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# 在流视频中搜索人脸
<a name="rekognition-video-stream-processor-search-faces"></a>

**注意**  
新客户不再可以使用流媒体视频和批量图像分析。有关更多信息，请参阅 [亚马逊 Rekognition 功能可用性变更](rekognition-availability-changes.md)。  
**此更改不会影响其他 Amazon Rekognition 功能的可用性。**

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](collections.md)。

**Topics**
+ [创建 Amazon Rekognition Video 人脸搜索流处理器](#streaming-video-creating-stream-processor)
+ [启动 Amazon Rekognition Video 人脸搜索流处理器](#streaming-video-starting-stream-processor)
+ [使用流处理器搜索人脸（Java V2 示例）](#using-stream-processors-v2)
+ [使用流处理器搜索人脸（Java V1 示例）](#using-stream-processors)
+ [读取流视频分析结果](streaming-video-kinesis-output.md)
+ [在本地使用 Kinesis 视频流显示 Rekognition 结果](displaying-rekognition-results-locally.md)
+ [了解 Kinesis 人脸识别 JSON 帧记录](streaming-video-kinesis-output-reference.md)

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

![该图描绘了使用 Amazon Rekognition Video 处理来自 Amazon Kinesis 的视频流的工作流。](http://docs.aws.amazon.com/zh_cn/rekognition/latest/dg/images/VideoRekognitionStream.png)


## 创建 Amazon Rekognition Video 人脸搜索流处理器
<a name="streaming-video-creating-stream-processor"></a>

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](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_CreateStreamProcessor.html)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
<a name="streaming-video-starting-stream-processor"></a>

您可使用在 `CreateStreamProcessor` 中指定的流处理器名称来调用 [StartStreamProcessor](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartStreamProcessor.html)，由此开始分析流视频。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）
<a name="using-stream-processors-v2"></a>

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](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartStreamProcessor.html)，例如[CreateStreamProcessor](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_CreateStreamProcessor.html)和。

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/CreateStreamProcessor.java)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.
 * <p>
 * For more information, see the following documentation topic:
 * <p>
 * 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）
<a name="using-stream-processors"></a>

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](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartStreamProcessor.html)，例如[CreateStreamProcessor](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_CreateStreamProcessor.html)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:**

1. 将 Starter 类成员字段的值设置为所需值。

1. 在 Starter 类函数 `main` 中，取消注释所需的函数调用。

### Starter 类
<a name="streaming-started"></a>

```
//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
<a name="streaming-manager"></a>

```
//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());
        }
    }
}
```