À utiliser DetectDocumentText avec un AWS SDK ou CLI

Les exemples de code suivants montrent comment utiliserDetectDocumentText.

CLI

AWS CLI

Pour détecter du texte dans un document

L'exemple suivant montre comment détecter du texte dans un document. detect-document-text

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 la section Détection du texte d'un document avec Amazon Textract dans le manuel Amazon Textract Developers Guide

• Pour API plus de détails, voir DetectDocumentTextla section Référence des AWS CLI commandes.

Java

SDKpour Java 2.x

Note

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.

Détecte 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:
                    <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);
        }
    }
}

Détecte 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:
                    <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);
        }
    }
}

• Pour API plus de détails, voir DetectDocumentTextla section AWS SDK for Java 2.x APIRéférence.

Python

SDKpour Python (Boto3)

Note

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.

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 API plus de détails, reportez-vous DetectDocumentTextà la section AWS SDKpour Python (Boto3) Reference. API

SAP ABAP

SDKpour SAP ABAP

Note

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.

    "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 API plus de détails, reportez-vous DetectDocumentTextà la section AWS SDKpour SAP ABAP API référence.