使用亚马逊 Textract 分析身份证件

分析身份证件 (API)

1. 如果您尚未执行以下操作，请：

   1. 向用户提供AmazonTextractFullAccess和AmazonS3ReadOnlyAccess权限。有关更多信息，请参阅 第 1 步：设置 AWS 账户并创建用户。

   2. 安装和配置 AWS CLI 和 AWS SDK。有关更多信息，请参阅 步骤 2：设置 AWS CLI and AWS 软件开发工具包。

2. 将包含文档的图像上传到您的 S3 存储桶。

   有关说明，请参阅《Amazon Simple Storage Service 用户指南》中的将对象上传到 Amazon S3。

3. 使用以下示例调用 AnalyzeID 操作。

   AWS CLI

   以下示例从 S3 存储桶中获取输入文件并在其上运行AnalyzeID操作。在以下代码中，将的Bucket值替换为您的 S3 存储桶的名称，将的值Name替换为存储桶中文件的名称。profile-name替换为可以代入该角色的配置文件名称和region要运行代码的区域。

   aws textract analyze-id \
       --document-pages '{"S3Object":{"Bucket":"bucket","Name":"name"}}' \
       --profile profile-name \
       --region region

   您还可以通过向输入中添加另一个 Amazon S3 对象来使用驾驶执照的正面和背面调用 API。

   aws textract analyze-id \
       --document-pages '[{"S3Object":{"Bucket":"bucket","Name":"name front"}}, {"S3Object":{"Bucket":"bucket","Name":"name back"}}]' \
       --profile profile-name \
       --region region

   如果您在 Windows 设备上访问 CLI，请使用双引号而不是单引号，并使用反斜杠 (\) 转义内部双引号，以解决可能遇到的任何解析器错误。例如，请参阅以下内容：

   aws textract analyze-id --document-pages "[{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"name\"}}]" --region region

   Python

   以下示例从 S3 存储桶中获取输入文件并在其上运行AnalyzeID操作，返回检测到的键值对。在以下代码中，将的bucket_name值替换为您的 S3 存储桶的名称，将的值file_name替换为存储桶中文件的名称。profile-name替换为可以代入该角色的配置文件名称和region要运行代码的区域。

   import boto3
   
   def analyze_id(client, bucket_name, file_name):
   
       # Analyze document
       # process using S3 object
       response = client.analyze_id(
           DocumentPages=[{'S3Object': {'Bucket': bucket_name, 'Name': file_name}}])
   
       for doc_fields in response['IdentityDocuments']:
           for id_field in doc_fields['IdentityDocumentFields']:
               for key, val in id_field.items():
                   if "Type" in str(key):
                       print("Type: " + str(val['Text']))
               for key, val in id_field.items():
                   if "ValueDetection" in str(key):
                       print("Value Detection: " + str(val['Text']))
               print()
   
   def main():
       session = boto3.Session(profile_name='profile-name')
       client = session.client('textract', region_name='region')
       bucket_name = "bucket"
       file_name = "file"
   
       analyze_id(client, bucket_name, file_name)
   
   if __name__ == "__main__":
       main()
   

   Java

   以下示例从 S3 存储桶中获取输入文件并在其上运行AnalyzeID操作，返回检测到的数据。在函数 main 中，将s3bucket和sourceDoc的值替换为您在步骤 2 中使用的 Amazon S3 存储桶和文档图像的名称。将credentialsProvider的值替换为您的开发人员资料的名称。

   /*
      Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
      SPDX-License-Identifier: Apache-2.0
   */
   
   package com.amazonaws.samples;
   
   
   import com.amazonaws.auth.profile.ProfileCredentialsProvider;
   import com.amazonaws.regions.Regions;
   import com.amazonaws.services.textract.AmazonTextractClient;
   import com.amazonaws.services.textract.AmazonTextractClientBuilder;
   import com.amazonaws.services.textract.model.*;
   import java.util.ArrayList;
   import java.util.List;
   
   public class AppTest1 {
   
    public static void main(String[] args) {
   
        final String USAGE = "\n" +
                "Usage:\n" +
                "    <s3bucket><sourceDoc> \n\n" +
                "Where:\n" +
                "    s3bucket - the Amazon S3 bucket where the document is located. \n" +
                "    sourceDoc - the name of the document. \n";
   
        if (args.length != 1) {
            System.out.println(USAGE);
            System.exit(1);
        }
        
        
     // set provider credentials
        AWSCredentialsProvider credentialsProvider = new ProfileCredentialsProvider("default");
   
        String s3bucket = "bucket-name"; //args[0];
        String sourceDoc = "sourcedoc-name";  //args[1];
        AmazonTextractClient textractClient = (AmazonTextractClient) AmazonTextractClientBuilder.standard().withCredentials(credentialsProvider)
                .withRegion(Regions.US_EAST_1)
                .build();
   
        getDocDetails(textractClient, s3bucket, sourceDoc);
    }
   
    public static void getDocDetails(AmazonTextractClient textractClient, String s3bucket, String sourceDoc ) {
   
       try {
   
            S3Object s3 = new S3Object();
            s3.setBucket(s3bucket);
            s3.setName(sourceDoc);
   
            com.amazonaws.services.textract.model.Document myDoc = new com.amazonaws.services.textract.model.Document();
            myDoc.setS3Object(s3);
   
            List<Document> list1 = new ArrayList();
            list1.add(myDoc);
   
            AnalyzeIDRequest idRequest = new AnalyzeIDRequest();
            idRequest.setDocumentPages(list1);
   
            AnalyzeIDResult result = textractClient.analyzeID(idRequest);
            List<IdentityDocument> docs =  result.getIdentityDocuments();
            for (IdentityDocument doc: docs) {
   
                List<IdentityDocumentField>idFields = doc.getIdentityDocumentFields();
                for (IdentityDocumentField field: idFields) {
                    System.out.println("Field type is "+ field.getType().getText());
                    System.out.println("Field value is "+ field.getValueDetection().getText());
                }
            }
   
       } catch (Exception e) {
            e.printStackTrace();
       }
    }
   }

   Java V2

   以下示例从 S3 存储桶中获取输入文件并在其上运行AnalyzeID操作，返回检测到的数据。在函数 main 中，将s3bucket和sourceDoc的值替换为您在步骤 2 中使用的 S3 存储桶和文档图像的名称。

   profile-name在创建的行中替换为TextractClient您的开发者个人资料的名称。

   import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
   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.*;
   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;
   // snippet-end:[textract.java2._analyze_doc.import]
   import java.util.Optional;
   
   import org.json.JSONObject;
   
   /**
    * 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 DetectCelebrityVideo {
   
       public static void main(String[] args) {
   
           final String usage = "\n" +
                    "Usage:\n" +
                    "    <bucketName> <docName> \n\n" +
                    "Where:\n" +
                    "    bucketName - The name of the Amazon S3 bucket that contains the document. \n\n" +
                    "    docName - The document name (must be an image, i.e., book.png). \n";
   
           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)
                   .credentialsProvider(ProfileCredentialsProvider.create("default"))
                   .build();
   
           analyzeID(textractClient, bucketName, docName);
           textractClient.close();
       }
   
       // snippet-start:[textract.java2._analyze_doc.main]
       public static void analyzeID(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();
               
               AnalyzeIdRequest analyzeIdRequest = AnalyzeIdRequest.builder()
                       .documentPages(myDoc).build();
               
               AnalyzeIdResponse analyzeId = textractClient.analyzeID(analyzeIdRequest);
               
              // System.out.println(analyzeExpense.toString());          
               List<IdentityDocument> Docs = analyzeId.identityDocuments();
               for (IdentityDocument doc: Docs) {
                  System.out.println(doc);
               }
               
               
           } catch (TextractException e) {
   
               System.err.println(e.getMessage());
               System.exit(1);
           }
       }
       // snippet-end:[textract.java2._analyze_doc.main]
   }

4. 这将为您提供AnalyzeID操作的 JSON 输出。