D'autres exemples de AWS SDK sont disponibles dans le référentiel [AWS Doc SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) GitHub .
Les traductions sont fournies par des outils de traduction automatique. En cas de conflit entre le contenu d'une traduction et celui de la version originale en anglais, la version anglaise prévaudra.
# Exemples de base pour l'utilisation d'Amazon Textract AWS SDKs
Les exemples de code suivants montrent comment utiliser les bases d'Amazon Textract avec. AWS SDKs
**Contents**
+ [Actions](textract_code_examples_actions.md)
+ [`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)
# Actions utilisées par Amazon Textract AWS SDKs
Les exemples de code suivants montrent comment effectuer des actions Amazon Textract individuelles avec. AWS SDKs Chaque exemple inclut un lien vers GitHub, où vous pouvez trouver des instructions pour configurer et exécuter le code.
Ces extraits appellent l’API Amazon Textract et sont des extraits de code de programmes plus volumineux qui doivent être exécutés en contexte. Vous pouvez voir les actions dans leur contexte dans [Scénarios d'utilisation d'Amazon Textract AWS SDKs](textract_code_examples_scenarios.md).
Les exemples suivants incluent uniquement les actions les plus couramment utilisées. Pour obtenir la liste complète, consultez la [Référence des API Amazon Textract](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)
# Utilisation `AnalyzeDocument` avec un AWS SDK ou une CLI
Les exemples de code suivants illustrent comment utiliser `AnalyzeDocument`.
------
#### [ CLI ]
**AWS CLI**
**Pour analyser le texte d’un document**
L’exemple `analyze-document` suivant montre comment analyser le texte d’un 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
```
Sortie :
```
{
"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
}
}
```
Pour plus d’informations, consultez Analyzing Document Text with Amazon Textract dans le *Guide du développeur Amazon Textract*.
+ Pour plus de détails sur l'API, reportez-vous [AnalyzeDocument](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/analyze-document.html)à la section *Référence des AWS CLI commandes*.
------
#### [ Java ]
**SDK pour Java 2.x**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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:
\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 featureTypes = new ArrayList();
featureTypes.add(FeatureType.FORMS);
featureTypes.add(FeatureType.TABLES);
AnalyzeDocumentRequest analyzeDocumentRequest = AnalyzeDocumentRequest.builder()
.featureTypes(featureTypes)
.document(myDoc)
.build();
AnalyzeDocumentResponse analyzeDocument = textractClient.analyzeDocument(analyzeDocumentRequest);
List docInfo = analyzeDocument.blocks();
Iterator 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);
}
}
}
```
+ Pour plus de détails sur l'API, voir [AnalyzeDocument](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/AnalyzeDocument)la section *Référence des AWS SDK for Java 2.x API*.
------
#### [ Python ]
**Kit SDK for Python (Boto3)**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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
```
+ Pour plus de détails sur l'API, consultez [AnalyzeDocument](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/AnalyzeDocument)le *AWS manuel de référence de l'API SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**Kit SDK pour SAP ABAP**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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.
```
+ Pour plus de détails sur l'API, consultez [AnalyzeDocument](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la section de référence du *AWS SDK pour l'API SAP ABAP*.
------
# Utilisation `DetectDocumentText` avec un AWS SDK ou une CLI
Les exemples de code suivants illustrent comment utiliser `DetectDocumentText`.
------
#### [ CLI ]
**AWS CLI**
**Pour détecter du texte dans un document**
L’exemple `detect-document-text` suivant montre comment détecter du texte dans un 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
```
Sortie :
```
{
"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
}
}
```
Pour plus d’informations, consultez Detecting Document Text with Amazon Textract dans le *Guide du développeur Amazon Textract*.
+ Pour plus de détails sur l'API, reportez-vous [DetectDocumentText](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/detect-document-text.html)à la section *Référence des AWS CLI commandes*.
------
#### [ Java ]
**SDK pour Java 2.x**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/textract#code-examples).
Détectez le texte d’un document d’entrée.
```
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:
\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 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);
}
}
}
```
Détectez le texte d’un document situé dans un compartiment Amazon S3.
```
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:
\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);
}
}
}
```
+ Pour plus de détails sur l'API, voir [DetectDocumentText](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/DetectDocumentText)la section *Référence des AWS SDK for Java 2.x API*.
------
#### [ Python ]
**Kit SDK for Python (Boto3)**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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
```
+ Pour plus de détails sur l'API, consultez [DetectDocumentText](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/DetectDocumentText)le *AWS manuel de référence de l'API SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**Kit SDK pour SAP ABAP**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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.
```
+ Pour plus de détails sur l'API, consultez [DetectDocumentText](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la section de référence du *AWS SDK pour l'API SAP ABAP*.
------
# Utilisation `GetDocumentAnalysis` avec un AWS SDK ou une CLI
Les exemples de code suivants illustrent comment utiliser `GetDocumentAnalysis`.
Les exemples d’actions sont des extraits de code de programmes de plus grande envergure et doivent être exécutés en contexte. Vous pouvez voir cette action en contexte dans l’exemple de code suivant :
+ [Premiers pas avec l’analyse de documents](textract_example_textract_Scenario_GettingStarted_section.md)
------
#### [ CLI ]
**AWS CLI**
**Pour obtenir les résultats de l’analyse de texte asynchrone d’un document de plusieurs pages**
L’exemple `get-document-analysis` suivant montre comment obtenir les résultats de l’analyse de texte asynchrone d’un document de plusieurs pages.
```
aws textract get-document-analysis \
--job-id df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b \
--max-results 1000
```
Sortie :
```
{
"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"
}
```
Pour plus d’informations, consultez Détection et analyse de texte dans des documents de plusieurs pages dans le *Guide du développeur Amazon Textract*.
+ Pour plus de détails sur l'API, reportez-vous [GetDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/get-document-analysis.html)à la section *Référence des AWS CLI commandes*.
------
#### [ Python ]
**Kit SDK for Python (Boto3)**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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
```
+ Pour plus de détails sur l'API, consultez [GetDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/GetDocumentAnalysis)le *AWS manuel de référence de l'API SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**Kit SDK pour SAP ABAP**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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.
```
+ Pour plus de détails sur l'API, consultez [GetDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la section de référence du *AWS SDK pour l'API SAP ABAP*.
------
# Utilisation `StartDocumentAnalysis` avec un AWS SDK ou une CLI
Les exemples de code suivants illustrent comment utiliser `StartDocumentAnalysis`.
Les exemples d’actions sont des extraits de code de programmes de plus grande envergure et doivent être exécutés en contexte. Vous pouvez voir cette action en contexte dans l’exemple de code suivant :
+ [Premiers pas avec l’analyse de documents](textract_example_textract_Scenario_GettingStarted_section.md)
------
#### [ CLI ]
**AWS CLI**
**Pour commencer à analyser le texte d’un document de plusieurs pages**
L’exemple `start-document-analysis` suivant montre comment lancer une analyse de texte asynchrone dans un document de plusieurs pages.
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"
```
Sortie :
```
{
"JobId": "df7cf32ebbd2a5de113535fcf4d921926a701b09b4e7d089f3aebadb41e0712b"
}
```
Pour plus d’informations, consultez Détection et analyse de texte dans des documents de plusieurs pages dans le *Guide du développeur Amazon Textract*.
+ Pour plus de détails sur l'API, reportez-vous [StartDocumentAnalysis](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-analysis.html)à la section *Référence des AWS CLI commandes*.
------
#### [ Java ]
**SDK pour Java 2.x**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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:
\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 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 "";
}
}
```
+ Pour plus de détails sur l'API, voir [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/SdkForJavaV2/textract-2018-06-27/StartDocumentAnalysis)la section *Référence des AWS SDK for Java 2.x API*.
------
#### [ Python ]
**Kit SDK for Python (Boto3)**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
Lancez une tâche asynchrone pour analyser un 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
```
+ Pour plus de détails sur l'API, consultez [StartDocumentAnalysis](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentAnalysis)le *AWS manuel de référence de l'API SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**Kit SDK pour SAP ABAP**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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.
```
+ Pour plus de détails sur l'API, consultez [StartDocumentAnalysis](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la section de référence du *AWS SDK pour l'API SAP ABAP*.
------
# Utilisation `StartDocumentTextDetection` avec un AWS SDK ou une CLI
Les exemples de code suivants illustrent comment utiliser `StartDocumentTextDetection`.
------
#### [ CLI ]
**AWS CLI**
**Pour commencer à détecter du texte dans un document de plusieurs pages**
L’exemple `start-document-text-detection` suivant montre comment lancer une détection de texte asynchrone dans un document de plusieurs pages.
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"
```
Sortie :
```
{
"JobId": "57849a3dc627d4df74123dca269d69f7b89329c870c65bb16c9fd63409d200b9"
}
```
Pour plus d’informations, consultez Détection et analyse de texte dans des documents de plusieurs pages dans le *Guide du développeur Amazon Textract*.
+ Pour plus de détails sur l'API, reportez-vous [StartDocumentTextDetection](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/textract/start-document-text-detection.html)à la section *Référence des AWS CLI commandes*.
------
#### [ Python ]
**Kit SDK for Python (Boto3)**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/textract#code-examples).
Démarrez une tâche asynchrone pour détecter du texte dans un 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
```
+ Pour plus de détails sur l'API, consultez [StartDocumentTextDetection](https://docs.aws.amazon.com/goto/boto3/textract-2018-06-27/StartDocumentTextDetection)le *AWS manuel de référence de l'API SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**Kit SDK pour SAP ABAP**
Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](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.
```
+ Pour plus de détails sur l'API, consultez [StartDocumentTextDetection](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la section de référence du *AWS SDK pour l'API SAP ABAP*.
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