在映像中偵測文字

若要偵測映像中的文字 (API)

1. 如果您尚未完成，請先完成事前準備：

   1. 建立或更新具有 AmazonRekognitionFullAccess 和 AmazonS3ReadOnlyAccess 許可的使用者。如需詳細資訊，請參閱 步驟 1：設定AWS帳戶並建立使用者。

   2. 安裝和設定 AWS Command Line Interface AWS 軟體開發套件。如需詳細資訊，請參閱 步驟 2：設定 AWS CLI 以及 AWS SDKs。

2. 上傳包含文字的映像到您的 S3 儲存貯體。

   如需指示說明，請參閱《Amazon Simple Storage Service 使用者指南》中的上傳物件至 Amazon S3。

3. 使用下列範例來呼叫 DetectText 操作。

   Java

   以下範例程式碼會顯示在映像中偵測到的行和文字。

   將 bucket 與 photo 的數值取代為您在步驟 2 中所使用的 S3 儲存貯體名稱與映像名稱。

   //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

   此代碼取自 AWS 文檔 SDK 示例 GitHub 存儲庫。請參閱此處的完整範例。

   /**
   *  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 命令會顯示 detect-text CLI 作業的 JSON 輸出。

   將 Bucket 與 Name 的數值取代為您在步驟 2 中所使用的 S3 儲存貯體名稱與映像名稱。

   使用您開發人員設定檔的名稱取代 profile_name 的值。

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

   如果您在 Windows 裝置上存取 CLI，請使用雙引號而非單引號，並以反斜線 (即\) 替代內部雙引號，以解決您可能遇到的任何剖析器錯誤。例如，請參閱下列內容：

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

   Python

   以下範例程式碼會顯示在映像中偵測到的行和文字。

   將 bucket 與 photo 的數值取代為您在步驟 2 中所使用的 S3 儲存貯體名稱與映像名稱。將建立 Rekognition 工作階段的行中 profile_name 值取代為您開發人員設定檔的名稱。

   # 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

   以下範例程式碼會顯示在映像中偵測到的行和文字。

   將 bucket 與 photo 的數值取代為您在步驟 2 中所使用的 S3 儲存貯體名稱與映像名稱。

   //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

   以下範例程式碼會顯示在映像中偵測到的行和文字。

   將 bucket 與 photo 的數值取代為您在步驟 2 中所使用的 S3 儲存貯體名稱與映像名稱。將 region 的值取代為 .aws 憑證中找到的區域。將建立 Rekognition 工作階段的行中 profile_name 值取代為您開發人員設定檔的名稱。

   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)
       } 
       )
     } 
   });