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# 识别图像中的名人
要识别图像中的名人并获取有关所识别名人的其他信息，请使用 [RecognizeCelebrities](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_RecognizeCelebrities.html) 非存储 API 操作。例如，在社交媒体或新闻和娱乐界，信息收集时间紧张，您可使用 `RecognizeCelebrities` 操作识别一张图像中多达 64 位名人并返回指向名人网页（如有）的链接。Amazon Rekognition 不会记住它在哪一张图像中检测到过名人。您的应用程序必须存储此信息。
如果您尚未存储 `RecognizeCelebrities` 返回的某位名人的其他信息，并且您希望避免重新分析图像以获取这些信息，请使用 [GetCelebrityInfo](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_GetCelebrityInfo.html)。要调用 `GetCelebrityInfo`，您需要 Amazon Rekognition 分配给每位名人的唯一标识符。该标识符将作为针对在图像中识别的每位名人的 `RecognizeCelebrities` 响应的一部分返回。
如果您有大型图像集要做名人识别处理，请考虑使用 [AWS Batch](https://docs.aws.amazon.com/batch/latest/userguide/) 在后台分批处理对 `RecognizeCelebrities` 的调用。向收藏夹中添加新图片时，您可以使用 AWS Lambda 函数识别名人，方法是在图片上传到 S3 存储桶时调用`RecognizeCelebrities`。
## 正在呼叫 RecognizeCelebrities
您可以使用 () 或 AWS 软件开发工具包将输入图像作为图像字节数组（base64 编码的图像字节AWS CLI）或 Amazon S3 对象提供。 AWS Command Line Interface 在此 AWS CLI 过程中，您将.jpg 或.png 格式的图像上传到 S3 存储桶。在 AWS SDK 过程中，您使用的是从本地文件系统加载的图像。有关图像建议的信息，请参阅[使用图像](images.md)。
要运行此过程，您需要一个包含一张或多张名人人脸的图像文件。
**识别图像中的名人**
1. 如果您尚未执行以下操作，请：
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](setting-up.md#setting-up-iam)。
1. 安装和配置 AWS CLI 和 AWS SDK。有关更多信息，请参阅 [第 2 步：设置 AWS CLI and AWS 软件开发工具包](setup-awscli-sdk.md)。
1. 使用以下示例调用 `RecognizeCelebrities` 操作。
------
#### [ Java ]
此示例显示与图像中检测到的名人相关的信息。
将 `photo` 的值更改为包含一张或多张名人人脸的图像的路径和文件名。
```
//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.Image;
import com.amazonaws.services.rekognition.model.BoundingBox;
import com.amazonaws.services.rekognition.model.Celebrity;
import com.amazonaws.services.rekognition.model.RecognizeCelebritiesRequest;
import com.amazonaws.services.rekognition.model.RecognizeCelebritiesResult;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.nio.ByteBuffer;
import com.amazonaws.util.IOUtils;
import java.util.List;
public class RecognizeCelebrities {
public static void main(String[] args) {
String photo = "moviestars.jpg";
AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
ByteBuffer imageBytes=null;
try (InputStream inputStream = new FileInputStream(new File(photo))) {
imageBytes = ByteBuffer.wrap(IOUtils.toByteArray(inputStream));
}
catch(Exception e)
{
System.out.println("Failed to load file " + photo);
System.exit(1);
}
RecognizeCelebritiesRequest request = new RecognizeCelebritiesRequest()
.withImage(new Image()
.withBytes(imageBytes));
System.out.println("Looking for celebrities in image " + photo + "\n");
RecognizeCelebritiesResult result=rekognitionClient.recognizeCelebrities(request);
//Display recognized celebrity information
List celebs=result.getCelebrityFaces();
System.out.println(celebs.size() + " celebrity(s) were recognized.\n");
for (Celebrity celebrity: celebs) {
System.out.println("Celebrity recognized: " + celebrity.getName());
System.out.println("Celebrity ID: " + celebrity.getId());
BoundingBox boundingBox=celebrity.getFace().getBoundingBox();
System.out.println("position: " +
boundingBox.getLeft().toString() + " " +
boundingBox.getTop().toString());
System.out.println("Further information (if available):");
for (String url: celebrity.getUrls()){
System.out.println(url);
}
System.out.println();
}
System.out.println(result.getUnrecognizedFaces().size() + " face(s) were unrecognized.");
}
}
```
------
#### [ Java V2 ]
此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在[此处](https://github.com/awsdocs/aws-doc-sdk-examples/blob/master/javav2/example_code/rekognition/src/main/java/com/example/rekognition/RecognizeCelebrities.java)查看完整示例。
```
//snippet-start:[rekognition.java2.recognize_celebs.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.core.SdkBytes;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.List;
import software.amazon.awssdk.services.rekognition.model.RecognizeCelebritiesRequest;
import software.amazon.awssdk.services.rekognition.model.RecognizeCelebritiesResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.Celebrity;
//snippet-end:[rekognition.java2.recognize_celebs.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 RecognizeCelebrities {
public static void main(String[] args) {
final String usage = "\n" +
"Usage: " +
" \n\n" +
"Where:\n" +
" sourceImage - The path to the image (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_EAST_1;
RekognitionClient rekClient = RekognitionClient.builder()
.region(region)
.credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
.build();
System.out.println("Locating celebrities in " + sourceImage);
recognizeAllCelebrities(rekClient, sourceImage);
rekClient.close();
}
// snippet-start:[rekognition.java2.recognize_celebs.main]
public static void recognizeAllCelebrities(RekognitionClient rekClient, String sourceImage) {
try {
InputStream sourceStream = new FileInputStream(sourceImage);
SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
Image souImage = Image.builder()
.bytes(sourceBytes)
.build();
RecognizeCelebritiesRequest request = RecognizeCelebritiesRequest.builder()
.image(souImage)
.build();
RecognizeCelebritiesResponse result = rekClient.recognizeCelebrities(request) ;
List celebs=result.celebrityFaces();
System.out.println(celebs.size() + " celebrity(s) were recognized.\n");
for (Celebrity celebrity: celebs) {
System.out.println("Celebrity recognized: " + celebrity.name());
System.out.println("Celebrity ID: " + celebrity.id());
System.out.println("Further information (if available):");
for (String url: celebrity.urls()){
System.out.println(url);
}
System.out.println();
}
System.out.println(result.unrecognizedFaces().size() + " face(s) were unrecognized.");
} catch (RekognitionException | FileNotFoundException e) {
System.out.println(e.getMessage());
System.exit(1);
}
}
// snippet-end:[rekognition.java2.recognize_celebs.main]
}
```
------
#### [ AWS CLI ]
此 AWS CLI 命令显示 `recognize-celebrities` CLI 操作的 JSON 输出。
将`amzn-s3-demo-bucket`更改为包含图像的 Amazon S3 存储桶的名称。将 `input.jpg` 更改为包含一张或多张名人人脸的图像的文件名。
将`profile_name`的值替换为您的开发人员资料的名称。
```
aws rekognition recognize-celebrities \
--image "S3Object={Bucket={{amzn-s3-demo-bucket}},Name={{input.jpg}}}"
```
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 recognize-celebrities --image \
"{\"S3Object\":{\"Bucket\":\"amzn-s3-demo-bucket\",\"Name\":\"image-name\"}}" --profile profile-name
```
------
#### [ Python ]
此示例显示与图像中检测到的名人相关的信息。
将 `photo` 的值更改为包含一张或多张名人人脸的图像的路径和文件名。
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 recognize_celebrities(photo):
session = boto3.Session(profile_name='profile-name')
client = session.client('rekognition')
with open(photo, 'rb') as image:
response = client.recognize_celebrities(Image={'Bytes': image.read()})
print('Detected faces for ' + photo)
for celebrity in response['CelebrityFaces']:
print('Name: ' + celebrity['Name'])
print('Id: ' + celebrity['Id'])
print('KnownGender: ' + celebrity['KnownGender']['Type'])
print('Smile: ' + str(celebrity['Face']['Smile']['Value']))
print('Position:')
print(' Left: ' + '{:.2f}'.format(celebrity['Face']['BoundingBox']['Height']))
print(' Top: ' + '{:.2f}'.format(celebrity['Face']['BoundingBox']['Top']))
print('Info')
for url in celebrity['Urls']:
print(' ' + url)
print()
return len(response['CelebrityFaces'])
def main():
photo = 'photo-name'
celeb_count = recognize_celebrities(photo)
print("Celebrities detected: " + str(celeb_count))
if __name__ == "__main__":
main()
```
------
#### [ Node.Js ]
此示例显示与图像中检测到的名人相关的信息。
将 `photo` 的值更改为包含一张或多张名人人脸的图像的路径和文件名。将`amzn-s3-demo-bucket`的值更改为包含所提供图像文件的 S3 存储桶的名称。将`REGION`的值更改为与您的用户关联的区域名称。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。
```
// Import required AWS SDK clients and commands for Node.js
import { RecognizeCelebritiesCommand } from "@aws-sdk/client-rekognition";
import { RekognitionClient } from "@aws-sdk/client-rekognition";
// Set the AWS Region.
const REGION = "region-name"; //e.g. "us-east-1"
const profileName = "profile-name";
// Create SNS service object.
const rekogClient = new RekognitionClient({region: REGION,
credentials: fromIni({profile: profileName,}),
});
const bucket = 'bucket-name'
const photo = 'photo-name'
// Set params
const params = {
Image: {
S3Object: {
Bucket: bucket,
Name: photo
},
},
}
const recognize_celebrity = async() => {
try {
const response = await rekogClient.send(new RecognizeCelebritiesCommand(params));
console.log(response.Labels)
response.CelebrityFaces.forEach(celebrity =>{
console.log(`Name: ${celebrity.Name}`)
console.log(`ID: ${celebrity.Id}`)
console.log(`KnownGender: ${celebrity.KnownGender.Type}`)
console.log(`Smile: ${celebrity.Smile}`)
console.log('Position: ')
console.log(` Left: ${celebrity.Face.BoundingBox.Height}`)
console.log(` Top : ${celebrity.Face.BoundingBox.Top}`)
})
return response.length; // For unit tests.
} catch (err) {
console.log("Error", err);
}
}
recognize_celebrity()
```
------
#### [ .NET ]
此示例显示与图像中检测到的名人相关的信息。
将`photo`的值更改为包含一张或多张名人人脸（.jpg 或 .png 格式）的图像文件的路径和文件名。
```
//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 CelebritiesInImage
{
public static void Example()
{
String photo = "moviestars.jpg";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
RecognizeCelebritiesRequest recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
Amazon.Rekognition.Model.Image img = new Amazon.Rekognition.Model.Image();
byte[] data = null;
try
{
using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read))
{
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
}
}
catch(Exception)
{
Console.WriteLine("Failed to load file " + photo);
return;
}
img.Bytes = new MemoryStream(data);
recognizeCelebritiesRequest.Image = img;
Console.WriteLine("Looking for celebrities in image " + photo + "\n");
RecognizeCelebritiesResponse recognizeCelebritiesResponse = rekognitionClient.RecognizeCelebrities(recognizeCelebritiesRequest);
Console.WriteLine(recognizeCelebritiesResponse.CelebrityFaces.Count + " celebrity(s) were recognized.\n");
foreach (Celebrity celebrity in recognizeCelebritiesResponse.CelebrityFaces)
{
Console.WriteLine("Celebrity recognized: " + celebrity.Name);
Console.WriteLine("Celebrity ID: " + celebrity.Id);
BoundingBox boundingBox = celebrity.Face.BoundingBox;
Console.WriteLine("position: " +
boundingBox.Left + " " + boundingBox.Top);
Console.WriteLine("Further information (if available):");
foreach (String url in celebrity.Urls)
Console.WriteLine(url);
}
Console.WriteLine(recognizeCelebritiesResponse.UnrecognizedFaces.Count + " face(s) were unrecognized.");
}
}
```
------
1. 记录显示的名人 ID 之一的值。您将在[获取有关名人的信息](get-celebrity-info-procedure.md)中需要它。
## RecognizeCelebrities 操作请求
对 `RecognizeCelebrities` 的输入是一个图像。在此示例中，图像作为图像字节传递。有关更多信息，请参阅 [使用图像](images.md)。
```
{
"Image": {
"Bytes": "/AoSiyvFpm....."
}
}
```
## RecognizeCelebrities 操作响应
下面是 `RecognizeCelebrities` 的示例 JSON 输入和输出。
`RecognizeCelebrities` 返回一个已识别名人数组和一个未识别人脸数组。在该示例中，请注意以下内容：
+ **已识别的名人** – `Celebrities` 是已识别名人的数组。该数组中的每个 [Celebrity](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_Celebritiy.html) 对象都包含名人姓名和指向相关内容的 URL 的列表，例如，名人的 IMDB 或 Wikidata 链接。Amazon Rekognition 会[ComparedFace](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_ComparedFace.html)返回一个对象，您的应用程序可以使用该对象来确定名人脸部在图片上的位置以及名人的唯一标识符。之后通过 [GetCelebrityInfo](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_GetCelebrityInfo.html) API 操作使用唯一标识符检索名人信息。
+ **未识别的人脸** – `UnrecognizedFaces` 是与任何已知名人都不匹配的人脸的数组。该数组中的每个 [ComparedFace](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_ComparedFace.html) 对象都包含一个您可用于找到人脸在图像上的位置的边界框 (以及其他信息)。
```
{
"CelebrityFaces": [{
"Face": {
"BoundingBox": {
"Height": 0.617123007774353,
"Left": 0.15641026198863983,
"Top": 0.10864841192960739,
"Width": 0.3641025722026825
},
"Confidence": 99.99589538574219,
"Emotions": [{
"Confidence": 96.3981749057023,
"Type": "Happy"
}
],
"Landmarks": [{
"Type": "eyeLeft",
"X": 0.2837241291999817,
"Y": 0.3637104034423828
}, {
"Type": "eyeRight",
"X": 0.4091649055480957,
"Y": 0.37378931045532227
}, {
"Type": "nose",
"X": 0.35267341136932373,
"Y": 0.49657556414604187
}, {
"Type": "mouthLeft",
"X": 0.2786353826522827,
"Y": 0.5455248355865479
}, {
"Type": "mouthRight",
"X": 0.39566439390182495,
"Y": 0.5597742199897766
}],
"Pose": {
"Pitch": -7.749263763427734,
"Roll": 2.004552125930786,
"Yaw": 9.012002944946289
},
"Quality": {
"Brightness": 32.69192123413086,
"Sharpness": 99.9305191040039
},
"Smile": {
"Confidence": 95.45394855702342,
"Value": True
}
},
"Id": "3Ir0du6",
"KnownGender": {
"Type": "Male"
},
"MatchConfidence": 98.0,
"Name": "Jeff Bezos",
"Urls": ["www.imdb.com/name/nm1757263"]
}],
"OrientationCorrection": "NULL",
"UnrecognizedFaces": [{
"BoundingBox": {
"Height": 0.5345501899719238,
"Left": 0.48461538553237915,
"Top": 0.16949152946472168,
"Width": 0.3153846263885498
},
"Confidence": 99.92860412597656,
"Landmarks": [{
"Type": "eyeLeft",
"X": 0.5863404870033264,
"Y": 0.36940744519233704
}, {
"Type": "eyeRight",
"X": 0.6999204754829407,
"Y": 0.3769848346710205
}, {
"Type": "nose",
"X": 0.6349524259567261,
"Y": 0.4804527163505554
}, {
"Type": "mouthLeft",
"X": 0.5872702598571777,
"Y": 0.5535582304000854
}, {
"Type": "mouthRight",
"X": 0.6952020525932312,
"Y": 0.5600858926773071
}],
"Pose": {
"Pitch": -7.386096477508545,
"Roll": 2.304218292236328,
"Yaw": -6.175624370574951
},
"Quality": {
"Brightness": 37.16635513305664,
"Sharpness": 99.9305191040039
},
"Smile": {
"Confidence": 95.45394855702342,
"Value": True
}
}]
}
```