Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.
# Mendeteksi objek dan konsep
labels = result.getLabels();
System.out.println("Detected labels for " + photo + "\n");
for (Label label : labels) {
System.out.println("Label: " + label.getName());
System.out.println("Confidence: " + label.getConfidence().toString() + "\n");
List instances = label.getInstances();
System.out.println("Instances of " + label.getName());
if (instances.isEmpty()) {
System.out.println(" " + "None");
} else {
for (Instance instance : instances) {
System.out.println(" Confidence: " + instance.getConfidence().toString());
System.out.println(" Bounding box: " + instance.getBoundingBox().toString());
}
}
System.out.println("Parent labels for " + label.getName() + ":");
List parents = label.getParents();
if (parents.isEmpty()) {
System.out.println(" None");
} else {
for (Parent parent : parents) {
System.out.println(" " + parent.getName());
}
}
System.out.println("--------------------");
System.out.println();
}
} catch (AmazonRekognitionException e) {
e.printStackTrace();
}
}
}
```
------
#### [ AWS CLI ]
Contoh ini menampilkan output JSON dari operasi CLI `detect-labels`. Ganti nilai-nilai `bucket` dan `photo` dengan nama bucket Amazon S3 dan citra yang Anda gunakan di Langkah 2. Ganti nilai `profile-name` dengan nama profil pengembang Anda.
```
aws rekognition detect-labels --image '{ "S3Object": { "Bucket": "bucket-name", "Name": "file-name" } }' \
--features GENERAL_LABELS IMAGE_PROPERTIES \
--settings '{"ImageProperties": {"MaxDominantColors":1}, {"GeneralLabels":{"LabelInclusionFilters":["Cat"]}}}' \
--profile profile-name \
--region us-east-1
```
Jika Anda mengakses CLI pada perangkat Windows, gunakan tanda kutip ganda alih-alih tanda kutip tunggal dan hindari tanda kutip ganda bagian dalam dengan garis miring terbalik (yaitu\$1) untuk mengatasi kesalahan parser yang mungkin Anda temui. Sebagai contoh, lihat berikut ini:
```
aws rekognition detect-labels --image "{\"S3Object\":{\"Bucket\":\"bucket-name\",\"Name\":\"file-name\"}}" --features GENERAL_LABELS IMAGE_PROPERTIES \
--settings "{\"GeneralLabels\":{\"LabelInclusionFilters\":[\"Car\"]}}" --profile profile-name --region us-east-1
```
------
#### [ Python ]
Contoh ini menampilkan label yang terdeteksi dalam citra input. Dalam fungsi `main`, ganti nilai-nilai `bucket` dan `photo` dengan nama bucket Amazon S3 dan citra yang Anda gunakan pada Langkah 2. Ganti nilai `profile_name` di baris yang membuat sesi Rekognition dengan nama profil pengembang Anda.
```
#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(photo, bucket):
session = boto3.Session(profile_name='profile-name')
client = session.client('rekognition')
response = client.detect_labels(Image={'S3Object':{'Bucket':bucket,'Name':photo}},
MaxLabels=10,
# Uncomment to use image properties and filtration settings
#Features=["GENERAL_LABELS", "IMAGE_PROPERTIES"],
#Settings={"GeneralLabels": {"LabelInclusionFilters":["Cat"]},
# "ImageProperties": {"MaxDominantColors":10}}
)
print('Detected labels for ' + photo)
print()
for label in response['Labels']:
print("Label: " + label['Name'])
print("Confidence: " + str(label['Confidence']))
print("Instances:")
for instance in label['Instances']:
print(" Bounding box")
print(" Top: " + str(instance['BoundingBox']['Top']))
print(" Left: " + str(instance['BoundingBox']['Left']))
print(" Width: " + str(instance['BoundingBox']['Width']))
print(" Height: " + str(instance['BoundingBox']['Height']))
print(" Confidence: " + str(instance['Confidence']))
print()
print("Parents:")
for parent in label['Parents']:
print(" " + parent['Name'])
print("Aliases:")
for alias in label['Aliases']:
print(" " + alias['Name'])
print("Categories:")
for category in label['Categories']:
print(" " + category['Name'])
print("----------")
print()
if "ImageProperties" in str(response):
print("Background:")
print(response["ImageProperties"]["Background"])
print()
print("Foreground:")
print(response["ImageProperties"]["Foreground"])
print()
print("Quality:")
print(response["ImageProperties"]["Quality"])
print()
return len(response['Labels'])
def main():
photo = 'photo-name'
bucket = 'amzn-s3-demo-bucket'
label_count = detect_labels(photo, bucket)
print("Labels detected: " + str(label_count))
if __name__ == "__main__":
main()
```
------
#### [ .NET ]
Contoh ini menampilkan daftar label yang terdeteksi pada citra input. Ganti nilai-nilai `bucket` dan `photo` dengan nama bucket Amazon S3 dan citra yang Anda gunakan di Langkah 2.
```
//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 DetectLabels
{
public static void Example()
{
String photo = "input.jpg";
String bucket = "amzn-s3-demo-bucket";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest()
{
Image = new Image()
{
S3Object = new S3Object()
{
Name = photo,
Bucket = bucket
},
},
MaxLabels = 10,
MinConfidence = 75F
};
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);
}
}
}
```
------
#### [ Ruby ]
Contoh ini menampilkan daftar label yang terdeteksi pada citra input. Ganti nilai-nilai `bucket` dan `photo` dengan nama bucket Amazon S3 dan citra yang Anda gunakan di Langkah 2.
```
# Add to your Gemfile
# gem 'aws-sdk-rekognition'
require 'aws-sdk-rekognition'
credentials = Aws::Credentials.new(
ENV['AWS_ACCESS_KEY_ID'],
ENV['AWS_SECRET_ACCESS_KEY']
)
bucket = 'bucket' # the bucket name without s3://
photo = 'photo' # the name of file
client = Aws::Rekognition::Client.new credentials: credentials
attrs = {
image: {
s3_object: {
bucket: bucket,
name: photo
},
},
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
```
------
#### [ Node.js ]
Contoh ini menampilkan daftar label yang terdeteksi pada citra input. Ganti nilai-nilai `bucket` dan `photo` dengan nama bucket Amazon S3 dan citra yang Anda gunakan di Langkah 2. Ganti nilai `profile_name` di baris yang membuat sesi Rekognition dengan nama profil pengembang Anda.
Jika Anda menggunakan TypeScript definisi, Anda mungkin perlu menggunakan `import AWS from 'aws-sdk'` alih-alih`const AWS = require('aws-sdk')`, untuk menjalankan program dengan Node.js. Anda dapat melihat [AWS SDK for Javascript](https://docs.aws.amazon.com/AWSJavaScriptSDK/latest/) untuk detailnya selengkapnya. Tergantung bagaimana konfigurasi diatur, Anda juga mungkin perlu menentukan wilayah Anda dengan `AWS.config.update({region:region});`.
```
// Load the SDK
var AWS = require('aws-sdk');
const bucket = 'bucket-name' // the bucketname without s3://
const photo = 'image-name' // the name of file
var credentials = new AWS.SharedIniFileCredentials({profile: 'profile-name'});
AWS.config.credentials = credentials;
AWS.config.update({region:'region-name'});
const client = new AWS.Rekognition();
const params = {
Image: {
S3Object: {
Bucket: bucket,
Name: photo
},
},
MaxLabels: 10
}
client.detectLabels(params, function(err, response) {
if (err) {
console.log(err, err.stack); // if an error occurred
} else {
console.log(`Detected labels for: ${photo}`)
response.Labels.forEach(label => {
console.log(`Label: ${label.Name}`)
console.log(`Confidence: ${label.Confidence}`)
console.log("Instances:")
label.Instances.forEach(instance => {
let box = instance.BoundingBox
console.log(" Bounding box:")
console.log(` Top: ${box.Top}`)
console.log(` Left: ${box.Left}`)
console.log(` Width: ${box.Width}`)
console.log(` Height: ${box.Height}`)
console.log(` Confidence: ${instance.Confidence}`)
})
console.log("Parents:")
label.Parents.forEach(parent => {
console.log(` ${parent.Name}`)
})
console.log("------------")
console.log("")
}) // for response.labels
} // if
});
```
------
#### [ 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).
```
//snippet-start:[rekognition.java2.detect_labels.import]
import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.DetectLabelsRequest;
import software.amazon.awssdk.services.rekognition.model.DetectLabelsResponse;
import software.amazon.awssdk.services.rekognition.model.Label;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.S3Object;
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 = "\n" +
"Usage: " +
" \n\n" +
"Where:\n" +
" bucket - The name of the Amazon S3 bucket that contains the image (for example, ,ImageBucket)." +
" image - The name of the image located in the Amazon S3 bucket (for example, Lake.png). \n\n";
if (args.length != 2) {
System.out.println(usage);
System.exit(1);
}
String bucket = args[0];
String image = args[1];
Region region = Region.US_WEST_2;
RekognitionClient rekClient = RekognitionClient.builder()
.region(region)
.credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
.build();
getLabelsfromImage(rekClient, bucket, image);
rekClient.close();
}
// snippet-start:[rekognition.java2.detect_labels_s3.main]
public static void getLabelsfromImage(RekognitionClient rekClient, String bucket, String image) {
try {
S3Object s3Object = S3Object.builder()
.bucket(bucket)
.name(image)
.build() ;
Image myImage = Image.builder()
.s3Object(s3Object)
.build();
DetectLabelsRequest detectLabelsRequest = DetectLabelsRequest.builder()
.image(myImage)
.maxLabels(10)
.build();
DetectLabelsResponse labelsResponse = rekClient.detectLabels(detectLabelsRequest);
List 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);
}
}
// snippet-end:[rekognition.java2.detect_labels.main]
}
```
------
## DetectLabels permintaan operasi
],
"LabelExclusionFilters": [],
"LabelCategoryInclusionFilters": [],
"LabelCategoryExclusionFilters": []
},
"ImageProperties": {
"MaxDominantColors":10
}
}
}
```
## DetectLabels respon