检测图像中的文本

检测图像中的文本 (API)

1. 如果您尚未完成，请完成以下先决条件。

   1. 使用 AmazonRekognitionFullAccess 和 AmazonS3ReadOnlyAccess 权限创建或更新用户。有关更多信息，请参阅 步骤 1：设置AWS账户并创建用户。

   2. 安装和配置 AWS Command Line Interface 和 AWS SDK。有关更多信息，请参阅 第 2 步：设置 AWS CLI 以及 AWS SDKs。

2. 将包含文本的图像上传到您的 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 DetectText 操作。

   Java

   以下示例代码显示在图像中检测到的行和单词。

   将bucket和photo的值替换为您在步骤 2 中使用的 S3 存储桶和图像的名称。

   //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   package aws.example.rekognition.image;
   import com.amazonaws.services.rekognition.AmazonRekognition;
   import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
   import com.amazonaws.services.rekognition.model.AmazonRekognitionException;
   import com.amazonaws.services.rekognition.model.Image;
   import com.amazonaws.services.rekognition.model.S3Object;
   import com.amazonaws.services.rekognition.model.DetectTextRequest;
   import com.amazonaws.services.rekognition.model.DetectTextResult;
   import com.amazonaws.services.rekognition.model.TextDetection;
   import java.util.List;
   
   
   
   public class DetectText {
   
      public static void main(String[] args) throws Exception {
         
     
         String photo = "inputtext.jpg";
         String bucket = "bucket";
   
         AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
   
        
         
         DetectTextRequest request = new DetectTextRequest()
                 .withImage(new Image()
                 .withS3Object(new S3Object()
                 .withName(photo)
                 .withBucket(bucket)));
       
   
         try {
            DetectTextResult result = rekognitionClient.detectText(request);
            List<TextDetection> textDetections = result.getTextDetections();
   
            System.out.println("Detected lines and words for " + photo);
            for (TextDetection text: textDetections) {
         
                    System.out.println("Detected: " + text.getDetectedText());
                    System.out.println("Confidence: " + text.getConfidence().toString());
                    System.out.println("Id : " + text.getId());
                    System.out.println("Parent Id: " + text.getParentId());
                    System.out.println("Type: " + text.getType());
                    System.out.println();
            }
         } catch(AmazonRekognitionException e) {
            e.printStackTrace();
         }
      }
   }

   Java V2

   此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在此处查看完整示例。

   /**
   *  To run this code example, ensure that you perform the Prerequisites as stated in the Amazon Rekognition Guide:
   *  https://docs.aws.amazon.com/rekognition/latest/dg/video-analyzing-with-sqs.html
   *
   * Also, ensure that set up your development environment, including your credentials.
   *
   * For information, see this documentation topic:
   *
   * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
   */
   
   //snippet-start:[rekognition.java2.detect_text.import]
   import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
   import software.amazon.awssdk.core.SdkBytes;
   import software.amazon.awssdk.regions.Region;
   import software.amazon.awssdk.services.rekognition.RekognitionClient;
   import software.amazon.awssdk.services.rekognition.model.DetectTextRequest;
   import software.amazon.awssdk.services.rekognition.model.Image;
   import software.amazon.awssdk.services.rekognition.model.DetectTextResponse;
   import software.amazon.awssdk.services.rekognition.model.TextDetection;
   import software.amazon.awssdk.services.rekognition.model.RekognitionException;
   import java.io.FileInputStream;
   import java.io.FileNotFoundException;
   import java.io.InputStream;
   import java.util.List;
   //snippet-end:[rekognition.java2.detect_text.import]
   
   /**
   * 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 DetectTextImage {
   
    public static void main(String[] args) {
   
        final String usage = "\n" +
            "Usage: " +
            "   <sourceImage>\n\n" +
            "Where:\n" +
            "   sourceImage - The path to the image that contains text (for example, C:\\AWS\\pic1.png). \n\n";
   
      if (args.length != 1) {
            System.out.println(usage);
            System.exit(1);
        }
   
        String sourceImage = args[0] ;
        Region region = Region.US_WEST_2;
        RekognitionClient rekClient = RekognitionClient.builder()
            .region(region)
            .credentialsProvider(ProfileCredentialsProvider.create("default"))
            .build();
   
        detectTextLabels(rekClient, sourceImage );
        rekClient.close();
    }
   
    // snippet-start:[rekognition.java2.detect_text.main]
    public static void detectTextLabels(RekognitionClient rekClient, String sourceImage) {
   
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            Image souImage = Image.builder()
                .bytes(sourceBytes)
                .build();
   
            DetectTextRequest textRequest = DetectTextRequest.builder()
                .image(souImage)
                .build();
   
            DetectTextResponse textResponse = rekClient.detectText(textRequest);
            List<TextDetection> textCollection = textResponse.textDetections();
            System.out.println("Detected lines and words");
            for (TextDetection text: textCollection) {
                System.out.println("Detected: " + text.detectedText());
                System.out.println("Confidence: " + text.confidence().toString());
                System.out.println("Id : " + text.id());
                System.out.println("Parent Id: " + text.parentId());
                System.out.println("Type: " + text.type());
                System.out.println();
            }
   
        } catch (RekognitionException | FileNotFoundException e) {
            System.out.println(e.getMessage());
            System.exit(1);
        }
    }
    // snippet-end:[rekognition.java2.detect_text.main]

   AWS CLI

   此 AWS CLI 命令显示 detect-text CLI 操作的 JSON 输出。

   将Bucket和Name的值替换为您在步骤 2 中使用的 S3 存储桶和图像的名称。

   将profile_name的值替换为您的开发人员资料的名称。

   aws rekognition detect-text  --image "{"S3Object":{"Bucket":"bucket-name","Name":"image-name"}}" --profile default

   如果您在 Windows 设备上访问 CLI，请使用双引号代替单引号，并用反斜杠（即 \）对内部双引号进行转义，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 rekognition detect-text  --image "{\"S3Object\":{\"Bucket\":\"bucket-name\",\"Name\":\"image-name\"}}" --profile default

   Python

   以下示例代码显示在图像中检测到的行和单词。

   将bucket和photo的值替换为您在步骤 2 中使用的 S3 存储桶和图像的名称。将创建 Rekognition 会话的行中的profile_name值替换为您的开发人员资料的名称。

   # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   # PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   import boto3
   
   def detect_text(photo, bucket):
   
       session = boto3.Session(profile_name='default')
       client = session.client('rekognition')
   
       response = client.detect_text(Image={'S3Object': {'Bucket': bucket, 'Name': photo}})
   
       textDetections = response['TextDetections']
       print('Detected text\n----------')
       for text in textDetections:
           print('Detected text:' + text['DetectedText'])
           print('Confidence: ' + "{:.2f}".format(text['Confidence']) + "%")
           print('Id: {}'.format(text['Id']))
           if 'ParentId' in text:
               print('Parent Id: {}'.format(text['ParentId']))
           print('Type:' + text['Type'])
           print()
       return len(textDetections)
   
   def main():
       bucket = 'bucket-name'
       photo = 'photo-name'
       text_count = detect_text(photo, bucket)
       print("Text detected: " + str(text_count))
   
   if __name__ == "__main__":
       main()

   .NET

   以下示例代码显示在图像中检测到的行和单词。

   将bucket和photo的值替换为您在步骤 2 中使用的 S3 存储桶和图像的名称。

   //Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
   //PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
   
   using System;
   using Amazon.Rekognition;
   using Amazon.Rekognition.Model;
   
   public class DetectText
   {
       public static void Example()
       {
           String photo = "input.jpg";
           String bucket = "bucket";
   
           AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
   
           DetectTextRequest detectTextRequest = new DetectTextRequest()
           {
               Image = new Image()
               {
                   S3Object = new S3Object()
                   {
                       Name = photo,
                       Bucket = bucket
                   }
               }
           };
   
           try
           {
               DetectTextResponse detectTextResponse = rekognitionClient.DetectText(detectTextRequest);
               Console.WriteLine("Detected lines and words for " + photo);
               foreach (TextDetection text in detectTextResponse.TextDetections)
               {
                   Console.WriteLine("Detected: " + text.DetectedText);
                   Console.WriteLine("Confidence: " + text.Confidence);
                   Console.WriteLine("Id : " + text.Id);
                   Console.WriteLine("Parent Id: " + text.ParentId);
                   Console.WriteLine("Type: " + text.Type);
               }
           }
           catch (Exception e)
           {
               Console.WriteLine(e.Message);
           }
       }
   }

   Node.JS

   以下示例代码显示在图像中检测到的行和单词。

   将bucket和photo的值替换为您在步骤 2 中使用的 S3 存储桶和图像的名称。将region的值替换为在您的 .aws 凭证中找到的区域。将创建 Rekognition 会话的行中的profile_name值替换为您的开发人员资料的名称。

   var AWS = require('aws-sdk');
   
   const bucket = 'bucket' // the bucketname without s3://
   const photo  = 'photo' // the name of file
   
   const config = new AWS.Config({
     accessKeyId: process.env.AWS_ACCESS_KEY_ID,
     secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY,
   }) 
   AWS.config.update({region:'region'});
   const client = new AWS.Rekognition();
   const params = {
     Image: {
       S3Object: {
         Bucket: bucket,
         Name: photo
       },
     },
   }
   client.detectText(params, function(err, response) {
     if (err) {
       console.log(err, err.stack); // handle error if an error occurred
     } else {
       console.log(`Detected Text for: ${photo}`)
       console.log(response)
       response.TextDetections.forEach(label => {
         console.log(`Detected Text: ${label.DetectedText}`),
         console.log(`Type: ${label.Type}`),
         console.log(`ID: ${label.Id}`),
         console.log(`Parent ID: ${label.ParentId}`),
         console.log(`Confidence: ${label.Confidence}`),
         console.log(`Polygon: `)
         console.log(label.Geometry.Polygon)
       } 
       )
     } 
   });