Esempi di utilizzo di Amazon SDK Rekognition per Java 2.x

I seguenti esempi di codice mostrano come eseguire azioni e implementare scenari comuni utilizzando Amazon AWS SDK for Java 2.x Rekognition.

Le operazioni sono estratti di codice da programmi più grandi e devono essere eseguite nel contesto. Sebbene le operazioni mostrino come richiamare le singole funzioni del servizio, è possibile visualizzarle contestualizzate negli scenari correlati e negli esempi tra servizi.

Scenari: esempi di codice che mostrano come eseguire un'attività specifica richiamando più funzioni all'interno dello stesso servizio.

Ogni esempio include un collegamento a GitHub, dove puoi trovare istruzioni su come configurare ed eseguire il codice nel contesto.

Azioni

CompareFaces

Il seguente esempio di codice mostra come utilizzareCompareFaces.

Per ulteriori informazioni, consulta Confronto dei volti nelle immagini.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.CompareFacesRequest;
import software.amazon.awssdk.services.rekognition.model.CompareFacesResponse;
import software.amazon.awssdk.services.rekognition.model.CompareFacesMatch;
import software.amazon.awssdk.services.rekognition.model.ComparedFace;
import software.amazon.awssdk.services.rekognition.model.BoundingBox;
import software.amazon.awssdk.core.SdkBytes;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 CompareFaces {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <pathSource> <pathTarget>

                Where:
                   pathSource - The path to the source image (for example, C:\\AWS\\pic1.png).\s
                    pathTarget - The path to the target image (for example, C:\\AWS\\pic2.png).\s
                """;

        if (args.length != 2) {
            System.out.println(usage);
            System.exit(1);
        }

        Float similarityThreshold = 70F;
        String sourceImage = args[0];
        String targetImage = args[1];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        compareTwoFaces(rekClient, similarityThreshold, sourceImage, targetImage);
        rekClient.close();
    }

    public static void compareTwoFaces(RekognitionClient rekClient, Float similarityThreshold, String sourceImage,
            String targetImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            InputStream tarStream = new FileInputStream(targetImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            SdkBytes targetBytes = SdkBytes.fromInputStream(tarStream);

            // Create an Image object for the source image.
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            Image tarImage = Image.builder()
                    .bytes(targetBytes)
                    .build();

            CompareFacesRequest facesRequest = CompareFacesRequest.builder()
                    .sourceImage(souImage)
                    .targetImage(tarImage)
                    .similarityThreshold(similarityThreshold)
                    .build();

            // Compare the two images.
            CompareFacesResponse compareFacesResult = rekClient.compareFaces(facesRequest);
            List<CompareFacesMatch> faceDetails = compareFacesResult.faceMatches();
            for (CompareFacesMatch match : faceDetails) {
                ComparedFace face = match.face();
                BoundingBox position = face.boundingBox();
                System.out.println("Face at " + position.left().toString()
                        + " " + position.top()
                        + " matches with " + face.confidence().toString()
                        + "% confidence.");

            }
            List<ComparedFace> uncompared = compareFacesResult.unmatchedFaces();
            System.out.println("There was " + uncompared.size() + " face(s) that did not match");
            System.out.println("Source image rotation: " + compareFacesResult.sourceImageOrientationCorrection());
            System.out.println("target image rotation: " + compareFacesResult.targetImageOrientationCorrection());

        } catch (RekognitionException | FileNotFoundException e) {
            System.out.println("Failed to load source image " + sourceImage);
            System.exit(1);
        }
    }
}

• Per API i dettagli, vedi CompareFaces AWS SDK for Java 2.xAPIReference.

CreateCollection

Il seguente esempio di codice mostra come utilizzareCreateCollection.

Per ulteriori informazioni, consulta Creazione di una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.CreateCollectionResponse;
import software.amazon.awssdk.services.rekognition.model.CreateCollectionRequest;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;

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

                Usage:    <collectionName>\s

                Where:
                   collectionName - The name of the collection.\s
                """;

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

        String collectionId = args[0];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Creating collection: " + collectionId);
        createMyCollection(rekClient, collectionId);
        rekClient.close();
    }

    public static void createMyCollection(RekognitionClient rekClient, String collectionId) {
        try {
            CreateCollectionRequest collectionRequest = CreateCollectionRequest.builder()
                    .collectionId(collectionId)
                    .build();

            CreateCollectionResponse collectionResponse = rekClient.createCollection(collectionRequest);
            System.out.println("CollectionArn: " + collectionResponse.collectionArn());
            System.out.println("Status code: " + collectionResponse.statusCode().toString());

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

• Per API i dettagli, vedi CreateCollection AWS SDK for Java 2.xAPIReference.

DeleteCollection

Il seguente esempio di codice mostra come utilizzareDeleteCollection.

Per ulteriori informazioni, consulta Eliminazione di una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.DeleteCollectionRequest;
import software.amazon.awssdk.services.rekognition.model.DeleteCollectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;

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

                Usage:    <collectionId>\s

                Where:
                   collectionId - The id of the collection to delete.\s
                """;

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

        String collectionId = args[0];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Deleting collection: " + collectionId);
        deleteMyCollection(rekClient, collectionId);
        rekClient.close();
    }

    public static void deleteMyCollection(RekognitionClient rekClient, String collectionId) {
        try {
            DeleteCollectionRequest deleteCollectionRequest = DeleteCollectionRequest.builder()
                    .collectionId(collectionId)
                    .build();

            DeleteCollectionResponse deleteCollectionResponse = rekClient.deleteCollection(deleteCollectionRequest);
            System.out.println(collectionId + ": " + deleteCollectionResponse.statusCode().toString());

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

• Per API i dettagli, vedi DeleteCollection AWS SDK for Java 2.xAPIReference.

DeleteFaces

Il seguente esempio di codice mostra come utilizzareDeleteFaces.

Per ulteriori informazioni, consulta Eliminazione dei volti da una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.DeleteFacesRequest;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;

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

                Usage:    <collectionId> <faceId>\s

                Where:
                   collectionId - The id of the collection from which faces are deleted.\s

                   faceId - The id of the face to delete.\s
                """;

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

        String collectionId = args[0];
        String faceId = args[1];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Deleting collection: " + collectionId);
        deleteFacesCollection(rekClient, collectionId, faceId);
        rekClient.close();
    }

    public static void deleteFacesCollection(RekognitionClient rekClient,
            String collectionId,
            String faceId) {

        try {
            DeleteFacesRequest deleteFacesRequest = DeleteFacesRequest.builder()
                    .collectionId(collectionId)
                    .faceIds(faceId)
                    .build();

            rekClient.deleteFaces(deleteFacesRequest);
            System.out.println("The face was deleted from the collection.");

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

• Per API i dettagli, vedi DeleteFaces AWS SDK for Java 2.xAPIReference.

DescribeCollection

Il seguente esempio di codice mostra come utilizzareDescribeCollection.

Per ulteriori informazioni, consulta Descrizione di una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.DescribeCollectionRequest;
import software.amazon.awssdk.services.rekognition.model.DescribeCollectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;

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

                Usage:    <collectionName>

                Where:
                   collectionName - The name of the Amazon Rekognition collection.\s
                """;

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

        String collectionName = args[0];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        describeColl(rekClient, collectionName);
        rekClient.close();
    }

    public static void describeColl(RekognitionClient rekClient, String collectionName) {
        try {
            DescribeCollectionRequest describeCollectionRequest = DescribeCollectionRequest.builder()
                    .collectionId(collectionName)
                    .build();

            DescribeCollectionResponse describeCollectionResponse = rekClient
                    .describeCollection(describeCollectionRequest);
            System.out.println("Collection Arn : " + describeCollectionResponse.collectionARN());
            System.out.println("Created : " + describeCollectionResponse.creationTimestamp().toString());

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

• Per API i dettagli, vedi DescribeCollection AWS SDK for Java 2.xAPIReference.

DetectFaces

Il seguente esempio di codice mostra come utilizzareDetectFaces.

Per ulteriori informazioni, consulta Rilevamento dei volti in un'immagine.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.DetectFacesRequest;
import software.amazon.awssdk.services.rekognition.model.DetectFacesResponse;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.Attribute;
import software.amazon.awssdk.services.rekognition.model.FaceDetail;
import software.amazon.awssdk.services.rekognition.model.AgeRange;
import software.amazon.awssdk.core.SdkBytes;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 DetectFaces {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <sourceImage>

                Where:
                   sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s
                """;

        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)
                .build();

        detectFacesinImage(rekClient, sourceImage);
        rekClient.close();
    }

    public static void detectFacesinImage(RekognitionClient rekClient, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);

            // Create an Image object for the source image.
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            DetectFacesRequest facesRequest = DetectFacesRequest.builder()
                    .attributes(Attribute.ALL)
                    .image(souImage)
                    .build();

            DetectFacesResponse facesResponse = rekClient.detectFaces(facesRequest);
            List<FaceDetail> faceDetails = facesResponse.faceDetails();
            for (FaceDetail face : faceDetails) {
                AgeRange ageRange = face.ageRange();
                System.out.println("The detected face is estimated to be between "
                        + ageRange.low().toString() + " and " + ageRange.high().toString()
                        + " years old.");

                System.out.println("There is a smile : " + face.smile().value().toString());
            }

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

• Per API i dettagli, vedi DetectFaces AWS SDK for Java 2.xAPIReference.

DetectLabels

Il seguente esempio di codice mostra come utilizzareDetectLabels.

Per ulteriori informazioni, consulta Rilevamento delle etichette in un'immagine.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.core.SdkBytes;
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 java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 = """

                Usage:    <sourceImage>

                Where:
                   sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s
                """;

        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)
                .build();

        detectImageLabels(rekClient, sourceImage);
        rekClient.close();
    }

    public static void detectImageLabels(RekognitionClient rekClient, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);

            // Create an Image object for the source image.
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            DetectLabelsRequest detectLabelsRequest = DetectLabelsRequest.builder()
                    .image(souImage)
                    .maxLabels(10)
                    .build();

            DetectLabelsResponse labelsResponse = rekClient.detectLabels(detectLabelsRequest);
            List<Label> 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 | FileNotFoundException e) {
            System.out.println(e.getMessage());
            System.exit(1);
        }
    }
}

• Per API i dettagli, vedi DetectLabels AWS SDK for Java 2.xAPIReference.

DetectModerationLabels

Il seguente esempio di codice mostra come utilizzareDetectModerationLabels.

Per ulteriori informazioni, consulta Rilevamento di immagini non appropriate.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.DetectModerationLabelsRequest;
import software.amazon.awssdk.services.rekognition.model.DetectModerationLabelsResponse;
import software.amazon.awssdk.services.rekognition.model.ModerationLabel;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 DetectModerationLabels {

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

                Usage:    <sourceImage>

                Where:
                   sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s
                """;

        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)
                .build();

        detectModLabels(rekClient, sourceImage);
        rekClient.close();
    }

    public static void detectModLabels(RekognitionClient rekClient, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            DetectModerationLabelsRequest moderationLabelsRequest = DetectModerationLabelsRequest.builder()
                    .image(souImage)
                    .minConfidence(60F)
                    .build();

            DetectModerationLabelsResponse moderationLabelsResponse = rekClient
                    .detectModerationLabels(moderationLabelsRequest);
            List<ModerationLabel> labels = moderationLabelsResponse.moderationLabels();
            System.out.println("Detected labels for image");
            for (ModerationLabel label : labels) {
                System.out.println("Label: " + label.name()
                        + "\n Confidence: " + label.confidence().toString() + "%"
                        + "\n Parent:" + label.parentName());
            }

        } catch (RekognitionException | FileNotFoundException e) {
            e.printStackTrace();
            System.exit(1);
        }
    }
}

• Per API i dettagli, vedi DetectModerationLabels AWS SDK for Java 2.xAPIReference.

DetectText

Il seguente esempio di codice mostra come utilizzareDetectText.

Per ulteriori informazioni, consulta Rilevamento del testo in un'immagine.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.DetectTextRequest;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.DetectTextResponse;
import software.amazon.awssdk.services.rekognition.model.TextDetection;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 DetectText {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <sourceImage>

                Where:
                   sourceImage - The path to the image that contains text (for example, C:\\AWS\\pic1.png).\s
                """;

        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)
                .build();

        detectTextLabels(rekClient, sourceImage);
        rekClient.close();
    }

    public static void detectTextLabels(RekognitionClient rekClient, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            DetectTextRequest textRequest = DetectTextRequest.builder()
                    .image(souImage)
                    .build();

            DetectTextResponse textResponse = rekClient.detectText(textRequest);
            List<TextDetection> textCollection = textResponse.textDetections();
            System.out.println("Detected lines and words");
            for (TextDetection text : textCollection) {
                System.out.println("Detected: " + text.detectedText());
                System.out.println("Confidence: " + text.confidence().toString());
                System.out.println("Id : " + text.id());
                System.out.println("Parent Id: " + text.parentId());
                System.out.println("Type: " + text.type());
                System.out.println();
            }

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

• Per API i dettagli, vedi DetectText AWS SDK for Java 2.xAPIReference.

IndexFaces

Il seguente esempio di codice mostra come utilizzareIndexFaces.

Per ulteriori informazioni, consulta Indicizzazione dei volti in una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.IndexFacesResponse;
import software.amazon.awssdk.services.rekognition.model.IndexFacesRequest;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.QualityFilter;
import software.amazon.awssdk.services.rekognition.model.Attribute;
import software.amazon.awssdk.services.rekognition.model.FaceRecord;
import software.amazon.awssdk.services.rekognition.model.UnindexedFace;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.Reason;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 AddFacesToCollection {
    public static void main(String[] args) {

        final String usage = """

                Usage:     <collectionId> <sourceImage>

                Where:
                    collectionName - The name of the collection.
                    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 collectionId = args[0];
        String sourceImage = args[1];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        addToCollection(rekClient, collectionId, sourceImage);
        rekClient.close();
    }

    public static void addToCollection(RekognitionClient rekClient, String collectionId, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(sourceImage);
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            IndexFacesRequest facesRequest = IndexFacesRequest.builder()
                    .collectionId(collectionId)
                    .image(souImage)
                    .maxFaces(1)
                    .qualityFilter(QualityFilter.AUTO)
                    .detectionAttributes(Attribute.DEFAULT)
                    .build();

            IndexFacesResponse facesResponse = rekClient.indexFaces(facesRequest);
            System.out.println("Results for the image");
            System.out.println("\n Faces indexed:");
            List<FaceRecord> faceRecords = facesResponse.faceRecords();
            for (FaceRecord faceRecord : faceRecords) {
                System.out.println("  Face ID: " + faceRecord.face().faceId());
                System.out.println("  Location:" + faceRecord.faceDetail().boundingBox().toString());
            }

            List<UnindexedFace> unindexedFaces = facesResponse.unindexedFaces();
            System.out.println("Faces not indexed:");
            for (UnindexedFace unindexedFace : unindexedFaces) {
                System.out.println("  Location:" + unindexedFace.faceDetail().boundingBox().toString());
                System.out.println("  Reasons:");
                for (Reason reason : unindexedFace.reasons()) {
                    System.out.println("Reason:  " + reason);
                }
            }

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

• Per API i dettagli, vedi IndexFaces AWS SDK for Java 2.xAPIReference.

ListCollections

Il seguente esempio di codice mostra come utilizzareListCollections.

Per ulteriori informazioni, consulta Creazione dell'elenco delle raccolte.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.ListCollectionsRequest;
import software.amazon.awssdk.services.rekognition.model.ListCollectionsResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
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 ListCollections {
    public static void main(String[] args) {
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Listing collections");
        listAllCollections(rekClient);
        rekClient.close();
    }

    public static void listAllCollections(RekognitionClient rekClient) {
        try {
            ListCollectionsRequest listCollectionsRequest = ListCollectionsRequest.builder()
                    .maxResults(10)
                    .build();

            ListCollectionsResponse response = rekClient.listCollections(listCollectionsRequest);
            List<String> collectionIds = response.collectionIds();
            for (String resultId : collectionIds) {
                System.out.println(resultId);
            }

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

• Per API i dettagli, vedi ListCollections AWS SDK for Java 2.xAPIReference.

ListFaces

Il seguente esempio di codice mostra come utilizzareListFaces.

Per ulteriori informazioni, consulta Creazione dell'elenco dei volti in una raccolta.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.Face;
import software.amazon.awssdk.services.rekognition.model.ListFacesRequest;
import software.amazon.awssdk.services.rekognition.model.ListFacesResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
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 ListFacesInCollection {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <collectionId>

                Where:
                   collectionId - The name of the collection.\s
                """;

        if (args.length < 1) {
            System.out.println(usage);
            System.exit(1);
        }

        String collectionId = args[0];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Faces in collection " + collectionId);
        listFacesCollection(rekClient, collectionId);
        rekClient.close();
    }

    public static void listFacesCollection(RekognitionClient rekClient, String collectionId) {
        try {
            ListFacesRequest facesRequest = ListFacesRequest.builder()
                    .collectionId(collectionId)
                    .maxResults(10)
                    .build();

            ListFacesResponse facesResponse = rekClient.listFaces(facesRequest);
            List<Face> faces = facesResponse.faces();
            for (Face face : faces) {
                System.out.println("Confidence level there is a face: " + face.confidence());
                System.out.println("The face Id value is " + face.faceId());
            }

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

• Per API i dettagli, vedi ListFaces AWS SDK for Java 2.xAPIReference.

RecognizeCelebrities

Il seguente esempio di codice mostra come utilizzareRecognizeCelebrities.

Per ulteriori informazioni, consulta Riconoscimento delle celebrità in un'immagine.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

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;

/**
 * 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:    <sourceImage>

                Where:
                   sourceImage - The path to the image (for example, C:\\AWS\\pic1.png).\s
                """;

        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)
                .build();

        System.out.println("Locating celebrities in " + sourceImage);
        recognizeAllCelebrities(rekClient, sourceImage);
        rekClient.close();
    }

    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<Celebrity> 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);
        }
    }
}

• Per API i dettagli, vedi RecognizeCelebrities AWS SDK for Java 2.xAPIReference.

SearchFaces

Il seguente esempio di codice mostra come utilizzareSearchFaces.

Per ulteriori informazioni, consulta Ricerca di un volto (ID volto).

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.SearchFacesByImageRequest;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.SearchFacesByImageResponse;
import software.amazon.awssdk.services.rekognition.model.FaceMatch;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.InputStream;
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 SearchFaceMatchingImageCollection {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <collectionId> <sourceImage>

                Where:
                   collectionId - The id of the collection. \s
                   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 collectionId = args[0];
        String sourceImage = args[1];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Searching for a face in a collections");
        searchFaceInCollection(rekClient, collectionId, sourceImage);
        rekClient.close();
    }

    public static void searchFaceInCollection(RekognitionClient rekClient, String collectionId, String sourceImage) {
        try {
            InputStream sourceStream = new FileInputStream(new File(sourceImage));
            SdkBytes sourceBytes = SdkBytes.fromInputStream(sourceStream);
            Image souImage = Image.builder()
                    .bytes(sourceBytes)
                    .build();

            SearchFacesByImageRequest facesByImageRequest = SearchFacesByImageRequest.builder()
                    .image(souImage)
                    .maxFaces(10)
                    .faceMatchThreshold(70F)
                    .collectionId(collectionId)
                    .build();

            SearchFacesByImageResponse imageResponse = rekClient.searchFacesByImage(facesByImageRequest);
            System.out.println("Faces matching in the collection");
            List<FaceMatch> faceImageMatches = imageResponse.faceMatches();
            for (FaceMatch face : faceImageMatches) {
                System.out.println("The similarity level is  " + face.similarity());
                System.out.println();
            }

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

• Per API i dettagli, vedi SearchFaces AWS SDK for Java 2.xAPIReference.

SearchFacesByImage

Il seguente esempio di codice mostra come utilizzareSearchFacesByImage.

Per ulteriori informazioni, consulta Ricerca di un volto (immagine).

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.SearchFacesRequest;
import software.amazon.awssdk.services.rekognition.model.SearchFacesResponse;
import software.amazon.awssdk.services.rekognition.model.FaceMatch;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
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 SearchFaceMatchingIdCollection {
    public static void main(String[] args) {
        final String usage = """

                Usage:    <collectionId> <sourceImage>

                Where:
                   collectionId - The id of the collection. \s
                   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 collectionId = args[0];
        String faceId = args[1];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        System.out.println("Searching for a face in a collections");
        searchFacebyId(rekClient, collectionId, faceId);
        rekClient.close();
    }

    public static void searchFacebyId(RekognitionClient rekClient, String collectionId, String faceId) {
        try {
            SearchFacesRequest searchFacesRequest = SearchFacesRequest.builder()
                    .collectionId(collectionId)
                    .faceId(faceId)
                    .faceMatchThreshold(70F)
                    .maxFaces(2)
                    .build();

            SearchFacesResponse imageResponse = rekClient.searchFaces(searchFacesRequest);
            System.out.println("Faces matching in the collection");
            List<FaceMatch> faceImageMatches = imageResponse.faceMatches();
            for (FaceMatch face : faceImageMatches) {
                System.out.println("The similarity level is  " + face.similarity());
                System.out.println();
            }

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

• Per API i dettagli, vedi SearchFacesByImage AWS SDK for Java 2.xAPIReference.

Scenari

Rilevamento delle informazioni nei video

L'esempio di codice seguente mostra come:

• Avvia i processi di Amazon Rekognition per rilevare elementi come persone, oggetti e testo nei video.

• Controlla lo stato del processo fino al suo termine.

• Crea un output con l'elenco degli elementi rilevati da ciascun processo.

SDKper Java 2.x

Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Ottieni risultati relativi alle celebrità da un video che si trova in un bucket Amazon S3.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartCelebrityRecognitionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.CelebrityRecognitionSortBy;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.CelebrityRecognition;
import software.amazon.awssdk.services.rekognition.model.CelebrityDetail;
import software.amazon.awssdk.services.rekognition.model.StartCelebrityRecognitionRequest;
import software.amazon.awssdk.services.rekognition.model.GetCelebrityRecognitionRequest;
import software.amazon.awssdk.services.rekognition.model.GetCelebrityRecognitionResponse;
import java.util.List;

/**
 * To run this code example, ensure that you perform the Prerequisites as stated
 * in the Amazon Rekognition Guide:
 * https://docs.aws.amazon.com/rekognition/latest/dg/video-analyzing-with-sqs.html
 *
 * Also, ensure that set up your development environment, including your
 * credentials.
 *
 * For information, see this documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */

public class VideoCelebrityDetection {
    private static String startJobId = "";

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

                Usage:    <bucket> <video> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of video (for example, people.mp4).\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

        if (args.length != 4) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucket = args[0];
        String video = args[1];
        String topicArn = args[2];
        String roleArn = args[3];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startCelebrityDetection(rekClient, channel, bucket, video);
        getCelebrityDetectionResults(rekClient);
        System.out.println("This example is done!");
        rekClient.close();
    }

    public static void startCelebrityDetection(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartCelebrityRecognitionRequest recognitionRequest = StartCelebrityRecognitionRequest.builder()
                    .jobTag("Celebrities")
                    .notificationChannel(channel)
                    .video(vidOb)
                    .build();

            StartCelebrityRecognitionResponse startCelebrityRecognitionResult = rekClient
                    .startCelebrityRecognition(recognitionRequest);
            startJobId = startCelebrityRecognitionResult.jobId();

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

    public static void getCelebrityDetectionResults(RekognitionClient rekClient) {

        try {
            String paginationToken = null;
            GetCelebrityRecognitionResponse recognitionResponse = null;
            boolean finished = false;
            String status;
            int yy = 0;

            do {
                if (recognitionResponse != null)
                    paginationToken = recognitionResponse.nextToken();

                GetCelebrityRecognitionRequest recognitionRequest = GetCelebrityRecognitionRequest.builder()
                        .jobId(startJobId)
                        .nextToken(paginationToken)
                        .sortBy(CelebrityRecognitionSortBy.TIMESTAMP)
                        .maxResults(10)
                        .build();

                // Wait until the job succeeds
                while (!finished) {
                    recognitionResponse = rekClient.getCelebrityRecognition(recognitionRequest);
                    status = recognitionResponse.jobStatusAsString();

                    if (status.compareTo("SUCCEEDED") == 0)
                        finished = true;
                    else {
                        System.out.println(yy + " status is: " + status);
                        Thread.sleep(1000);
                    }
                    yy++;
                }

                finished = false;

                // Proceed when the job is done - otherwise VideoMetadata is null.
                VideoMetadata videoMetaData = recognitionResponse.videoMetadata();
                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());
                System.out.println("Job");

                List<CelebrityRecognition> celebs = recognitionResponse.celebrities();
                for (CelebrityRecognition celeb : celebs) {
                    long seconds = celeb.timestamp() / 1000;
                    System.out.print("Sec: " + seconds + " ");
                    CelebrityDetail details = celeb.celebrity();
                    System.out.println("Name: " + details.name());
                    System.out.println("Id: " + details.id());
                    System.out.println();
                }

            } while (recognitionResponse.nextToken() != null);

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

Rileva le etichette in un video tramite un'operazione di rilevamento delle etichette.

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.JsonMappingException;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.StartLabelDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartLabelDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.GetLabelDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.GetLabelDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.LabelDetectionSortBy;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.LabelDetection;
import software.amazon.awssdk.services.rekognition.model.Label;
import software.amazon.awssdk.services.rekognition.model.Instance;
import software.amazon.awssdk.services.rekognition.model.Parent;
import software.amazon.awssdk.services.sqs.SqsClient;
import software.amazon.awssdk.services.sqs.model.Message;
import software.amazon.awssdk.services.sqs.model.ReceiveMessageRequest;
import software.amazon.awssdk.services.sqs.model.DeleteMessageRequest;
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 VideoDetect {
    private static String startJobId = "";

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

                Usage:    <bucket> <video> <queueUrl> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of the video (for example, people.mp4).\s
                   queueUrl- The URL of a SQS queue.\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

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

        String bucket = args[0];
        String video = args[1];
        String queueUrl = args[2];
        String topicArn = args[3];
        String roleArn = args[4];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        SqsClient sqs = SqsClient.builder()
                .region(Region.US_EAST_1)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startLabels(rekClient, channel, bucket, video);
        getLabelJob(rekClient, sqs, queueUrl);
        System.out.println("This example is done!");
        sqs.close();
        rekClient.close();
    }

    public static void startLabels(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartLabelDetectionRequest labelDetectionRequest = StartLabelDetectionRequest.builder()
                    .jobTag("DetectingLabels")
                    .notificationChannel(channel)
                    .video(vidOb)
                    .minConfidence(50F)
                    .build();

            StartLabelDetectionResponse labelDetectionResponse = rekClient.startLabelDetection(labelDetectionRequest);
            startJobId = labelDetectionResponse.jobId();

            boolean ans = true;
            String status = "";
            int yy = 0;
            while (ans) {

                GetLabelDetectionRequest detectionRequest = GetLabelDetectionRequest.builder()
                        .jobId(startJobId)
                        .maxResults(10)
                        .build();

                GetLabelDetectionResponse result = rekClient.getLabelDetection(detectionRequest);
                status = result.jobStatusAsString();

                if (status.compareTo("SUCCEEDED") == 0)
                    ans = false;
                else
                    System.out.println(yy + " status is: " + status);

                Thread.sleep(1000);
                yy++;
            }

            System.out.println(startJobId + " status is: " + status);

        } catch (RekognitionException | InterruptedException e) {
            e.getMessage();
            System.exit(1);
        }
    }

    public static void getLabelJob(RekognitionClient rekClient, SqsClient sqs, String queueUrl) {
        List<Message> messages;
        ReceiveMessageRequest messageRequest = ReceiveMessageRequest.builder()
                .queueUrl(queueUrl)
                .build();

        try {
            messages = sqs.receiveMessage(messageRequest).messages();

            if (!messages.isEmpty()) {
                for (Message message : messages) {
                    String notification = message.body();

                    // Get the status and job id from the notification
                    ObjectMapper mapper = new ObjectMapper();
                    JsonNode jsonMessageTree = mapper.readTree(notification);
                    JsonNode messageBodyText = jsonMessageTree.get("Message");
                    ObjectMapper operationResultMapper = new ObjectMapper();
                    JsonNode jsonResultTree = operationResultMapper.readTree(messageBodyText.textValue());
                    JsonNode operationJobId = jsonResultTree.get("JobId");
                    JsonNode operationStatus = jsonResultTree.get("Status");
                    System.out.println("Job found in JSON is " + operationJobId);

                    DeleteMessageRequest deleteMessageRequest = DeleteMessageRequest.builder()
                            .queueUrl(queueUrl)
                            .build();

                    String jobId = operationJobId.textValue();
                    if (startJobId.compareTo(jobId) == 0) {
                        System.out.println("Job id: " + operationJobId);
                        System.out.println("Status : " + operationStatus.toString());

                        if (operationStatus.asText().equals("SUCCEEDED"))
                            getResultsLabels(rekClient);
                        else
                            System.out.println("Video analysis failed");

                        sqs.deleteMessage(deleteMessageRequest);
                    } else {
                        System.out.println("Job received was not job " + startJobId);
                        sqs.deleteMessage(deleteMessageRequest);
                    }
                }
            }

        } catch (RekognitionException e) {
            e.getMessage();
            System.exit(1);
        } catch (JsonMappingException e) {
            e.printStackTrace();
        } catch (JsonProcessingException e) {
            e.printStackTrace();
        }
    }

    // Gets the job results by calling GetLabelDetection
    private static void getResultsLabels(RekognitionClient rekClient) {

        int maxResults = 10;
        String paginationToken = null;
        GetLabelDetectionResponse labelDetectionResult = null;

        try {
            do {
                if (labelDetectionResult != null)
                    paginationToken = labelDetectionResult.nextToken();

                GetLabelDetectionRequest labelDetectionRequest = GetLabelDetectionRequest.builder()
                        .jobId(startJobId)
                        .sortBy(LabelDetectionSortBy.TIMESTAMP)
                        .maxResults(maxResults)
                        .nextToken(paginationToken)
                        .build();

                labelDetectionResult = rekClient.getLabelDetection(labelDetectionRequest);
                VideoMetadata videoMetaData = labelDetectionResult.videoMetadata();
                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());

                List<LabelDetection> detectedLabels = labelDetectionResult.labels();
                for (LabelDetection detectedLabel : detectedLabels) {
                    long seconds = detectedLabel.timestamp();
                    Label label = detectedLabel.label();
                    System.out.println("Millisecond: " + seconds + " ");

                    System.out.println("   Label:" + label.name());
                    System.out.println("   Confidence:" + detectedLabel.label().confidence().toString());

                    List<Instance> instances = label.instances();
                    System.out.println("   Instances of " + label.name());

                    if (instances.isEmpty()) {
                        System.out.println("        " + "None");
                    } else {
                        for (Instance instance : instances) {
                            System.out.println("        Confidence: " + instance.confidence().toString());
                            System.out.println("        Bounding box: " + instance.boundingBox().toString());
                        }
                    }
                    System.out.println("   Parent labels for " + label.name() + ":");
                    List<Parent> parents = label.parents();

                    if (parents.isEmpty()) {
                        System.out.println("        None");
                    } else {
                        for (Parent parent : parents) {
                            System.out.println("   " + parent.name());
                        }
                    }
                    System.out.println();
                }
            } while (labelDetectionResult != null && labelDetectionResult.nextToken() != null);

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

Rileva i volti in un video archiviato in un bucket Amazon S3.

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.JsonMappingException;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.StartLabelDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartLabelDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.GetLabelDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.GetLabelDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.LabelDetectionSortBy;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.LabelDetection;
import software.amazon.awssdk.services.rekognition.model.Label;
import software.amazon.awssdk.services.rekognition.model.Instance;
import software.amazon.awssdk.services.rekognition.model.Parent;
import software.amazon.awssdk.services.sqs.SqsClient;
import software.amazon.awssdk.services.sqs.model.Message;
import software.amazon.awssdk.services.sqs.model.ReceiveMessageRequest;
import software.amazon.awssdk.services.sqs.model.DeleteMessageRequest;
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 VideoDetect {
    private static String startJobId = "";

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

                Usage:    <bucket> <video> <queueUrl> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of the video (for example, people.mp4).\s
                   queueUrl- The URL of a SQS queue.\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

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

        String bucket = args[0];
        String video = args[1];
        String queueUrl = args[2];
        String topicArn = args[3];
        String roleArn = args[4];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        SqsClient sqs = SqsClient.builder()
                .region(Region.US_EAST_1)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startLabels(rekClient, channel, bucket, video);
        getLabelJob(rekClient, sqs, queueUrl);
        System.out.println("This example is done!");
        sqs.close();
        rekClient.close();
    }

    public static void startLabels(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartLabelDetectionRequest labelDetectionRequest = StartLabelDetectionRequest.builder()
                    .jobTag("DetectingLabels")
                    .notificationChannel(channel)
                    .video(vidOb)
                    .minConfidence(50F)
                    .build();

            StartLabelDetectionResponse labelDetectionResponse = rekClient.startLabelDetection(labelDetectionRequest);
            startJobId = labelDetectionResponse.jobId();

            boolean ans = true;
            String status = "";
            int yy = 0;
            while (ans) {

                GetLabelDetectionRequest detectionRequest = GetLabelDetectionRequest.builder()
                        .jobId(startJobId)
                        .maxResults(10)
                        .build();

                GetLabelDetectionResponse result = rekClient.getLabelDetection(detectionRequest);
                status = result.jobStatusAsString();

                if (status.compareTo("SUCCEEDED") == 0)
                    ans = false;
                else
                    System.out.println(yy + " status is: " + status);

                Thread.sleep(1000);
                yy++;
            }

            System.out.println(startJobId + " status is: " + status);

        } catch (RekognitionException | InterruptedException e) {
            e.getMessage();
            System.exit(1);
        }
    }

    public static void getLabelJob(RekognitionClient rekClient, SqsClient sqs, String queueUrl) {
        List<Message> messages;
        ReceiveMessageRequest messageRequest = ReceiveMessageRequest.builder()
                .queueUrl(queueUrl)
                .build();

        try {
            messages = sqs.receiveMessage(messageRequest).messages();

            if (!messages.isEmpty()) {
                for (Message message : messages) {
                    String notification = message.body();

                    // Get the status and job id from the notification
                    ObjectMapper mapper = new ObjectMapper();
                    JsonNode jsonMessageTree = mapper.readTree(notification);
                    JsonNode messageBodyText = jsonMessageTree.get("Message");
                    ObjectMapper operationResultMapper = new ObjectMapper();
                    JsonNode jsonResultTree = operationResultMapper.readTree(messageBodyText.textValue());
                    JsonNode operationJobId = jsonResultTree.get("JobId");
                    JsonNode operationStatus = jsonResultTree.get("Status");
                    System.out.println("Job found in JSON is " + operationJobId);

                    DeleteMessageRequest deleteMessageRequest = DeleteMessageRequest.builder()
                            .queueUrl(queueUrl)
                            .build();

                    String jobId = operationJobId.textValue();
                    if (startJobId.compareTo(jobId) == 0) {
                        System.out.println("Job id: " + operationJobId);
                        System.out.println("Status : " + operationStatus.toString());

                        if (operationStatus.asText().equals("SUCCEEDED"))
                            getResultsLabels(rekClient);
                        else
                            System.out.println("Video analysis failed");

                        sqs.deleteMessage(deleteMessageRequest);
                    } else {
                        System.out.println("Job received was not job " + startJobId);
                        sqs.deleteMessage(deleteMessageRequest);
                    }
                }
            }

        } catch (RekognitionException e) {
            e.getMessage();
            System.exit(1);
        } catch (JsonMappingException e) {
            e.printStackTrace();
        } catch (JsonProcessingException e) {
            e.printStackTrace();
        }
    }

    // Gets the job results by calling GetLabelDetection
    private static void getResultsLabels(RekognitionClient rekClient) {

        int maxResults = 10;
        String paginationToken = null;
        GetLabelDetectionResponse labelDetectionResult = null;

        try {
            do {
                if (labelDetectionResult != null)
                    paginationToken = labelDetectionResult.nextToken();

                GetLabelDetectionRequest labelDetectionRequest = GetLabelDetectionRequest.builder()
                        .jobId(startJobId)
                        .sortBy(LabelDetectionSortBy.TIMESTAMP)
                        .maxResults(maxResults)
                        .nextToken(paginationToken)
                        .build();

                labelDetectionResult = rekClient.getLabelDetection(labelDetectionRequest);
                VideoMetadata videoMetaData = labelDetectionResult.videoMetadata();
                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());

                List<LabelDetection> detectedLabels = labelDetectionResult.labels();
                for (LabelDetection detectedLabel : detectedLabels) {
                    long seconds = detectedLabel.timestamp();
                    Label label = detectedLabel.label();
                    System.out.println("Millisecond: " + seconds + " ");

                    System.out.println("   Label:" + label.name());
                    System.out.println("   Confidence:" + detectedLabel.label().confidence().toString());

                    List<Instance> instances = label.instances();
                    System.out.println("   Instances of " + label.name());

                    if (instances.isEmpty()) {
                        System.out.println("        " + "None");
                    } else {
                        for (Instance instance : instances) {
                            System.out.println("        Confidence: " + instance.confidence().toString());
                            System.out.println("        Bounding box: " + instance.boundingBox().toString());
                        }
                    }
                    System.out.println("   Parent labels for " + label.name() + ":");
                    List<Parent> parents = label.parents();

                    if (parents.isEmpty()) {
                        System.out.println("        None");
                    } else {
                        for (Parent parent : parents) {
                            System.out.println("   " + parent.name());
                        }
                    }
                    System.out.println();
                }
            } while (labelDetectionResult != null && labelDetectionResult.nextToken() != null);

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

Rileva contenuti non appropriati o offensivi in un video archiviato in un bucket Amazon S3.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartContentModerationRequest;
import software.amazon.awssdk.services.rekognition.model.StartContentModerationResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.GetContentModerationResponse;
import software.amazon.awssdk.services.rekognition.model.GetContentModerationRequest;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.ContentModerationDetection;
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 VideoDetectInappropriate {
    private static String startJobId = "";

    public static void main(String[] args) {

        final String usage = """

                Usage:    <bucket> <video> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of video (for example, people.mp4).\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

        if (args.length != 4) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucket = args[0];
        String video = args[1];
        String topicArn = args[2];
        String roleArn = args[3];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startModerationDetection(rekClient, channel, bucket, video);
        getModResults(rekClient);
        System.out.println("This example is done!");
        rekClient.close();
    }

    public static void startModerationDetection(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {

        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartContentModerationRequest modDetectionRequest = StartContentModerationRequest.builder()
                    .jobTag("Moderation")
                    .notificationChannel(channel)
                    .video(vidOb)
                    .build();

            StartContentModerationResponse startModDetectionResult = rekClient
                    .startContentModeration(modDetectionRequest);
            startJobId = startModDetectionResult.jobId();

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

    public static void getModResults(RekognitionClient rekClient) {
        try {
            String paginationToken = null;
            GetContentModerationResponse modDetectionResponse = null;
            boolean finished = false;
            String status;
            int yy = 0;

            do {
                if (modDetectionResponse != null)
                    paginationToken = modDetectionResponse.nextToken();

                GetContentModerationRequest modRequest = GetContentModerationRequest.builder()
                        .jobId(startJobId)
                        .nextToken(paginationToken)
                        .maxResults(10)
                        .build();

                // Wait until the job succeeds.
                while (!finished) {
                    modDetectionResponse = rekClient.getContentModeration(modRequest);
                    status = modDetectionResponse.jobStatusAsString();

                    if (status.compareTo("SUCCEEDED") == 0)
                        finished = true;
                    else {
                        System.out.println(yy + " status is: " + status);
                        Thread.sleep(1000);
                    }
                    yy++;
                }

                finished = false;

                // Proceed when the job is done - otherwise VideoMetadata is null.
                VideoMetadata videoMetaData = modDetectionResponse.videoMetadata();
                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());
                System.out.println("Job");

                List<ContentModerationDetection> mods = modDetectionResponse.moderationLabels();
                for (ContentModerationDetection mod : mods) {
                    long seconds = mod.timestamp() / 1000;
                    System.out.print("Mod label: " + seconds + " ");
                    System.out.println(mod.moderationLabel().toString());
                    System.out.println();
                }

            } while (modDetectionResponse != null && modDetectionResponse.nextToken() != null);

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

Rileva segmenti di segnali d'azione tecnici e segmenti di rilevamento delle riprese in un video archiviato in un bucket Amazon S3.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartShotDetectionFilter;
import software.amazon.awssdk.services.rekognition.model.StartTechnicalCueDetectionFilter;
import software.amazon.awssdk.services.rekognition.model.StartSegmentDetectionFilters;
import software.amazon.awssdk.services.rekognition.model.StartSegmentDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.StartSegmentDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.GetSegmentDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.GetSegmentDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.SegmentDetection;
import software.amazon.awssdk.services.rekognition.model.TechnicalCueSegment;
import software.amazon.awssdk.services.rekognition.model.ShotSegment;
import software.amazon.awssdk.services.rekognition.model.SegmentType;
import software.amazon.awssdk.services.sqs.SqsClient;
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 VideoDetectSegment {
    private static String startJobId = "";

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

                Usage:    <bucket> <video> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of video (for example, people.mp4).\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

        if (args.length != 4) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucket = args[0];
        String video = args[1];
        String topicArn = args[2];
        String roleArn = args[3];

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

        SqsClient sqs = SqsClient.builder()
                .region(Region.US_EAST_1)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startSegmentDetection(rekClient, channel, bucket, video);
        getSegmentResults(rekClient);
        System.out.println("This example is done!");
        sqs.close();
        rekClient.close();
    }

    public static void startSegmentDetection(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartShotDetectionFilter cueDetectionFilter = StartShotDetectionFilter.builder()
                    .minSegmentConfidence(60F)
                    .build();

            StartTechnicalCueDetectionFilter technicalCueDetectionFilter = StartTechnicalCueDetectionFilter.builder()
                    .minSegmentConfidence(60F)
                    .build();

            StartSegmentDetectionFilters filters = StartSegmentDetectionFilters.builder()
                    .shotFilter(cueDetectionFilter)
                    .technicalCueFilter(technicalCueDetectionFilter)
                    .build();

            StartSegmentDetectionRequest segDetectionRequest = StartSegmentDetectionRequest.builder()
                    .jobTag("DetectingLabels")
                    .notificationChannel(channel)
                    .segmentTypes(SegmentType.TECHNICAL_CUE, SegmentType.SHOT)
                    .video(vidOb)
                    .filters(filters)
                    .build();

            StartSegmentDetectionResponse segDetectionResponse = rekClient.startSegmentDetection(segDetectionRequest);
            startJobId = segDetectionResponse.jobId();

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

    public static void getSegmentResults(RekognitionClient rekClient) {
        try {
            String paginationToken = null;
            GetSegmentDetectionResponse segDetectionResponse = null;
            boolean finished = false;
            String status;
            int yy = 0;

            do {
                if (segDetectionResponse != null)
                    paginationToken = segDetectionResponse.nextToken();

                GetSegmentDetectionRequest recognitionRequest = GetSegmentDetectionRequest.builder()
                        .jobId(startJobId)
                        .nextToken(paginationToken)
                        .maxResults(10)
                        .build();

                // Wait until the job succeeds.
                while (!finished) {
                    segDetectionResponse = rekClient.getSegmentDetection(recognitionRequest);
                    status = segDetectionResponse.jobStatusAsString();

                    if (status.compareTo("SUCCEEDED") == 0)
                        finished = true;
                    else {
                        System.out.println(yy + " status is: " + status);
                        Thread.sleep(1000);
                    }
                    yy++;
                }
                finished = false;

                // Proceed when the job is done - otherwise VideoMetadata is null.
                List<VideoMetadata> videoMetaData = segDetectionResponse.videoMetadata();
                for (VideoMetadata metaData : videoMetaData) {
                    System.out.println("Format: " + metaData.format());
                    System.out.println("Codec: " + metaData.codec());
                    System.out.println("Duration: " + metaData.durationMillis());
                    System.out.println("FrameRate: " + metaData.frameRate());
                    System.out.println("Job");
                }

                List<SegmentDetection> detectedSegments = segDetectionResponse.segments();
                for (SegmentDetection detectedSegment : detectedSegments) {
                    String type = detectedSegment.type().toString();
                    if (type.contains(SegmentType.TECHNICAL_CUE.toString())) {
                        System.out.println("Technical Cue");
                        TechnicalCueSegment segmentCue = detectedSegment.technicalCueSegment();
                        System.out.println("\tType: " + segmentCue.type());
                        System.out.println("\tConfidence: " + segmentCue.confidence().toString());
                    }

                    if (type.contains(SegmentType.SHOT.toString())) {
                        System.out.println("Shot");
                        ShotSegment segmentShot = detectedSegment.shotSegment();
                        System.out.println("\tIndex " + segmentShot.index());
                        System.out.println("\tConfidence: " + segmentShot.confidence().toString());
                    }

                    long seconds = detectedSegment.durationMillis();
                    System.out.println("\tDuration : " + seconds + " milliseconds");
                    System.out.println("\tStart time code: " + detectedSegment.startTimecodeSMPTE());
                    System.out.println("\tEnd time code: " + detectedSegment.endTimecodeSMPTE());
                    System.out.println("\tDuration time code: " + detectedSegment.durationSMPTE());
                    System.out.println();
                }

            } while (segDetectionResponse != null && segDetectionResponse.nextToken() != null);

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

Rileva il testo in un video archiviato in un bucket Amazon S3.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartTextDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.StartTextDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.GetTextDetectionResponse;
import software.amazon.awssdk.services.rekognition.model.GetTextDetectionRequest;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.TextDetectionResult;
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 VideoDetectText {
    private static String startJobId = "";

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

                Usage:    <bucket> <video> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of video (for example, people.mp4).\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

        if (args.length != 4) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucket = args[0];
        String video = args[1];
        String topicArn = args[2];
        String roleArn = args[3];

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

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startTextLabels(rekClient, channel, bucket, video);
        getTextResults(rekClient);
        System.out.println("This example is done!");
        rekClient.close();
    }

    public static void startTextLabels(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartTextDetectionRequest labelDetectionRequest = StartTextDetectionRequest.builder()
                    .jobTag("DetectingLabels")
                    .notificationChannel(channel)
                    .video(vidOb)
                    .build();

            StartTextDetectionResponse labelDetectionResponse = rekClient.startTextDetection(labelDetectionRequest);
            startJobId = labelDetectionResponse.jobId();

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

    public static void getTextResults(RekognitionClient rekClient) {
        try {
            String paginationToken = null;
            GetTextDetectionResponse textDetectionResponse = null;
            boolean finished = false;
            String status;
            int yy = 0;

            do {
                if (textDetectionResponse != null)
                    paginationToken = textDetectionResponse.nextToken();

                GetTextDetectionRequest recognitionRequest = GetTextDetectionRequest.builder()
                        .jobId(startJobId)
                        .nextToken(paginationToken)
                        .maxResults(10)
                        .build();

                // Wait until the job succeeds.
                while (!finished) {
                    textDetectionResponse = rekClient.getTextDetection(recognitionRequest);
                    status = textDetectionResponse.jobStatusAsString();

                    if (status.compareTo("SUCCEEDED") == 0)
                        finished = true;
                    else {
                        System.out.println(yy + " status is: " + status);
                        Thread.sleep(1000);
                    }
                    yy++;
                }

                finished = false;

                // Proceed when the job is done - otherwise VideoMetadata is null.
                VideoMetadata videoMetaData = textDetectionResponse.videoMetadata();
                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());
                System.out.println("Job");

                List<TextDetectionResult> labels = textDetectionResponse.textDetections();
                for (TextDetectionResult detectedText : labels) {
                    System.out.println("Confidence: " + detectedText.textDetection().confidence().toString());
                    System.out.println("Id : " + detectedText.textDetection().id());
                    System.out.println("Parent Id: " + detectedText.textDetection().parentId());
                    System.out.println("Type: " + detectedText.textDetection().type());
                    System.out.println("Text: " + detectedText.textDetection().detectedText());
                    System.out.println();
                }

            } while (textDetectionResponse != null && textDetectionResponse.nextToken() != null);

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

Rileva le persone in un video archiviato in un bucket Amazon S3.

import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.S3Object;
import software.amazon.awssdk.services.rekognition.model.NotificationChannel;
import software.amazon.awssdk.services.rekognition.model.StartPersonTrackingRequest;
import software.amazon.awssdk.services.rekognition.model.Video;
import software.amazon.awssdk.services.rekognition.model.StartPersonTrackingResponse;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.rekognition.model.GetPersonTrackingResponse;
import software.amazon.awssdk.services.rekognition.model.GetPersonTrackingRequest;
import software.amazon.awssdk.services.rekognition.model.VideoMetadata;
import software.amazon.awssdk.services.rekognition.model.PersonDetection;
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 VideoPersonDetection {
    private static String startJobId = "";

    public static void main(String[] args) {

        final String usage = """

                Usage:    <bucket> <video> <topicArn> <roleArn>

                Where:
                   bucket - The name of the bucket in which the video is located (for example, (for example, myBucket).\s
                   video - The name of video (for example, people.mp4).\s
                   topicArn - The ARN of the Amazon Simple Notification Service (Amazon SNS) topic.\s
                   roleArn - The ARN of the AWS Identity and Access Management (IAM) role to use.\s
                """;

        if (args.length != 4) {
            System.out.println(usage);
            System.exit(1);
        }

        String bucket = args[0];
        String video = args[1];
        String topicArn = args[2];
        String roleArn = args[3];
        Region region = Region.US_EAST_1;
        RekognitionClient rekClient = RekognitionClient.builder()
                .region(region)
                .build();

        NotificationChannel channel = NotificationChannel.builder()
                .snsTopicArn(topicArn)
                .roleArn(roleArn)
                .build();

        startPersonLabels(rekClient, channel, bucket, video);
        getPersonDetectionResults(rekClient);
        System.out.println("This example is done!");
        rekClient.close();
    }

    public static void startPersonLabels(RekognitionClient rekClient,
            NotificationChannel channel,
            String bucket,
            String video) {
        try {
            S3Object s3Obj = S3Object.builder()
                    .bucket(bucket)
                    .name(video)
                    .build();

            Video vidOb = Video.builder()
                    .s3Object(s3Obj)
                    .build();

            StartPersonTrackingRequest personTrackingRequest = StartPersonTrackingRequest.builder()
                    .jobTag("DetectingLabels")
                    .video(vidOb)
                    .notificationChannel(channel)
                    .build();

            StartPersonTrackingResponse labelDetectionResponse = rekClient.startPersonTracking(personTrackingRequest);
            startJobId = labelDetectionResponse.jobId();

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

    public static void getPersonDetectionResults(RekognitionClient rekClient) {
        try {
            String paginationToken = null;
            GetPersonTrackingResponse personTrackingResult = null;
            boolean finished = false;
            String status;
            int yy = 0;

            do {
                if (personTrackingResult != null)
                    paginationToken = personTrackingResult.nextToken();

                GetPersonTrackingRequest recognitionRequest = GetPersonTrackingRequest.builder()
                        .jobId(startJobId)
                        .nextToken(paginationToken)
                        .maxResults(10)
                        .build();

                // Wait until the job succeeds
                while (!finished) {

                    personTrackingResult = rekClient.getPersonTracking(recognitionRequest);
                    status = personTrackingResult.jobStatusAsString();

                    if (status.compareTo("SUCCEEDED") == 0)
                        finished = true;
                    else {
                        System.out.println(yy + " status is: " + status);
                        Thread.sleep(1000);
                    }
                    yy++;
                }

                finished = false;

                // Proceed when the job is done - otherwise VideoMetadata is null.
                VideoMetadata videoMetaData = personTrackingResult.videoMetadata();

                System.out.println("Format: " + videoMetaData.format());
                System.out.println("Codec: " + videoMetaData.codec());
                System.out.println("Duration: " + videoMetaData.durationMillis());
                System.out.println("FrameRate: " + videoMetaData.frameRate());
                System.out.println("Job");

                List<PersonDetection> detectedPersons = personTrackingResult.persons();
                for (PersonDetection detectedPerson : detectedPersons) {
                    long seconds = detectedPerson.timestamp() / 1000;
                    System.out.print("Sec: " + seconds + " ");
                    System.out.println("Person Identifier: " + detectedPerson.person().index());
                    System.out.println();
                }

            } while (personTrackingResult != null && personTrackingResult.nextToken() != null);

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

• Per API i dettagli, consulta i seguenti argomenti in AWS SDK for Java 2.x APIRiferimento.

  • GetCelebrityRecognition

  • GetContentModeration

  • GetLabelDetection

  • GetPersonTracking

  • GetSegmentDetection

  • GetTextDetection

  • StartCelebrityRecognition

  • StartContentModeration

  • StartLabelDetection

  • StartPersonTracking

  • StartSegmentDetection

  • StartTextDetection