Weitere AWS SDK-Beispiele sind im GitHub Repo [AWS Doc SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) verfügbar.
Die vorliegende Übersetzung wurde maschinell erstellt. Im Falle eines Konflikts oder eines Widerspruchs zwischen dieser übersetzten Fassung und der englischen Fassung (einschließlich infolge von Verzögerungen bei der Übersetzung) ist die englische Fassung maßgeblich.
# Verwendung `RecognizeCelebrities` mit einem AWS SDK oder CLI
Die folgenden Code-Beispiele zeigen, wie `RecognizeCelebrities` verwendet wird.
Weitere Informationen finden Sie unter [Erkennen von Prominenten in einem Bild](https://docs.aws.amazon.com/rekognition/latest/dg/celebrities-procedure-image.html).
------
#### [ .NET ]
**SDK für .NET**
Es gibt noch mehr dazu GitHub. Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das [AWS -Code-Beispiel-](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/dotnetv3/Rekognition/#code-examples) einrichten und ausführen.
```
using System;
using System.IO;
using System.Threading.Tasks;
using Amazon.Rekognition;
using Amazon.Rekognition.Model;
///
/// Shows how to use Amazon Rekognition to identify celebrities in a photo.
///
public class CelebritiesInImage
{
public static async Task Main(string[] args)
{
string photo = "moviestars.jpg";
var rekognitionClient = new AmazonRekognitionClient();
var recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
var img = new Amazon.Rekognition.Model.Image();
byte[] data = null;
try
{
using var 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");
var recognizeCelebritiesResponse = await rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebritiesRequest);
Console.WriteLine($"{recognizeCelebritiesResponse.CelebrityFaces.Count} celebrity(s) were recognized.\n");
recognizeCelebritiesResponse.CelebrityFaces.ForEach(celeb =>
{
Console.WriteLine($"Celebrity recognized: {celeb.Name}");
Console.WriteLine($"Celebrity ID: {celeb.Id}");
BoundingBox boundingBox = celeb.Face.BoundingBox;
Console.WriteLine($"position: {boundingBox.Left} {boundingBox.Top}");
Console.WriteLine("Further information (if available):");
celeb.Urls.ForEach(url =>
{
Console.WriteLine(url);
});
});
Console.WriteLine($"{recognizeCelebritiesResponse.UnrecognizedFaces.Count} face(s) were unrecognized.");
}
}
```
+ Einzelheiten zur API finden Sie [RecognizeCelebrities](https://docs.aws.amazon.com/goto/DotNetSDKV3/rekognition-2016-06-27/RecognizeCelebrities)in der *AWS SDK für .NET API-Referenz*.
------
#### [ CLI ]
**AWS CLI**
**So erkennen Sie Prominente in einem Bild**
Der folgende `recognize-celebrities`-Befehl erkennt Prominente in dem angegebenen Bild, das in einem Amazon-S3-Bucket gespeichert ist:
```
aws rekognition recognize-celebrities \
--image "S3Object={Bucket=MyImageS3Bucket,Name=moviestars.jpg}"
```
Ausgabe:
```
{
"UnrecognizedFaces": [
{
"BoundingBox": {
"Width": 0.14416666328907013,
"Top": 0.07777778059244156,
"Left": 0.625,
"Height": 0.2746031880378723
},
"Confidence": 99.9990234375,
"Pose": {
"Yaw": 10.80408763885498,
"Roll": -12.761146545410156,
"Pitch": 10.96889877319336
},
"Quality": {
"Sharpness": 94.1185531616211,
"Brightness": 79.18367004394531
},
"Landmarks": [
{
"Y": 0.18220913410186768,
"X": 0.6702951788902283,
"Type": "eyeLeft"
},
{
"Y": 0.16337193548679352,
"X": 0.7188183665275574,
"Type": "eyeRight"
},
{
"Y": 0.20739148557186127,
"X": 0.7055801749229431,
"Type": "nose"
},
{
"Y": 0.2889308035373688,
"X": 0.687512218952179,
"Type": "mouthLeft"
},
{
"Y": 0.2706988751888275,
"X": 0.7250053286552429,
"Type": "mouthRight"
}
]
}
],
"CelebrityFaces": [
{
"MatchConfidence": 100.0,
"Face": {
"BoundingBox": {
"Width": 0.14000000059604645,
"Top": 0.1190476194024086,
"Left": 0.82833331823349,
"Height": 0.2666666805744171
},
"Confidence": 99.99359130859375,
"Pose": {
"Yaw": -10.509642601013184,
"Roll": -14.51749324798584,
"Pitch": 13.799399375915527
},
"Quality": {
"Sharpness": 78.74752044677734,
"Brightness": 42.201324462890625
},
"Landmarks": [
{
"Y": 0.2290833294391632,
"X": 0.8709492087364197,
"Type": "eyeLeft"
},
{
"Y": 0.20639978349208832,
"X": 0.9153988361358643,
"Type": "eyeRight"
},
{
"Y": 0.25417643785476685,
"X": 0.8907724022865295,
"Type": "nose"
},
{
"Y": 0.32729196548461914,
"X": 0.8876466155052185,
"Type": "mouthLeft"
},
{
"Y": 0.3115464746952057,
"X": 0.9238573312759399,
"Type": "mouthRight"
}
]
},
"Name": "Celeb A",
"Urls": [
"www.imdb.com/name/aaaaaaaaa"
],
"Id": "1111111"
},
{
"MatchConfidence": 97.0,
"Face": {
"BoundingBox": {
"Width": 0.13333334028720856,
"Top": 0.24920634925365448,
"Left": 0.4449999928474426,
"Height": 0.2539682686328888
},
"Confidence": 99.99979400634766,
"Pose": {
"Yaw": 6.557040691375732,
"Roll": -7.316643714904785,
"Pitch": 9.272967338562012
},
"Quality": {
"Sharpness": 83.23492431640625,
"Brightness": 78.83267974853516
},
"Landmarks": [
{
"Y": 0.3625510632991791,
"X": 0.48898839950561523,
"Type": "eyeLeft"
},
{
"Y": 0.35366007685661316,
"X": 0.5313721299171448,
"Type": "eyeRight"
},
{
"Y": 0.3894785940647125,
"X": 0.5173314809799194,
"Type": "nose"
},
{
"Y": 0.44889405369758606,
"X": 0.5020005702972412,
"Type": "mouthLeft"
},
{
"Y": 0.4408611059188843,
"X": 0.5351271629333496,
"Type": "mouthRight"
}
]
},
"Name": "Celeb B",
"Urls": [
"www.imdb.com/name/bbbbbbbbb"
],
"Id": "2222222"
},
{
"MatchConfidence": 100.0,
"Face": {
"BoundingBox": {
"Width": 0.12416666746139526,
"Top": 0.2968254089355469,
"Left": 0.2150000035762787,
"Height": 0.23650793731212616
},
"Confidence": 99.99958801269531,
"Pose": {
"Yaw": 7.801797866821289,
"Roll": -8.326810836791992,
"Pitch": 7.844768047332764
},
"Quality": {
"Sharpness": 86.93206024169922,
"Brightness": 79.81291198730469
},
"Landmarks": [
{
"Y": 0.4027804136276245,
"X": 0.2575301229953766,
"Type": "eyeLeft"
},
{
"Y": 0.3934555947780609,
"X": 0.2956969439983368,
"Type": "eyeRight"
},
{
"Y": 0.4309830069541931,
"X": 0.2837020754814148,
"Type": "nose"
},
{
"Y": 0.48186683654785156,
"X": 0.26812544465065,
"Type": "mouthLeft"
},
{
"Y": 0.47338807582855225,
"X": 0.29905644059181213,
"Type": "mouthRight"
}
]
},
"Name": "Celeb C",
"Urls": [
"www.imdb.com/name/ccccccccc"
],
"Id": "3333333"
},
{
"MatchConfidence": 97.0,
"Face": {
"BoundingBox": {
"Width": 0.11916666477918625,
"Top": 0.3698412775993347,
"Left": 0.008333333767950535,
"Height": 0.22698412835597992
},
"Confidence": 99.99999237060547,
"Pose": {
"Yaw": 16.38478660583496,
"Roll": -1.0260354280471802,
"Pitch": 5.975185394287109
},
"Quality": {
"Sharpness": 83.23492431640625,
"Brightness": 61.408443450927734
},
"Landmarks": [
{
"Y": 0.4632347822189331,
"X": 0.049406956881284714,
"Type": "eyeLeft"
},
{
"Y": 0.46388113498687744,
"X": 0.08722897619009018,
"Type": "eyeRight"
},
{
"Y": 0.5020678639411926,
"X": 0.0758260041475296,
"Type": "nose"
},
{
"Y": 0.544157862663269,
"X": 0.054029736667871475,
"Type": "mouthLeft"
},
{
"Y": 0.5463630557060242,
"X": 0.08464983850717545,
"Type": "mouthRight"
}
]
},
"Name": "Celeb D",
"Urls": [
"www.imdb.com/name/ddddddddd"
],
"Id": "4444444"
}
]
}
```
Weitere Informationen finden Sie unter [Erkennen von Prominenten in einem Bild](https://docs.aws.amazon.com/rekognition/latest/dg/celebrities-procedure-image.html) im *Entwicklerhandbuch für Amazon Rekognition*.
+ Einzelheiten zur API finden Sie [RecognizeCelebrities](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/rekognition/recognize-celebrities.html)in der *AWS CLI Befehlsreferenz*.
------
#### [ Java ]
**SDK für Java 2.x**
Es gibt noch mehr dazu GitHub. Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das [AWS -Code-Beispiel-](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/rekognition/#code-examples) einrichten und ausführen.
```
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.*;
/**
* 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 = """
Usage:
Where:
bucketName - The name of the S3 bucket where the images are stored.
sourceImage - The path to the image (for example, C:\\AWS\\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();
System.out.println("Locating celebrities in " + sourceImage);
recognizeAllCelebrities(rekClient, bucketName, sourceImage);
rekClient.close();
}
/**
* Recognizes all celebrities in an image stored in an Amazon S3 bucket.
*
* @param rekClient the Amazon Rekognition client used to perform the celebrity recognition operation
* @param bucketName the name of the Amazon S3 bucket where the source image is stored
* @param sourceImage the name of the source image file stored in the Amazon S3 bucket
*/
public static void recognizeAllCelebrities(RekognitionClient rekClient, String bucketName, String sourceImage) {
try {
S3Object s3ObjectTarget = S3Object.builder()
.bucket(bucketName)
.name(sourceImage)
.build();
Image souImage = Image.builder()
.s3Object(s3ObjectTarget)
.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 e) {
System.out.println(e.getMessage());
System.exit(1);
}
}
}
```
+ Einzelheiten zur API finden Sie [RecognizeCelebrities](https://docs.aws.amazon.com/goto/SdkForJavaV2/rekognition-2016-06-27/RecognizeCelebrities)in der *AWS SDK for Java 2.x API-Referenz*.
------
#### [ Kotlin ]
**SDK für Kotlin**
Es gibt noch mehr dazu GitHub. Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das [AWS -Code-Beispiel-](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/kotlin/services/rekognition#code-examples) einrichten und ausführen.
```
suspend fun recognizeAllCelebrities(sourceImage: String?) {
val souImage =
Image {
bytes = (File(sourceImage).readBytes())
}
val request =
RecognizeCelebritiesRequest {
image = souImage
}
RekognitionClient.fromEnvironment { region = "us-east-1" }.use { rekClient ->
val response = rekClient.recognizeCelebrities(request)
response.celebrityFaces?.forEach { celebrity ->
println("Celebrity recognized: ${celebrity.name}")
println("Celebrity ID:${celebrity.id}")
println("Further information (if available):")
celebrity.urls?.forEach { url ->
println(url)
}
}
println("${response.unrecognizedFaces?.size} face(s) were unrecognized.")
}
}
```
+ API-Details finden Sie [RecognizeCelebrities](https://sdk.amazonaws.com/kotlin/api/latest/index.html)in der *API-Referenz zum AWS SDK für Kotlin*.
------
#### [ Python ]
**SDK für Python (Boto3)**
Es gibt noch mehr dazu. GitHub Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das [AWS -Code-Beispiel-](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/rekognition#code-examples) einrichten und ausführen.
```
class RekognitionImage:
"""
Encapsulates an Amazon Rekognition image. This class is a thin wrapper
around parts of the Boto3 Amazon Rekognition API.
"""
def __init__(self, image, image_name, rekognition_client):
"""
Initializes the image object.
:param image: Data that defines the image, either the image bytes or
an Amazon S3 bucket and object key.
:param image_name: The name of the image.
:param rekognition_client: A Boto3 Rekognition client.
"""
self.image = image
self.image_name = image_name
self.rekognition_client = rekognition_client
def recognize_celebrities(self):
"""
Detects celebrities in the image.
:return: A tuple. The first element is the list of celebrities found in
the image. The second element is the list of faces that were
detected but did not match any known celebrities.
"""
try:
response = self.rekognition_client.recognize_celebrities(Image=self.image)
celebrities = [
RekognitionCelebrity(celeb) for celeb in response["CelebrityFaces"]
]
other_faces = [
RekognitionFace(face) for face in response["UnrecognizedFaces"]
]
logger.info(
"Found %s celebrities and %s other faces in %s.",
len(celebrities),
len(other_faces),
self.image_name,
)
except ClientError:
logger.exception("Couldn't detect celebrities in %s.", self.image_name)
raise
else:
return celebrities, other_faces
```
+ Einzelheiten zur API finden Sie [RecognizeCelebrities](https://docs.aws.amazon.com/goto/boto3/rekognition-2016-06-27/RecognizeCelebrities)in *AWS SDK for Python (Boto3) API* Reference.
------
#### [ SAP ABAP ]
**SDK für SAP ABAP**
Es gibt noch mehr dazu. GitHub Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das [AWS -Code-Beispiel-](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/rek#code-examples) einrichten und ausführen.
```
TRY.
" Create S3 object reference for the image
DATA(lo_s3object) = NEW /aws1/cl_reks3object(
iv_bucket = iv_s3_bucket
iv_name = iv_s3_key ).
" Create image object
DATA(lo_image) = NEW /aws1/cl_rekimage(
io_s3object = lo_s3object ).
" Recognize celebrities
oo_result = lo_rek->recognizecelebrities(
io_image = lo_image ).
DATA(lt_celebrity_faces) = oo_result->get_celebrityfaces( ).
DATA(lv_celeb_count) = lines( lt_celebrity_faces ).
DATA(lv_msg12) = |{ lv_celeb_count } celebrity/celebrities recognized.|.
MESSAGE lv_msg12 TYPE 'I'.
CATCH /aws1/cx_rekinvalids3objectex.
MESSAGE 'Invalid S3 object.' TYPE 'E'.
CATCH /aws1/cx_rekinvalidparameterex.
MESSAGE 'Invalid parameter value.' TYPE 'E'.
ENDTRY.
```
+ Einzelheiten zur API finden Sie [RecognizeCelebrities](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)in der *API-Referenz zum AWS SDK für SAP ABAP*.
------