = textract("AnalyzeDocument", Dict{String, Any}("Document"=>Document, "FeatureTypes"=>FeatureTypes); aws_config=aws_config)
analyze_document(Document, FeatureTypes, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("AnalyzeDocument", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("Document"=>Document, "FeatureTypes"=>FeatureTypes), args)); aws_config=aws_config)

"""
    DetectDocumentText()

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 an image in JPEG or PNG format. 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.

# Required Parameters
- `Document`: 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. 

"""
detect_document_text(Document; aws_config::AWSConfig=global_aws_config()) = textract("DetectDocumentText", Dict{String, Any}("Document"=>Document); aws_config=aws_config)
detect_document_text(Document, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("DetectDocumentText", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("Document"=>Document), args)); aws_config=aws_config)

"""
    GetDocumentAnalysis()

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).    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.

# Required Parameters
- `JobId`: A unique identifier for the text-detection job. The JobId is returned from StartDocumentAnalysis. A JobId value is only valid for 7 days.

# Optional Parameters
- `MaxResults`: The maximum number of results to return per paginated call. The largest value that you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.
- `NextToken`: If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.
"""
get_document_analysis(JobId; aws_config::AWSConfig=global_aws_config()) = textract("GetDocumentAnalysis", Dict{String, Any}("JobId"=>JobId); aws_config=aws_config)
get_document_analysis(JobId, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("GetDocumentAnalysis", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("JobId"=>JobId), args)); aws_config=aws_config)

"""
    GetDocumentTextDetection()

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.

# Required Parameters
- `JobId`: A unique identifier for the text detection job. The JobId is returned from StartDocumentTextDetection. A JobId value is only valid for 7 days.

# Optional Parameters
- `MaxResults`: The maximum number of results to return per paginated call. The largest value you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.
- `NextToken`: If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.
"""
get_document_text_detection(JobId; aws_config::AWSConfig=global_aws_config()) = textract("GetDocumentTextDetection", Dict{String, Any}("JobId"=>JobId); aws_config=aws_config)
get_document_text_detection(JobId, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("GetDocumentTextDetection", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("JobId"=>JobId), args)); aws_config=aws_config)

"""
    StartDocumentAnalysis()

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, 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.

# Required Parameters
- `DocumentLocation`: The location of the document to be processed.
- `FeatureTypes`: A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to FeatureTypes. All lines and words detected in the document are included in the response (including text that isn't related to the value of FeatureTypes). 

# Optional Parameters
- `ClientRequestToken`: The idempotent token that you use to identify the start request. If you use the same token with multiple StartDocumentAnalysis requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations.
- `JobTag`: An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).
- `KMSKeyId`: The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.
- `NotificationChannel`: The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to. 
- `OutputConfig`: Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.
"""
start_document_analysis(DocumentLocation, FeatureTypes; aws_config::AWSConfig=global_aws_config()) = textract("StartDocumentAnalysis", Dict{String, Any}("DocumentLocation"=>DocumentLocation, "FeatureTypes"=>FeatureTypes); aws_config=aws_config)
start_document_analysis(DocumentLocation, FeatureTypes, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("StartDocumentAnalysis", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("DocumentLocation"=>DocumentLocation, "FeatureTypes"=>FeatureTypes), args)); aws_config=aws_config)

"""
    StartDocumentTextDetection()

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, 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.

# Required Parameters
- `DocumentLocation`: The location of the document to be processed.

# Optional Parameters
- `ClientRequestToken`: The idempotent token that's used to identify the start request. If you use the same token with multiple StartDocumentTextDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations.
- `JobTag`: An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).
- `KMSKeyId`: The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.
- `NotificationChannel`: The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to. 
- `OutputConfig`: Sets if the output will go to a customer defined bucket. By default Amazon Textract will save the results internally to be accessed with the GetDocumentTextDetection operation.
"""
start_document_text_detection(DocumentLocation; aws_config::AWSConfig=global_aws_config()) = textract("StartDocumentTextDetection", Dict{String, Any}("DocumentLocation"=>DocumentLocation); aws_config=aws_config)
start_document_text_detection(DocumentLocation, args::AbstractDict{String, <:Any}; aws_config::AWSConfig=global_aws_config()) = textract("StartDocumentTextDetection", Dict{String, Any}(mergewith(_merge, Dict{String, Any}("DocumentLocation"=>DocumentLocation), args)); aws_config=aws_config)
