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# Menganalisis citra yang dimuat dari sistem file lokal
<a name="images-bytes"></a>

Operasi Amazon Rekognition Image dapat menganalisis citra yang disediakan sebagai bit citra atau citra yang disimpan dalam bucket Amazon S3.

Topik ini memberikan contoh menyediakan bit citra untuk operasi API Amazon Rekognition Image dengan menggunakan file yang dimuat dari sistem file lokal. Anda meneruskan byte gambar ke operasi Amazon Rekognition API dengan [menggunakan](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_Image.html) parameter input Image. Dalam `Image`, Anda menentukan properti `Bytes` untuk meneruskan bit citra yang dikodekan base64.

Bit citra diteruskan ke operasi API Amazon Rekognition dengan menggunakan parameter input `Bytes` yang harus dikodekan ke base64. AWS SDKs yang digunakan contoh ini secara otomatis mengkodekan gambar base64. Anda tidak perlu mengodekan bit citra sebelum memanggil operasi API Amazon Rekognition. Untuk informasi selengkapnya, lihat [Spesifikasi citra](images-information.md). 

Dalam contoh permintaan JSON ini untuk `DetectLabels`, bit citra sumber diteruskan dalam parameter input `Bytes`. 

```
{
    "Image": {
        "Bytes": "/9j/4AAQSk....."
    },
    "MaxLabels": 10,
    "MinConfidence": 77
}
```

Contoh berikut menggunakan berbagai AWS SDKs dan AWS CLI untuk memanggil`DetectLabels`. Untuk informasi tentang respons operasi `DetectLabels`, lihat [DetectLabels respon](labels-detect-labels-image.md#detectlabels-response).

Untuk JavaScript contoh sisi klien, lihat. [Menggunakan JavaScript](image-bytes-javascript.md)

**Untuk mendeteksi label dalam citra lokal**

1. Jika belum:

   1. Buat atau perbarui pengguna dengan `AmazonRekognitionFullAccess` dan `AmazonS3ReadOnlyAccess` izin. Untuk informasi selengkapnya, lihat [Langkah 1: Siapkan akun AWS dan buat Pengguna](setting-up.md#setting-up-iam).

   1. Instal dan konfigurasikan AWS CLI dan AWS SDKs. Untuk informasi selengkapnya, lihat [Langkah 2: Mengatur AWS CLI dan AWS SDKs](setup-awscli-sdk.md).

1. Gunakan contoh berikut untuk memanggil operasi `DetectLabels`.

------
#### [ Java ]

   Contoh Java berikut menunjukkan cara memuat citra dari sistem file lokal dan mendeteksi label dengan menggunakan operasi AWS SDK [detectLabels](https://sdk.amazonaws.com/java/api/latest/software/amazon/awssdk/services/rekognition/model/DetectLabelsRequest.html). Ubah nilai `photo` ke nama jalur dan file dari file citra (format .jpg atau .png).

   ```
   //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 java.io.File;
   import java.io.FileInputStream;
   import java.io.InputStream;
   import java.nio.ByteBuffer;
   import java.util.List;
   import com.amazonaws.services.rekognition.AmazonRekognition;
   import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
   import com.amazonaws.AmazonClientException;
   import com.amazonaws.services.rekognition.model.AmazonRekognitionException;
   import com.amazonaws.services.rekognition.model.DetectLabelsRequest;
   import com.amazonaws.services.rekognition.model.DetectLabelsResult;
   import com.amazonaws.services.rekognition.model.Image;
   import com.amazonaws.services.rekognition.model.Label;
   import com.amazonaws.util.IOUtils;
   
   public class DetectLabelsLocalFile {
       public static void main(String[] args) throws Exception {
       	String photo="input.jpg";
   
   
           ByteBuffer imageBytes;
           try (InputStream inputStream = new FileInputStream(new File(photo))) {
               imageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream));
           }
   
   
           AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
   
           DetectLabelsRequest request = new DetectLabelsRequest()
                   .withImage(new Image()
                           .withBytes(imageBytes))
                   .withMaxLabels(10)
                   .withMinConfidence(77F);
   
           try {
   
               DetectLabelsResult result = rekognitionClient.detectLabels(request);
               List <Label> labels = result.getLabels();
   
               System.out.println("Detected labels for " + photo);
               for (Label label: labels) {
                  System.out.println(label.getName() + ": " + label.getConfidence().toString());
               }
   
           } catch (AmazonRekognitionException e) {
               e.printStackTrace();
           }
   
       }
   }
   ```

------
#### [ Python ]

   Contoh [AWS SDK for Python](https://aws.amazon.com/sdk-for-python/) berikut menunjukkan cara untuk memuat citra dari sistem file lokal dan memanggil operasi [detect\$1labels](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/rekognition.html#Rekognition.Client.detect_labels). Ubah nilai `photo` ke nama jalur dan file dari file citra (format .jpg atau .png). 

   ```
   #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_labels_local_file(photo):
   
   
       client=boto3.client('rekognition')
      
       with open(photo, 'rb') as image:
           response = client.detect_labels(Image={'Bytes': image.read()})
           
       print('Detected labels in ' + photo)    
       for label in response['Labels']:
           print (label['Name'] + ' : ' + str(label['Confidence']))
   
       return len(response['Labels'])
   
   def main():
       photo='photo'
   
       label_count=detect_labels_local_file(photo)
       print("Labels detected: " + str(label_count))
   
   
   if __name__ == "__main__":
       main()
   ```

------
#### [ .NET ]

   Contoh berikut menunjukkan cara untuk memuat citra dari sistem file lokal dan mendeteksi label dengan menggunakan operasi `DetectLabels`. Ubah nilai `photo` ke nama jalur dan file dari file citra (format .jpg atau .png).

   ```
   //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 System.IO;
   using Amazon.Rekognition;
   using Amazon.Rekognition.Model;
   
   public class DetectLabelsLocalfile
   {
       public static void Example()
       {
           String photo = "input.jpg";
   
           Amazon.Rekognition.Model.Image image = new Amazon.Rekognition.Model.Image();
           try
           {
               using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read))
               {
                   byte[] data = null;
                   data = new byte[fs.Length];
                   fs.Read(data, 0, (int)fs.Length);
                   image.Bytes = new MemoryStream(data);
               }
           }
           catch (Exception)
           {
               Console.WriteLine("Failed to load file " + photo);
               return;
           }
   
           AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
   
           DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest()
           {
               Image = image,
               MaxLabels = 10,
               MinConfidence = 77F
           };
   
           try
           {
               DetectLabelsResponse detectLabelsResponse = rekognitionClient.DetectLabels(detectlabelsRequest);
               Console.WriteLine("Detected labels for " + photo);
               foreach (Label label in detectLabelsResponse.Labels)
                   Console.WriteLine("{0}: {1}", label.Name, label.Confidence);
           }
           catch (Exception e)
           {
               Console.WriteLine(e.Message);
           }
       }
   }
   ```

------
#### [ PHP ]

   Contoh [AWS SDK for](https://docs.aws.amazon.com/sdk-for-php/v3/developer-guide/welcome.html#getting-started) PHP berikut menunjukkan cara memuat gambar dari sistem file lokal dan memanggil operasi [DetectFaces](https://docs.aws.amazon.com/aws-sdk-php/v3/api/api-rekognition-2016-06-27.html#detectfaces)API. Ubah nilai `photo` ke nama jalur dan file dari file citra (format .jpg atau .png). 

   ```
   
   <?php
   //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.)
   
       require 'vendor/autoload.php';
   
       use Aws\Rekognition\RekognitionClient;
   
       $options = [
          'region'            => 'us-west-2',
           'version'           => 'latest'
       ];
   
       $rekognition = new RekognitionClient($options);
   	
       // Get local image
       $photo = 'input.jpg';
       $fp_image = fopen($photo, 'r');
       $image = fread($fp_image, filesize($photo));
       fclose($fp_image);
   
   
       // Call DetectFaces
       $result = $rekognition->DetectFaces(array(
          'Image' => array(
             'Bytes' => $image,
          ),
          'Attributes' => array('ALL')
          )
       );
   
       // Display info for each detected person
       print 'People: Image position and estimated age' . PHP_EOL;
       for ($n=0;$n<sizeof($result['FaceDetails']); $n++){
   
         print 'Position: ' . $result['FaceDetails'][$n]['BoundingBox']['Left'] . " "
         . $result['FaceDetails'][$n]['BoundingBox']['Top']
         . PHP_EOL
         . 'Age (low): '.$result['FaceDetails'][$n]['AgeRange']['Low']
         .  PHP_EOL
         . 'Age (high): ' . $result['FaceDetails'][$n]['AgeRange']['High']
         .  PHP_EOL . PHP_EOL;
       }
   ?>
   ```

------
#### [ Ruby ]

   Contoh ini menampilkan daftar label yang terdeteksi pada citra input. Ubah nilai `photo` ke nama jalur dan file dari file citra (format .jpg atau .png).

   ```
   #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.)
   
       # gem 'aws-sdk-rekognition'
       require 'aws-sdk-rekognition'
       credentials = Aws::Credentials.new(
          ENV['AWS_ACCESS_KEY_ID'],
          ENV['AWS_SECRET_ACCESS_KEY']
       )
       client   = Aws::Rekognition::Client.new credentials: credentials
       photo = 'photo.jpg'
       path = File.expand_path(photo) # expand path relative to the current directory
       file = File.read(path)
       attrs = {
         image: {
           bytes: file
         },
         max_labels: 10
       }
       response = client.detect_labels attrs
       puts "Detected labels for: #{photo}"
       response.labels.each do |label|
         puts "Label:      #{label.name}"
         puts "Confidence: #{label.confidence}"
         puts "Instances:"
         label['instances'].each do |instance|
           box = instance['bounding_box']
           puts "  Bounding box:"
           puts "    Top:        #{box.top}"
           puts "    Left:       #{box.left}"
           puts "    Width:      #{box.width}"
           puts "    Height:     #{box.height}"
           puts "  Confidence: #{instance.confidence}"
         end
         puts "Parents:"
         label.parents.each do |parent|
           puts "  #{parent.name}"
         end
         puts "------------"
         puts ""
       end
   ```

------
#### [ Java V2 ]

   Kode ini diambil dari GitHub repositori contoh SDK AWS Dokumentasi. Lihat contoh lengkapnya [di sini](https://github.com/awsdocs/aws-doc-sdk-examples/blob/master/javav2/example_code/rekognition/src/main/java/com/example/rekognition/DetectLabels.java).

   ```
   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.*;
   
   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 DetectLabels {
       public static void main(String[] args) {
           final String usage = """
               Usage: <bucketName> <sourceImage>
   
               Where:
                   bucketName - The name of the Amazon S3 bucket where the image is stored
                   sourceImage - The name of the image file (for example, pic1.png).\s
               """;
   
           if (args.length != 2) {
               System.out.println(usage);
               System.exit(1);
           }
   
           String bucketName = args[0] ;
           String sourceImage = args[1] ;
           Region region = Region.US_WEST_2;
           RekognitionClient rekClient = RekognitionClient.builder()
                   .region(region)
                   .build();
   
           detectImageLabels(rekClient, bucketName, sourceImage);
           rekClient.close();
       }
   
       /**
        * Detects the labels in an image stored in an Amazon S3 bucket using the Amazon Rekognition service.
        *
        * @param rekClient     the Amazon Rekognition client used to make the detection request
        * @param bucketName    the name of the Amazon S3 bucket where the image is stored
        * @param sourceImage   the name of the image file to be analyzed
        */
       public static void detectImageLabels(RekognitionClient rekClient, String bucketName, String sourceImage) {
           try {
               S3Object s3ObjectTarget = S3Object.builder()
                       .bucket(bucketName)
                       .name(sourceImage)
                       .build();
   
               Image souImage = Image.builder()
                       .s3Object(s3ObjectTarget)
                       .build();
   
               DetectLabelsRequest detectLabelsRequest = DetectLabelsRequest.builder()
                       .image(souImage)
                       .maxLabels(10)
                       .build();
   
               DetectLabelsResponse labelsResponse = rekClient.detectLabels(detectLabelsRequest);
               List<Label> labels = labelsResponse.labels();
               System.out.println("Detected labels for the given photo");
               for (Label label : labels) {
                   System.out.println(label.name() + ": " + label.confidence().toString());
               }
   
           } catch (RekognitionException e) {
               System.out.println(e.getMessage());
               System.exit(1);
           }
       }
   }
   ```

------