Amazon Textract Textract를 사용하여 문서의 비동기 분석을 시작합니다.AWSSDK

다음 코드 예제에서는 Amazon Textract Textract를 사용하여 문서의 비동기 분석을 시작하는 방법을 보여줍니다.

Java

SDK for Java 2.x

    public static String startDocAnalysisS3 (TextractClient textractClient, String bucketName, String docName) {

        try {

            List<FeatureType> myList = new ArrayList<FeatureType>();
            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 "";
    }

• GitHub에서 지침과 추가 코드를 확인해 보세요.

• API 자세한 내용은 단원을 참조하십시오.StartDocumentAnalysis에서AWS SDK for Java 2.xAPI 참조.

Python

SDK for Python(Boto3)

비동기 작업을 시작하여 문서를 분석합니다.

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

• GitHub에서 지침과 추가 코드를 확인해 보세요.

• API 자세한 내용은 단원을 참조하십시오.StartDocumentAnalysis에서AWSPython용 API 참조 SDK (Boto3).

의 전체 목록은 단원을 참조하십시오.AWSSDK 개발자 가이드 및 코드 예제는 다음을 참조하십시오.와 함께 Amazon Textract 추출을 사용하여AWSSDK. 이 항목에는 시작에 대한 정보와 이전 SDK 버전에 대한 세부 정보도 포함되어 있습니다.