创建 Amazon Rekognition Video 人脸搜索流处理器启动 Amazon Rekognition Video 人脸搜索流处理器使用流处理器搜索人脸（Java V2 示例）使用流处理器搜索人脸（Java V1 示例）

在流视频中搜索人脸

Amazon Rekognition Video 可以搜索集合中与在流视频中检测到的人脸匹配的人脸。有关集合的更多信息，请参阅在集合中搜索人脸。

主题

创建 Amazon Rekognition Video 人脸搜索流处理器
启动 Amazon Rekognition Video 人脸搜索流处理器
使用流处理器搜索人脸（Java V2 示例）
使用流处理器搜索人脸（Java V1 示例）
读取流视频分析结果
参考：Kinesis 人脸识别记录

下图显示了 Amazon Rekognition Video 如何检测和识别流视频中的人脸。

使用亚马逊 Rekognition Video 处理来自亚马逊 Kinesis 的视频流的工作流程图。

创建 Amazon Rekognition Video 人脸搜索流处理器

在分析流媒体视频之前，您需要先创建一个 Amazon Rekognition Video 流处理器 ()。CreateStreamProcessor流处理器包含有关 Kinesis 数据流和 Kinesis 视频流的信息。它还包含含有您要在输入流视频中识别的人脸的集合的标识符。您还可为流处理器指定名称。以下是 CreateStreamProcessor 请求的 JSON 示例。


{
       "Name": "streamProcessorForCam",
       "Input": {
              "KinesisVideoStream": {
                     "Arn": "arn:aws:kinesisvideo:us-east-1:nnnnnnnnnnnn:stream/inputVideo"
              }
       },
       "Output": {
              "KinesisDataStream": {
                     "Arn": "arn:aws:kinesis:us-east-1:nnnnnnnnnnnn:stream/outputData"
              }
       },
       "RoleArn": "arn:aws:iam::nnnnnnnnnnn:role/roleWithKinesisPermission",
       "Settings": {
              "FaceSearch": {
                     "CollectionId": "collection-with-100-faces",
                     "FaceMatchThreshold": 85.5
              }
       }
}

以下是来自 CreateStreamProcessor 的示例响应。


{
       “StreamProcessorArn”: “arn:aws:rekognition:us-east-1:nnnnnnnnnnnn:streamprocessor/streamProcessorForCam”
}

启动 Amazon Rekognition Video 人脸搜索流处理器

使用您在中指定的流处理器名称StartStreamProcessor进行调用，即可开始分析流式视频CreateStreamProcessor。以下是 StartStreamProcessor 请求的 JSON 示例。


{
       "Name": "streamProcessorForCam"
}

如果流处理器成功启动，则会返回 HTTP 200 响应以及空白的 JSON 正文。

使用流处理器搜索人脸（Java V2 示例）

以下示例代码展示了如何使用适用于 Java 的 AWS SDK 版本 2 调用各种流处理器操作 StartStreamProcessor，例如CreateStreamProcessor和。

此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在此处查看完整示例。


import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.CreateStreamProcessorRequest;
import software.amazon.awssdk.services.rekognition.model.CreateStreamProcessorResponse;
import software.amazon.awssdk.services.rekognition.model.FaceSearchSettings;
import software.amazon.awssdk.services.rekognition.model.KinesisDataStream;
import software.amazon.awssdk.services.rekognition.model.KinesisVideoStream;
import software.amazon.awssdk.services.rekognition.model.ListStreamProcessorsRequest;
import software.amazon.awssdk.services.rekognition.model.ListStreamProcessorsResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.StreamProcessor;
import software.amazon.awssdk.services.rekognition.model.StreamProcessorInput;
import software.amazon.awssdk.services.rekognition.model.StreamProcessorSettings;
import software.amazon.awssdk.services.rekognition.model.StreamProcessorOutput;
import software.amazon.awssdk.services.rekognition.model.StartStreamProcessorRequest;
import software.amazon.awssdk.services.rekognition.model.DescribeStreamProcessorRequest;
import software.amazon.awssdk.services.rekognition.model.DescribeStreamProcessorResponse;

/**
 * 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 CreateStreamProcessor {
        public static void main(String[] args) {
                final String usage = """

                                Usage:    <role> <kinInputStream> <kinOutputStream> <collectionName> <StreamProcessorName>

                                Where:
                                   role - The ARN of the AWS Identity and Access Management (IAM) role to use. \s
                                   kinInputStream - The ARN of the Kinesis video stream.\s
                                   kinOutputStream - The ARN of the Kinesis data stream.\s
                                   collectionName - The name of the collection to use that contains content. \s
                                   StreamProcessorName - The name of the Stream Processor. \s
                                """;

                if (args.length != 5) {
                        System.out.println(usage);
                        System.exit(1);
                }

                String role = args[0];
                String kinInputStream = args[1];
                String kinOutputStream = args[2];
                String collectionName = args[3];
                String streamProcessorName = args[4];

                Region region = Region.US_EAST_1;
                RekognitionClient rekClient = RekognitionClient.builder()
                                .region(region)
                                .build();

                processCollection(rekClient, streamProcessorName, kinInputStream, kinOutputStream, collectionName,
                                role);
                startSpecificStreamProcessor(rekClient, streamProcessorName);
                listStreamProcessors(rekClient);
                describeStreamProcessor(rekClient, streamProcessorName);
                deleteSpecificStreamProcessor(rekClient, streamProcessorName);
        }

        public static void listStreamProcessors(RekognitionClient rekClient) {
                ListStreamProcessorsRequest request = ListStreamProcessorsRequest.builder()
                                .maxResults(15)
                                .build();

                ListStreamProcessorsResponse listStreamProcessorsResult = rekClient.listStreamProcessors(request);
                for (StreamProcessor streamProcessor : listStreamProcessorsResult.streamProcessors()) {
                        System.out.println("StreamProcessor name - " + streamProcessor.name());
                        System.out.println("Status - " + streamProcessor.status());
                }
        }

        private static void describeStreamProcessor(RekognitionClient rekClient, String StreamProcessorName) {
                DescribeStreamProcessorRequest streamProcessorRequest = DescribeStreamProcessorRequest.builder()
                                .name(StreamProcessorName)
                                .build();

                DescribeStreamProcessorResponse describeStreamProcessorResult = rekClient
                                .describeStreamProcessor(streamProcessorRequest);
                System.out.println("Arn - " + describeStreamProcessorResult.streamProcessorArn());
                System.out.println("Input kinesisVideo stream - "
                                + describeStreamProcessorResult.input().kinesisVideoStream().arn());
                System.out.println("Output kinesisData stream - "
                                + describeStreamProcessorResult.output().kinesisDataStream().arn());
                System.out.println("RoleArn - " + describeStreamProcessorResult.roleArn());
                System.out.println(
                                "CollectionId - "
                                                + describeStreamProcessorResult.settings().faceSearch().collectionId());
                System.out.println("Status - " + describeStreamProcessorResult.status());
                System.out.println("Status message - " + describeStreamProcessorResult.statusMessage());
                System.out.println("Creation timestamp - " + describeStreamProcessorResult.creationTimestamp());
                System.out.println("Last update timestamp - " + describeStreamProcessorResult.lastUpdateTimestamp());
        }

        private static void startSpecificStreamProcessor(RekognitionClient rekClient, String StreamProcessorName) {
                try {
                        StartStreamProcessorRequest streamProcessorRequest = StartStreamProcessorRequest.builder()
                                        .name(StreamProcessorName)
                                        .build();

                        rekClient.startStreamProcessor(streamProcessorRequest);
                        System.out.println("Stream Processor " + StreamProcessorName + " started.");

                } catch (RekognitionException e) {
                        System.out.println(e.getMessage());
                        System.exit(1);
                }
        }

        private static void processCollection(RekognitionClient rekClient, String StreamProcessorName,
                        String kinInputStream, String kinOutputStream, String collectionName, String role) {
                try {
                        KinesisVideoStream videoStream = KinesisVideoStream.builder()
                                        .arn(kinInputStream)
                                        .build();

                        KinesisDataStream dataStream = KinesisDataStream.builder()
                                        .arn(kinOutputStream)
                                        .build();

                        StreamProcessorOutput processorOutput = StreamProcessorOutput.builder()
                                        .kinesisDataStream(dataStream)
                                        .build();

                        StreamProcessorInput processorInput = StreamProcessorInput.builder()
                                        .kinesisVideoStream(videoStream)
                                        .build();

                        FaceSearchSettings searchSettings = FaceSearchSettings.builder()
                                        .faceMatchThreshold(75f)
                                        .collectionId(collectionName)
                                        .build();

                        StreamProcessorSettings processorSettings = StreamProcessorSettings.builder()
                                        .faceSearch(searchSettings)
                                        .build();

                        CreateStreamProcessorRequest processorRequest = CreateStreamProcessorRequest.builder()
                                        .name(StreamProcessorName)
                                        .input(processorInput)
                                        .output(processorOutput)
                                        .roleArn(role)
                                        .settings(processorSettings)
                                        .build();

                        CreateStreamProcessorResponse response = rekClient.createStreamProcessor(processorRequest);
                        System.out.println("The ARN for the newly create stream processor is "
                                        + response.streamProcessorArn());

                } catch (RekognitionException e) {
                        System.out.println(e.getMessage());
                        System.exit(1);
                }
        }

        private static void deleteSpecificStreamProcessor(RekognitionClient rekClient, String StreamProcessorName) {
                rekClient.stopStreamProcessor(a -> a.name(StreamProcessorName));
                rekClient.deleteStreamProcessor(a -> a.name(StreamProcessorName));
                System.out.println("Stream Processor " + StreamProcessorName + " deleted.");
        }
}

使用流处理器搜索人脸（Java V1 示例）

以下示例代码显示如何使用 Java V1 调用各种流处理器操作 StartStreamProcessor，例如CreateStreamProcessor和。该示例包括一个流处理器管理器类 (StreamManager)，该类提供调用流处理器操作的方法。入门类（Starter）创建一个 StreamManager 对象并调用各种操作。

配置示例:

将 Starter 类成员字段的值设置为所需值。
在 Starter 类函数 main 中，取消注释所需的函数调用。

Starter 类


//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.)

// Starter class. Use to create a StreamManager class
// and call stream processor operations.
package com.amazonaws.samples;
import com.amazonaws.samples.*;

public class Starter {

	public static void main(String[] args) {
		
		
    	String streamProcessorName="Stream Processor Name";
    	String kinesisVideoStreamArn="Kinesis Video Stream Arn";
    	String kinesisDataStreamArn="Kinesis Data Stream Arn";
    	String roleArn="Role Arn";
    	String collectionId="Collection ID";
    	Float matchThreshold=50F;

		try {
			StreamManager sm= new StreamManager(streamProcessorName,
					kinesisVideoStreamArn,
					kinesisDataStreamArn,
					roleArn,
					collectionId,
					matchThreshold);
			//sm.createStreamProcessor();
			//sm.startStreamProcessor();
			//sm.deleteStreamProcessor();
			//sm.deleteStreamProcessor();
			//sm.stopStreamProcessor();
			//sm.listStreamProcessors();
			//sm.describeStreamProcessor();
		}
		catch(Exception e){
			System.out.println(e.getMessage());
		}
	}
}

StreamManager 班级


//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.)

// Stream manager class. Provides methods for calling
// Stream Processor operations.
package com.amazonaws.samples;

import com.amazonaws.services.rekognition.AmazonRekognition;
import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
import com.amazonaws.services.rekognition.model.CreateStreamProcessorRequest;
import com.amazonaws.services.rekognition.model.CreateStreamProcessorResult;
import com.amazonaws.services.rekognition.model.DeleteStreamProcessorRequest;
import com.amazonaws.services.rekognition.model.DeleteStreamProcessorResult;
import com.amazonaws.services.rekognition.model.DescribeStreamProcessorRequest;
import com.amazonaws.services.rekognition.model.DescribeStreamProcessorResult;
import com.amazonaws.services.rekognition.model.FaceSearchSettings;
import com.amazonaws.services.rekognition.model.KinesisDataStream;
import com.amazonaws.services.rekognition.model.KinesisVideoStream;
import com.amazonaws.services.rekognition.model.ListStreamProcessorsRequest;
import com.amazonaws.services.rekognition.model.ListStreamProcessorsResult;
import com.amazonaws.services.rekognition.model.StartStreamProcessorRequest;
import com.amazonaws.services.rekognition.model.StartStreamProcessorResult;
import com.amazonaws.services.rekognition.model.StopStreamProcessorRequest;
import com.amazonaws.services.rekognition.model.StopStreamProcessorResult;
import com.amazonaws.services.rekognition.model.StreamProcessor;
import com.amazonaws.services.rekognition.model.StreamProcessorInput;
import com.amazonaws.services.rekognition.model.StreamProcessorOutput;
import com.amazonaws.services.rekognition.model.StreamProcessorSettings;

public class StreamManager {

    private String streamProcessorName;
    private String kinesisVideoStreamArn;
    private String kinesisDataStreamArn;
    private String roleArn;
    private String collectionId;
    private float matchThreshold;

    private AmazonRekognition rekognitionClient;
    

    public StreamManager(String spName,
    		String kvStreamArn,
    		String kdStreamArn,
    		String iamRoleArn,
    		String collId,
    		Float threshold){
    	streamProcessorName=spName;
    	kinesisVideoStreamArn=kvStreamArn;
    	kinesisDataStreamArn=kdStreamArn;
    	roleArn=iamRoleArn;
    	collectionId=collId;
    	matchThreshold=threshold;
    	rekognitionClient=AmazonRekognitionClientBuilder.defaultClient();
    	
    }
    
    public void createStreamProcessor() {
    	//Setup input parameters
        KinesisVideoStream kinesisVideoStream = new KinesisVideoStream().withArn(kinesisVideoStreamArn);
        StreamProcessorInput streamProcessorInput =
                new StreamProcessorInput().withKinesisVideoStream(kinesisVideoStream);
        KinesisDataStream kinesisDataStream = new KinesisDataStream().withArn(kinesisDataStreamArn);
        StreamProcessorOutput streamProcessorOutput =
                new StreamProcessorOutput().withKinesisDataStream(kinesisDataStream);
        FaceSearchSettings faceSearchSettings =
                new FaceSearchSettings().withCollectionId(collectionId).withFaceMatchThreshold(matchThreshold);
        StreamProcessorSettings streamProcessorSettings =
                new StreamProcessorSettings().withFaceSearch(faceSearchSettings);

        //Create the stream processor
        CreateStreamProcessorResult createStreamProcessorResult = rekognitionClient.createStreamProcessor(
                new CreateStreamProcessorRequest().withInput(streamProcessorInput).withOutput(streamProcessorOutput)
                        .withSettings(streamProcessorSettings).withRoleArn(roleArn).withName(streamProcessorName));

        //Display result
        System.out.println("Stream Processor " + streamProcessorName + " created.");
        System.out.println("StreamProcessorArn - " + createStreamProcessorResult.getStreamProcessorArn());
    }

    public void startStreamProcessor() {
        StartStreamProcessorResult startStreamProcessorResult =
                rekognitionClient.startStreamProcessor(new StartStreamProcessorRequest().withName(streamProcessorName));
        System.out.println("Stream Processor " + streamProcessorName + " started.");
    }

    public void stopStreamProcessor() {
        StopStreamProcessorResult stopStreamProcessorResult =
                rekognitionClient.stopStreamProcessor(new StopStreamProcessorRequest().withName(streamProcessorName));
        System.out.println("Stream Processor " + streamProcessorName + " stopped.");
    }

    public void deleteStreamProcessor() {
        DeleteStreamProcessorResult deleteStreamProcessorResult = rekognitionClient
                .deleteStreamProcessor(new DeleteStreamProcessorRequest().withName(streamProcessorName));
        System.out.println("Stream Processor " + streamProcessorName + " deleted.");
    }

    public void describeStreamProcessor() {
        DescribeStreamProcessorResult describeStreamProcessorResult = rekognitionClient
                .describeStreamProcessor(new DescribeStreamProcessorRequest().withName(streamProcessorName));

        //Display various stream processor attributes.
        System.out.println("Arn - " + describeStreamProcessorResult.getStreamProcessorArn());
        System.out.println("Input kinesisVideo stream - "
                + describeStreamProcessorResult.getInput().getKinesisVideoStream().getArn());
        System.out.println("Output kinesisData stream - "
                + describeStreamProcessorResult.getOutput().getKinesisDataStream().getArn());
        System.out.println("RoleArn - " + describeStreamProcessorResult.getRoleArn());
        System.out.println(
                "CollectionId - " + describeStreamProcessorResult.getSettings().getFaceSearch().getCollectionId());
        System.out.println("Status - " + describeStreamProcessorResult.getStatus());
        System.out.println("Status message - " + describeStreamProcessorResult.getStatusMessage());
        System.out.println("Creation timestamp - " + describeStreamProcessorResult.getCreationTimestamp());
        System.out.println("Last update timestamp - " + describeStreamProcessorResult.getLastUpdateTimestamp());
    }

    public void listStreamProcessors() {
        ListStreamProcessorsResult listStreamProcessorsResult =
                rekognitionClient.listStreamProcessors(new ListStreamProcessorsRequest().withMaxResults(100));

        //List all stream processors (and state) returned from Rekognition
        for (StreamProcessor streamProcessor : listStreamProcessorsResult.getStreamProcessors()) {
            System.out.println("StreamProcessor name - " + streamProcessor.getName());
            System.out.println("Status - " + streamProcessor.getStatus());
        }
    }
}

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读取分析结果