

There are more AWS SDK examples available in the [AWS Doc SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) GitHub repo.

# Actions for Amazon Textract using AWS SDKs
<a name="textract_code_examples_actions"></a>

The following code examples demonstrate how to perform individual Amazon Textract actions with AWS SDKs. Each example includes a link to GitHub, where you can find instructions for setting up and running the code. 

These excerpts call the Amazon Textract API and are code excerpts from larger programs that must be run in context. You can see actions in context in [Scenarios for Amazon Textract using AWS SDKs](textract_code_examples_scenarios.md). 

 The following examples include only the most commonly used actions. For a complete list, see the [Amazon Textract API Reference](https://docs.aws.amazon.com/textract/latest/dg/API_Reference.html). 

**Topics**
+ [`AnalyzeDocument`](textract_example_textract_AnalyzeDocument_section.md)
+ [`DetectDocumentText`](textract_example_textract_DetectDocumentText_section.md)
+ [`GetDocumentAnalysis`](textract_example_textract_GetDocumentAnalysis_section.md)
+ [`StartDocumentAnalysis`](textract_example_textract_StartDocumentAnalysis_section.md)
+ [`StartDocumentTextDetection`](textract_example_textract_StartDocumentTextDetection_section.md)

# Use `AnalyzeDocument` with an AWS SDK or CLI
<a name="textract_example_textract_AnalyzeDocument_section"></a>

The following code examples show how to use `AnalyzeDocument`.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example: 
+  [Getting started with Amazon Textract](textract_example_s3_GettingStarted_074_section.md) 

------
#### [ CLI ]

**AWS CLI**  
**To analyze text in a document**  
The following `analyze-document` example shows how to analyze text in a document.  
Linux/macOS:  

```
aws textract analyze-document \
    --document '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
    --feature-types '["TABLES","FORMS"]'
```
Windows:  

```
aws textract analyze-document \
    --document "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
    --feature-types "[\"TABLES\",\"FORMS\"]" \
    --region region-name
```
Output:  

```
{
    "Blocks": [
        {
            "Geometry": {
                "BoundingBox": {
                    "Width": 1.0,
                    "Top": 0.0,
                    "Left": 0.0,
                    "Height": 1.0
                },
                "Polygon": [
                    {
                        "Y": 0.0,
                        "X": 0.0
                    },
                    {
                        "Y": 0.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 0.0
                    }
                ]
            },
            "Relationships": [
                {
                    "Type": "CHILD",
                    "Ids": [
                        "87586964-d50d-43e2-ace5-8a890657b9a0",
                        "a1e72126-21d9-44f4-a8d6-5c385f9002ba",
                        "e889d012-8a6b-4d2e-b7cd-7a8b327d876a"
                    ]
                }
            ],
            "BlockType": "PAGE",
            "Id": "c2227f12-b25d-4e1f-baea-1ee180d926b2"
        }
    ],
    "DocumentMetadata": {
        "Pages": 1
    }
}
```
For more information, see Analyzing Document Text with Amazon Textract in the *Amazon Textract Developers Guide*  
+  For API details, see [AnalyzeDocument](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/analyze-document.html) in *AWS CLI Command Reference*. 

------
#### [ Java ]

**SDK for Java 2.x**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples). 

```
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.AnalyzeDocumentRequest;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.FeatureType;
import software.amazon.awssdk.services.textract.model.AnalyzeDocumentResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.TextractException;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

/**
 * Before running this Java V2 code example, set up your development
 * environment, including your credentials.
 *
 * For more information, see the following documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */
public class AnalyzeDocument {
    public static void main(String[] args) {
        final String usage = """

                Usage:
                    <sourceDoc>\s

                Where:
                    sourceDoc - The path where the document is located (must be an image, for example, C:/AWS/book.png).\s
                """;

        if (args.length != 1) {
            System.out.println(usage);
            System.exit(1);
        }

        String sourceDoc = args[0];
        Region region = Region.US_EAST_2;
        TextractClient textractClient = TextractClient.builder()
                .region(region)
                .build();

        analyzeDoc(textractClient, sourceDoc);
        textractClient.close();
    }

    public static void analyzeDoc(TextractClient textractClient, String sourceDoc) {
        try {
            InputStream sourceStream = new FileInputStream(new File(sourceDoc));
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);

            // Get the input Document object as bytes
            Document myDoc = Document.builder()
                    .bytes(sourceBytes)
                    .build();

            List<FeatureType> featureTypes = new ArrayList<FeatureType>();
            featureTypes.add(FeatureType.FORMS);
            featureTypes.add(FeatureType.TABLES);

            AnalyzeDocumentRequest analyzeDocumentRequest = AnalyzeDocumentRequest.builder()
                    .featureTypes(featureTypes)
                    .document(myDoc)
                    .build();

            AnalyzeDocumentResponse analyzeDocument = textractClient.analyzeDocument(analyzeDocumentRequest);
            List<Block> docInfo = analyzeDocument.blocks();
            Iterator<Block> blockIterator = docInfo.iterator();

            while (blockIterator.hasNext()) {
                Block block = blockIterator.next();
                System.out.println("The block type is " + block.blockType().toString());
            }

        } catch (TextractException | FileNotFoundException e) {

            System.err.println(e.getMessage());
            System.exit(1);
        }
    }
}
```
+  For API details, see [AnalyzeDocument](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/AnalyzeDocument) in *AWS SDK for Java 2.x API Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples). 

```
class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def analyze_file(
        self, feature_types, *, document_file_name=None, document_bytes=None
    ):
        """
        Detects text and additional elements, such as forms or tables, in a local image
        file or from in-memory byte data.
        The image must be in PNG or JPG format.

        :param feature_types: The types of additional document features to detect.
        :param document_file_name: The name of a document image file.
        :param document_bytes: In-memory byte data of a document image.
        :return: The response from Amazon Textract, including a list of blocks
                 that describe elements detected in the image.
        """
        if document_file_name is not None:
            with open(document_file_name, "rb") as document_file:
                document_bytes = document_file.read()
        try:
            response = self.textract_client.analyze_document(
                Document={"Bytes": document_bytes}, FeatureTypes=feature_types
            )
            logger.info("Detected %s blocks.", len(response["Blocks"]))
        except ClientError:
            logger.exception("Couldn't detect text.")
            raise
        else:
            return response
```
+  For API details, see [AnalyzeDocument](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/AnalyzeDocument) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples). 

```
    "Detects text and additional elements, such as forms or tables,"
    "in a local image file or from in-memory byte data."
    "The image must be in PNG or JPG format."


    "Create ABAP objects for feature type."
    "Add TABLES to return information about the tables."
    "Add FORMS to return detected form data."
    "To perform both types of analysis, add TABLES and FORMS to FeatureTypes."

    DATA(lt_featuretypes) = VALUE /aws1/cl_texfeaturetypes_w=>tt_featuretypes(
      ( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'FORMS' ) )
      ( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'TABLES' ) ) ).

    "Create an ABAP object for the Amazon Simple Storage Service (Amazon S3) object."
    DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
      iv_name   = iv_s3object ).

    "Create an ABAP object for the document."
    DATA(lo_document) = NEW /aws1/cl_texdocument( io_s3object = lo_s3object ).

    "Analyze document stored in Amazon S3."
    TRY.
        oo_result = lo_tex->analyzedocument(      "oo_result is returned for testing purposes."
          io_document        = lo_document
          it_featuretypes    = lt_featuretypes ).
        LOOP AT oo_result->get_blocks( ) INTO DATA(lo_block).
          IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
            MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
          ENDIF.
        ENDLOOP.
        MESSAGE 'Analyze document completed.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texbaddocumentex.
        MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
      CATCH /aws1/cx_texdocumenttoolargeex.
        MESSAGE 'The document is too large.' TYPE 'E'.
      CATCH /aws1/cx_texhlquotaexceededex.
        MESSAGE 'Human loop quota exceeded.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.

      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
      CATCH /aws1/cx_texunsupporteddocex.
        MESSAGE 'The document is not supported.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [AnalyzeDocument](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

------

# Use `DetectDocumentText` with an AWS SDK or CLI
<a name="textract_example_textract_DetectDocumentText_section"></a>

The following code examples show how to use `DetectDocumentText`.

------
#### [ CLI ]

**AWS CLI**  
**To detect text in a document**  
The following `detect-document-text` The following example shows how to detect text in a document.  
Linux/macOS:  

```
aws textract detect-document-text \
    --document '{"S3Object":{"Bucket":"bucket","Name":"document"}}'
```
Windows:  

```
aws textract detect-document-text \
    --document "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
    --region region-name
```
Output:  

```
{
    "Blocks": [
        {
            "Geometry": {
                "BoundingBox": {
                    "Width": 1.0,
                    "Top": 0.0,
                    "Left": 0.0,
                    "Height": 1.0
                },
                "Polygon": [
                    {
                        "Y": 0.0,
                        "X": 0.0
                    },
                    {
                        "Y": 0.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 0.0
                    }
                ]
            },
            "Relationships": [
                {
                    "Type": "CHILD",
                    "Ids": [
                        "896a9f10-9e70-4412-81ce-49ead73ed881",
                        "0da18623-dc4c-463d-a3d1-9ac050e9e720",
                        "167338d7-d38c-4760-91f1-79a8ec457bb2"
                    ]
                }
            ],
            "BlockType": "PAGE",
            "Id": "21f0535e-60d5-4bc7-adf2-c05dd851fa25"
        },
        {
            "Relationships": [
                {
                    "Type": "CHILD",
                    "Ids": [
                        "62490c26-37ea-49fa-8034-7a9ff9369c9c",
                        "1e4f3f21-05bd-4da9-ba10-15d01e66604c"
                    ]
                }
            ],
            "Confidence": 89.11581420898438,
            "Geometry": {
                "BoundingBox": {
                    "Width": 0.33642634749412537,
                    "Top": 0.17169663310050964,
                    "Left": 0.13885067403316498,
                    "Height": 0.49159330129623413
                },
                "Polygon": [
                    {
                        "Y": 0.17169663310050964,
                        "X": 0.13885067403316498
                    },
                    {
                        "Y": 0.17169663310050964,
                        "X": 0.47527703642845154
                    },
                    {
                        "Y": 0.6632899641990662,
                        "X": 0.47527703642845154
                    },
                    {
                        "Y": 0.6632899641990662,
                        "X": 0.13885067403316498
                    }
                ]
            },
            "Text": "He llo,",
            "BlockType": "LINE",
            "Id": "896a9f10-9e70-4412-81ce-49ead73ed881"
        },
        {
            "Relationships": [
                {
                    "Type": "CHILD",
                    "Ids": [
                        "19b28058-9516-4352-b929-64d7cef29daf"
                    ]
                }
            ],
            "Confidence": 85.5694351196289,
            "Geometry": {
                "BoundingBox": {
                    "Width": 0.33182239532470703,
                    "Top": 0.23131252825260162,
                    "Left": 0.5091826915740967,
                    "Height": 0.3766750991344452
                },
                "Polygon": [
                    {
                        "Y": 0.23131252825260162,
                        "X": 0.5091826915740967
                    },
                    {
                        "Y": 0.23131252825260162,
                        "X": 0.8410050868988037
                    },
                    {
                        "Y": 0.607987642288208,
                        "X": 0.8410050868988037
                    },
                    {
                        "Y": 0.607987642288208,
                        "X": 0.5091826915740967
                    }
                ]
            },
            "Text": "worlc",
            "BlockType": "LINE",
            "Id": "0da18623-dc4c-463d-a3d1-9ac050e9e720"
        }
    ],
    "DocumentMetadata": {
        "Pages": 1
    }
}
```
For more information, see Detecting Document Text with Amazon Textract in the *Amazon Textract Developers Guide*  
+  For API details, see [DetectDocumentText](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/detect-document-text.html) in *AWS CLI Command Reference*. 

------
#### [ Java ]

**SDK for Java 2.x**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples). 
Detect text from an input document.  

```
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextRequest;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.DocumentMetadata;
import software.amazon.awssdk.services.textract.model.TextractException;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.List;

/**
 * Before running this Java V2 code example, set up your development
 * environment, including your credentials.
 *
 * For more information, see the following documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */
public class DetectDocumentText {
    public static void main(String[] args) {
        final String usage = """

                Usage:
                    <sourceDoc>\s

                Where:
                    sourceDoc - The path where the document is located (must be an image, for example, C:/AWS/book.png).\s
                """;

        if (args.length != 1) {
            System.out.println(usage);
            System.exit(1);
        }

        String sourceDoc = args[0];
        Region region = Region.US_EAST_2;
        TextractClient textractClient = TextractClient.builder()
                .region(region)
                .build();

        detectDocText(textractClient, sourceDoc);
        textractClient.close();
    }

    public static void detectDocText(TextractClient textractClient, String sourceDoc) {
        try {
            InputStream sourceStream = new FileInputStream(new File(sourceDoc));
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);

            // Get the input Document object as bytes.
            Document myDoc = Document.builder()
                    .bytes(sourceBytes)
                    .build();

            DetectDocumentTextRequest detectDocumentTextRequest = DetectDocumentTextRequest.builder()
                    .document(myDoc)
                    .build();

            // Invoke the Detect operation.
            DetectDocumentTextResponse textResponse = textractClient.detectDocumentText(detectDocumentTextRequest);
            List<Block> docInfo = textResponse.blocks();
            for (Block block : docInfo) {
                System.out.println("The block type is " + block.blockType().toString());
            }

            DocumentMetadata documentMetadata = textResponse.documentMetadata();
            System.out.println("The number of pages in the document is " + documentMetadata.pages());

        } catch (TextractException | FileNotFoundException e) {

            System.err.println(e.getMessage());
            System.exit(1);
        }
    }
}
```
Detect text from a document located in an Amazon S3 bucket.  

```
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.model.S3Object;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.Document;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextRequest;
import software.amazon.awssdk.services.textract.model.DetectDocumentTextResponse;
import software.amazon.awssdk.services.textract.model.Block;
import software.amazon.awssdk.services.textract.model.DocumentMetadata;
import software.amazon.awssdk.services.textract.model.TextractException;

/**
 * Before running this Java V2 code example, set up your development
 * environment, including your credentials.
 *
 * For more information, see the following documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */
public class DetectDocumentTextS3 {

    public static void main(String[] args) {
        final String usage = """

                Usage:
                    <bucketName> <docName>\s

                Where:
                    bucketName - The name of the Amazon S3 bucket that contains the document.\s

                    docName - The document name (must be an image, i.e., book.png).\s
                """;

        if (args.length != 2) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucketName = args[0];
        String docName = args[1];
        Region region = Region.US_WEST_2;
        TextractClient textractClient = TextractClient.builder()
                .region(region)
                .build();

        detectDocTextS3(textractClient, bucketName, docName);
        textractClient.close();
    }

    public static void detectDocTextS3(TextractClient textractClient, String bucketName, String docName) {
        try {
            S3Object s3Object = S3Object.builder()
                    .bucket(bucketName)
                    .name(docName)
                    .build();

            // Create a Document object and reference the s3Object instance.
            Document myDoc = Document.builder()
                    .s3Object(s3Object)
                    .build();

            DetectDocumentTextRequest detectDocumentTextRequest = DetectDocumentTextRequest.builder()
                    .document(myDoc)
                    .build();

            DetectDocumentTextResponse textResponse = textractClient.detectDocumentText(detectDocumentTextRequest);
            for (Block block : textResponse.blocks()) {
                System.out.println("The block type is " + block.blockType().toString());
            }

            DocumentMetadata documentMetadata = textResponse.documentMetadata();
            System.out.println("The number of pages in the document is " + documentMetadata.pages());

        } catch (TextractException e) {

            System.err.println(e.getMessage());
            System.exit(1);
        }
    }
}
```
+  For API details, see [DetectDocumentText](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/DetectDocumentText) in *AWS SDK for Java 2.x API Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples). 

```
class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def detect_file_text(self, *, document_file_name=None, document_bytes=None):
        """
        Detects text elements in a local image file or from in-memory byte data.
        The image must be in PNG or JPG format.

        :param document_file_name: The name of a document image file.
        :param document_bytes: In-memory byte data of a document image.
        :return: The response from Amazon Textract, including a list of blocks
                 that describe elements detected in the image.
        """
        if document_file_name is not None:
            with open(document_file_name, "rb") as document_file:
                document_bytes = document_file.read()
        try:
            response = self.textract_client.detect_document_text(
                Document={"Bytes": document_bytes}
            )
            logger.info("Detected %s blocks.", len(response["Blocks"]))
        except ClientError:
            logger.exception("Couldn't detect text.")
            raise
        else:
            return response
```
+  For API details, see [DetectDocumentText](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/DetectDocumentText) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples). 

```
    "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."

    "Create an ABAP object for the Amazon S3 object."
    DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
      iv_name   = iv_s3object ).

    "Create an ABAP object for the document."
    DATA(lo_document) = NEW /aws1/cl_texdocument( io_s3object = lo_s3object ).
    "Analyze document stored in Amazon S3."
    TRY.
        oo_result = lo_tex->detectdocumenttext( io_document = lo_document ).         "oo_result is returned for testing purposes."
        LOOP AT oo_result->get_blocks( ) INTO DATA(lo_block).
          IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
            MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
          ENDIF.
        ENDLOOP.
        DATA(lo_metadata) = oo_result->get_documentmetadata( ).
        MESSAGE 'The number of pages in the document is ' && lo_metadata->ask_pages( ) TYPE 'I'.
        MESSAGE 'Detect document text completed.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texbaddocumentex.
        MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
      CATCH /aws1/cx_texdocumenttoolargeex.
        MESSAGE 'The document is too large.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit' TYPE 'E'.
      CATCH /aws1/cx_texunsupporteddocex.
        MESSAGE 'The document is not supported.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [DetectDocumentText](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

------

# Use `GetDocumentAnalysis` with an AWS SDK or CLI
<a name="textract_example_textract_GetDocumentAnalysis_section"></a>

The following code examples show how to use `GetDocumentAnalysis`.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example: 
+  [Get started with document analysis](textract_example_textract_Scenario_GettingStarted_section.md) 

------
#### [ CLI ]

**AWS CLI**  
**To get the results of asynchronous text analysis of a multi-page document**  
The following `get-document-analysis` example shows how to get the results of asynchronous text analysis of a multi-page document.  

```
aws textract get-document-analysis \
    --job-id df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b \
    --max-results 1000
```
Output:  

```
{
    "Blocks": [
        {
            "Geometry": {
                "BoundingBox": {
                    "Width": 1.0,
                    "Top": 0.0,
                    "Left": 0.0,
                    "Height": 1.0
                },
                "Polygon": [
                    {
                        "Y": 0.0,
                        "X": 0.0
                    },
                    {
                        "Y": 0.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 1.0
                    },
                    {
                        "Y": 1.0,
                        "X": 0.0
                    }
                ]
            },
            "Relationships": [
                {
                    "Type": "CHILD",
                    "Ids": [
                        "75966e64-81c2-4540-9649-d66ec341cd8f",
                        "bb099c24-8282-464c-a179-8a9fa0a057f0",
                        "5ebf522d-f9e4-4dc7-bfae-a288dc094595"
                    ]
                }
            ],
            "BlockType": "PAGE",
            "Id": "247c28ee-b63d-4aeb-9af0-5f7ea8ba109e",
            "Page": 1
        }
    ],
    "NextToken": "cY1W3eTFvoB0cH7YrKVudI4Gb0H8J0xAYLo8xI/JunCIPWCthaKQ+07n/ElyutsSy0+1VOImoTRmP1zw4P0RFtaeV9Bzhnfedpx1YqwB4xaGDA==",
    "DocumentMetadata": {
        "Pages": 1
    },
    "JobStatus": "SUCCEEDED"
}
```
For more information, see Detecting and Analyzing Text in Multi-Page Documents in the *Amazon Textract Developers Guide*  
+  For API details, see [GetDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/get-document-analysis.html) in *AWS CLI Command Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples). 

```
class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def get_analysis_job(self, job_id):
        """
        Gets data for a previously started detection job that includes additional
        elements.

        :param job_id: The ID of the job to retrieve.
        :return: The job data, including a list of blocks that describe elements
                 detected in the image.
        """
        try:
            response = self.textract_client.get_document_analysis(JobId=job_id)
            job_status = response["JobStatus"]
            logger.info("Job %s status is %s.", job_id, job_status)
        except ClientError:
            logger.exception("Couldn't get data for job %s.", job_id)
            raise
        else:
            return response
```
+  For API details, see [GetDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/GetDocumentAnalysis) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples). 

```
    "Gets the results for an Amazon Textract"
    "asynchronous operation that analyzes text in a document."
    TRY.
        oo_result = lo_tex->getdocumentanalysis( iv_jobid = iv_jobid ).    "oo_result is returned for testing purposes."
        WHILE oo_result->get_jobstatus( ) <> 'SUCCEEDED'.
          IF sy-index = 10.
            EXIT.               "Maximum 300 seconds.
          ENDIF.
          WAIT UP TO 30 SECONDS.
          oo_result = lo_tex->getdocumentanalysis( iv_jobid = iv_jobid ).
        ENDWHILE.

        DATA(lt_blocks) = oo_result->get_blocks( ).
        LOOP AT lt_blocks INTO DATA(lo_block).
          IF lo_block->get_text( ) = 'INGREDIENTS: POWDERED SUGAR* (CANE SUGAR,'.
            MESSAGE 'Found text in the doc: ' && lo_block->get_text( ) TYPE 'I'.
          ENDIF.
        ENDLOOP.
        MESSAGE 'Document analysis retrieved.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidjobidex.
        MESSAGE 'Job ID is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidkmskeyex.
        MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [GetDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

------

# Use `StartDocumentAnalysis` with an AWS SDK or CLI
<a name="textract_example_textract_StartDocumentAnalysis_section"></a>

The following code examples show how to use `StartDocumentAnalysis`.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example: 
+  [Get started with document analysis](textract_example_textract_Scenario_GettingStarted_section.md) 

------
#### [ CLI ]

**AWS CLI**  
**To start analyzing text in a multi-page document**  
The following `start-document-analysis` example shows how to start asynchronous analysis of text in a multi-page document.  
Linux/macOS:  

```
aws textract start-document-analysis \
    --document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
    --feature-types '["TABLES","FORMS"]' \
    --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Windows:  

```
aws textract start-document-analysis \
    --document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
    --feature-types "[\"TABLES\", \"FORMS\"]" \
    --region region-name \
    --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Output:  

```
{
    "JobId": "df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b"
}
```
For more information, see Detecting and Analyzing Text in Multi-Page Documents in the *Amazon Textract Developers Guide*  
+  For API details, see [StartDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-analysis.html) in *AWS CLI Command Reference*. 

------
#### [ Java ]

**SDK for Java 2.x**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples). 

```
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.textract.model.S3Object;
import software.amazon.awssdk.services.textract.TextractClient;
import software.amazon.awssdk.services.textract.model.StartDocumentAnalysisRequest;
import software.amazon.awssdk.services.textract.model.DocumentLocation;
import software.amazon.awssdk.services.textract.model.TextractException;
import software.amazon.awssdk.services.textract.model.StartDocumentAnalysisResponse;
import software.amazon.awssdk.services.textract.model.GetDocumentAnalysisRequest;
import software.amazon.awssdk.services.textract.model.GetDocumentAnalysisResponse;
import software.amazon.awssdk.services.textract.model.FeatureType;
import java.util.ArrayList;
import java.util.List;

/**
 * Before running this Java V2 code example, set up your development
 * environment, including your credentials.
 *
 * For more information, see the following documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */
public class StartDocumentAnalysis {
    public static void main(String[] args) {
        final String usage = """

                Usage:
                    <bucketName> <docName>\s

                Where:
                    bucketName - The name of the Amazon S3 bucket that contains the document.\s
                    docName - The document name (must be an image, for example, book.png).\s
                """;

        if (args.length != 2) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucketName = args[0];
        String docName = args[1];
        Region region = Region.US_WEST_2;
        TextractClient textractClient = TextractClient.builder()
                .region(region)
                .build();

        String jobId = startDocAnalysisS3(textractClient, bucketName, docName);
        System.out.println("Getting results for job " + jobId);
        String status = getJobResults(textractClient, jobId);
        System.out.println("The job status is " + status);
        textractClient.close();
    }

    public static String startDocAnalysisS3(TextractClient textractClient, String bucketName, String docName) {
        try {
            List<FeatureType> myList = new ArrayList<>();
            myList.add(FeatureType.TABLES);
            myList.add(FeatureType.FORMS);

            S3Object s3Object = S3Object.builder()
                    .bucket(bucketName)
                    .name(docName)
                    .build();

            DocumentLocation location = DocumentLocation.builder()
                    .s3Object(s3Object)
                    .build();

            StartDocumentAnalysisRequest documentAnalysisRequest = StartDocumentAnalysisRequest.builder()
                    .documentLocation(location)
                    .featureTypes(myList)
                    .build();

            StartDocumentAnalysisResponse response = textractClient.startDocumentAnalysis(documentAnalysisRequest);

            // Get the job ID
            String jobId = response.jobId();
            return jobId;

        } catch (TextractException e) {
            System.err.println(e.getMessage());
            System.exit(1);
        }
        return "";
    }

    private static String getJobResults(TextractClient textractClient, String jobId) {
        boolean finished = false;
        int index = 0;
        String status = "";

        try {
            while (!finished) {
                GetDocumentAnalysisRequest analysisRequest = GetDocumentAnalysisRequest.builder()
                        .jobId(jobId)
                        .maxResults(1000)
                        .build();

                GetDocumentAnalysisResponse response = textractClient.getDocumentAnalysis(analysisRequest);
                status = response.jobStatus().toString();

                if (status.compareTo("SUCCEEDED") == 0)
                    finished = true;
                else {
                    System.out.println(index + " status is: " + status);
                    Thread.sleep(1000);
                }
                index++;
            }

            return status;

        } catch (InterruptedException e) {
            System.out.println(e.getMessage());
            System.exit(1);
        }
        return "";
    }
}
```
+  For API details, see [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/StartDocumentAnalysis) in *AWS SDK for Java 2.x API Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples). 
Start an asynchronous job to analyze a document.  

```
class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def start_analysis_job(
        self,
        bucket_name,
        document_file_name,
        feature_types,
        sns_topic_arn,
        sns_role_arn,
    ):
        """
        Starts an asynchronous job to detect text and additional elements, such as
        forms or tables, in an image stored in an Amazon S3 bucket. Textract publishes
        a notification to the specified Amazon SNS topic when the job completes.
        The image must be in PNG, JPG, or PDF format.

        :param bucket_name: The name of the Amazon S3 bucket that contains the image.
        :param document_file_name: The name of the document image stored in Amazon S3.
        :param feature_types: The types of additional document features to detect.
        :param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
                              where job completion notification is published.
        :param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
                             role that can be assumed by Textract and grants permission
                             to publish to the Amazon SNS topic.
        :return: The ID of the job.
        """
        try:
            response = self.textract_client.start_document_analysis(
                DocumentLocation={
                    "S3Object": {"Bucket": bucket_name, "Name": document_file_name}
                },
                NotificationChannel={
                    "SNSTopicArn": sns_topic_arn,
                    "RoleArn": sns_role_arn,
                },
                FeatureTypes=feature_types,
            )
            job_id = response["JobId"]
            logger.info(
                "Started text analysis job %s on %s.", job_id, document_file_name
            )
        except ClientError:
            logger.exception("Couldn't analyze text in %s.", document_file_name)
            raise
        else:
            return job_id
```
+  For API details, see [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentAnalysis) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples). 

```
    "Starts the asynchronous analysis of an input document for relationships"
    "between detected items such as key-value pairs, tables, and selection elements."

    "Create ABAP objects for feature type."
    "Add TABLES to return information about the tables."
    "Add FORMS to return detected form data."
    "To perform both types of analysis, add TABLES and FORMS to FeatureTypes."

    DATA(lt_featuretypes) = VALUE /aws1/cl_texfeaturetypes_w=>tt_featuretypes(
      ( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'FORMS' ) )
      ( NEW /aws1/cl_texfeaturetypes_w( iv_value = 'TABLES' ) ) ).
    "Create an ABAP object for the Amazon S3 object."
    DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
      iv_name   = iv_s3object ).
    "Create an ABAP object for the document."
    DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).

    "Start async document analysis."
    TRY.
        oo_result = lo_tex->startdocumentanalysis(      "oo_result is returned for testing purposes."
          io_documentlocation     = lo_documentlocation
          it_featuretypes         = lt_featuretypes ).
        DATA(lv_jobid) = oo_result->get_jobid( ).

        MESSAGE 'Document analysis started.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texbaddocumentex.
        MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
      CATCH /aws1/cx_texdocumenttoolargeex.
        MESSAGE 'The document is too large.' TYPE 'E'.
      CATCH /aws1/cx_texidempotentprmmis00.
        MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidkmskeyex.
        MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texlimitexceededex.
        MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
      CATCH /aws1/cx_texunsupporteddocex.
        MESSAGE 'The document is not supported.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [StartDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

------

# Use `StartDocumentTextDetection` with an AWS SDK or CLI
<a name="textract_example_textract_StartDocumentTextDetection_section"></a>

The following code examples show how to use `StartDocumentTextDetection`.

------
#### [ CLI ]

**AWS CLI**  
**To start detecting text in a multi-page document**  
The following `start-document-text-detection` example shows how to start asynchronous detection of text in a multi-page document.  
Linux/macOS:  

```
aws textract start-document-text-detection \
        --document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
        --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleARN"
```
Windows:  

```
aws textract start-document-text-detection \
    --document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
    --region region-name \
    --notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
```
Output:  

```
{
    "JobId": "57849a3dc627d4df74123dca269d69f7b89329c870c65bb16c9fd63409d200b9"
}
```
For more information, see Detecting and Analyzing Text in Multi-Page Documents in the *Amazon Textract Developers Guide*  
+  For API details, see [StartDocumentTextDetection](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-text-detection.html) in *AWS CLI Command Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples). 
Start an asynchronous job to detect text in a document.  

```
class TextractWrapper:
    """Encapsulates Textract functions."""

    def __init__(self, textract_client, s3_resource, sqs_resource):
        """
        :param textract_client: A Boto3 Textract client.
        :param s3_resource: A Boto3 Amazon S3 resource.
        :param sqs_resource: A Boto3 Amazon SQS resource.
        """
        self.textract_client = textract_client
        self.s3_resource = s3_resource
        self.sqs_resource = sqs_resource


    def start_detection_job(
        self, bucket_name, document_file_name, sns_topic_arn, sns_role_arn
    ):
        """
        Starts an asynchronous job to detect text elements in an image stored in an
        Amazon S3 bucket. Textract publishes a notification to the specified Amazon SNS
        topic when the job completes.
        The image must be in PNG, JPG, or PDF format.

        :param bucket_name: The name of the Amazon S3 bucket that contains the image.
        :param document_file_name: The name of the document image stored in Amazon S3.
        :param sns_topic_arn: The Amazon Resource Name (ARN) of an Amazon SNS topic
                              where the job completion notification is published.
        :param sns_role_arn: The ARN of an AWS Identity and Access Management (IAM)
                             role that can be assumed by Textract and grants permission
                             to publish to the Amazon SNS topic.
        :return: The ID of the job.
        """
        try:
            response = self.textract_client.start_document_text_detection(
                DocumentLocation={
                    "S3Object": {"Bucket": bucket_name, "Name": document_file_name}
                },
                NotificationChannel={
                    "SNSTopicArn": sns_topic_arn,
                    "RoleArn": sns_role_arn,
                },
            )
            job_id = response["JobId"]
            logger.info(
                "Started text detection job %s on %s.", job_id, document_file_name
            )
        except ClientError:
            logger.exception("Couldn't detect text in %s.", document_file_name)
            raise
        else:
            return job_id
```
+  For API details, see [StartDocumentTextDetection](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentTextDetection) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/tex#code-examples). 

```
    "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."

    "Create an ABAP object for the Amazon S3 object."
    DATA(lo_s3object) = NEW /aws1/cl_texs3object( iv_bucket = iv_s3bucket
      iv_name   = iv_s3object ).
    "Create an ABAP object for the document."
    DATA(lo_documentlocation) = NEW /aws1/cl_texdocumentlocation( io_s3object = lo_s3object ).
    "Start document analysis."
    TRY.
        oo_result = lo_tex->startdocumenttextdetection( io_documentlocation = lo_documentlocation ).
        DATA(lv_jobid) = oo_result->get_jobid( ).             "oo_result is returned for testing purposes."
        MESSAGE 'Document analysis started.' TYPE 'I'.
      CATCH /aws1/cx_texaccessdeniedex.
        MESSAGE 'You do not have permission to perform this action.' TYPE 'E'.
      CATCH /aws1/cx_texbaddocumentex.
        MESSAGE 'Amazon Textract is not able to read the document.' TYPE 'E'.
      CATCH /aws1/cx_texdocumenttoolargeex.
        MESSAGE 'The document is too large.' TYPE 'E'.
      CATCH /aws1/cx_texidempotentprmmis00.
        MESSAGE 'Idempotent parameter mismatch exception.' TYPE 'E'.
      CATCH /aws1/cx_texinternalservererr.
        MESSAGE 'Internal server error.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidkmskeyex.
        MESSAGE 'AWS KMS key is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texinvalidparameterex.
        MESSAGE 'Request has non-valid parameters.' TYPE 'E'.
      CATCH /aws1/cx_texinvalids3objectex.
        MESSAGE 'Amazon S3 object is not valid.' TYPE 'E'.
      CATCH /aws1/cx_texlimitexceededex.
        MESSAGE 'An Amazon Textract service limit was exceeded.' TYPE 'E'.
      CATCH /aws1/cx_texprovthruputexcdex.
        MESSAGE 'Provisioned throughput exceeded limit.' TYPE 'E'.
      CATCH /aws1/cx_texthrottlingex.
        MESSAGE 'The request processing exceeded the limit.' TYPE 'E'.
      CATCH /aws1/cx_texunsupporteddocex.
        MESSAGE 'The document is not supported.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [StartDocumentTextDetection](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

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