Esempi di utilizzo di Amazon Rekognition per Kotlin SDK

suspend fun compareTwoFaces(
    similarityThresholdVal: Float,
    sourceImageVal: String,
    targetImageVal: String,
) {
    val sourceBytes = (File(sourceImageVal).readBytes())
    val targetBytes = (File(targetImageVal).readBytes())

    // Create an Image object for the source image.
    val souImage =
        Image {
            bytes = sourceBytes
        }

    val tarImage =
        Image {
            bytes = targetBytes
        }

    val facesRequest =
        CompareFacesRequest {
            sourceImage = souImage
            targetImage = tarImage
            similarityThreshold = similarityThresholdVal
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->

        val compareFacesResult = rekClient.compareFaces(facesRequest)
        val faceDetails = compareFacesResult.faceMatches

        if (faceDetails != null) {
            for (match: CompareFacesMatch in faceDetails) {
                val face = match.face
                val position = face?.boundingBox
                if (position != null) {
                    println("Face at ${position.left} ${position.top} matches with ${face.confidence} % confidence.")
                }
            }
        }

        val uncompared = compareFacesResult.unmatchedFaces
        if (uncompared != null) {
            println("There was ${uncompared.size} face(s) that did not match")
        }

        println("Source image rotation: ${compareFacesResult.sourceImageOrientationCorrection}")
        println("target image rotation: ${compareFacesResult.targetImageOrientationCorrection}")
    }
}

suspend fun createMyCollection(collectionIdVal: String) {
    val request =
        CreateCollectionRequest {
            collectionId = collectionIdVal
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.createCollection(request)
        println("Collection ARN is ${response.collectionArn}")
        println("Status code is ${response.statusCode}")
    }
}

suspend fun deleteMyCollection(collectionIdVal: String) {
    val request =
        DeleteCollectionRequest {
            collectionId = collectionIdVal
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.deleteCollection(request)
        println("The collectionId status is ${response.statusCode}")
    }
}

suspend fun deleteFacesCollection(
    collectionIdVal: String?,
    faceIdVal: String,
) {
    val deleteFacesRequest =
        DeleteFacesRequest {
            collectionId = collectionIdVal
            faceIds = listOf(faceIdVal)
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        rekClient.deleteFaces(deleteFacesRequest)
        println("$faceIdVal was deleted from the collection")
    }
}

suspend fun describeColl(collectionName: String) {
    val request =
        DescribeCollectionRequest {
            collectionId = collectionName
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.describeCollection(request)
        println("The collection Arn is ${response.collectionArn}")
        println("The collection contains this many faces ${response.faceCount}")
    }
}

suspend fun detectFacesinImage(sourceImage: String?) {
    val souImage =
        Image {
            bytes = (File(sourceImage).readBytes())
        }

    val request =
        DetectFacesRequest {
            attributes = listOf(Attribute.All)
            image = souImage
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.detectFaces(request)
        response.faceDetails?.forEach { face ->
            val ageRange = face.ageRange
            println("The detected face is estimated to be between ${ageRange?.low} and ${ageRange?.high} years old.")
            println("There is a smile ${face.smile?.value}")
        }
    }
}

suspend fun detectImageLabels(sourceImage: String) {
    val souImage =
        Image {
            bytes = (File(sourceImage).readBytes())
        }
    val request =
        DetectLabelsRequest {
            image = souImage
            maxLabels = 10
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.detectLabels(request)
        response.labels?.forEach { label ->
            println("${label.name} : ${label.confidence}")
        }
    }
}

suspend fun detectModLabels(sourceImage: String) {
    val myImage =
        Image {
            this.bytes = (File(sourceImage).readBytes())
        }

    val request =
        DetectModerationLabelsRequest {
            image = myImage
            minConfidence = 60f
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.detectModerationLabels(request)
        response.moderationLabels?.forEach { label ->
            println("Label: ${label.name} - Confidence: ${label.confidence} % Parent: ${label.parentName}")
        }
    }
}

suspend fun detectTextLabels(sourceImage: String?) {
    val souImage =
        Image {
            bytes = (File(sourceImage).readBytes())
        }

    val request =
        DetectTextRequest {
            image = souImage
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.detectText(request)
        response.textDetections?.forEach { text ->
            println("Detected: ${text.detectedText}")
            println("Confidence: ${text.confidence}")
            println("Id: ${text.id}")
            println("Parent Id:  ${text.parentId}")
            println("Type: ${text.type}")
        }
    }
}

suspend fun addToCollection(
    collectionIdVal: String?,
    sourceImage: String,
) {
    val souImage =
        Image {
            bytes = (File(sourceImage).readBytes())
        }

    val request =
        IndexFacesRequest {
            collectionId = collectionIdVal
            image = souImage
            maxFaces = 1
            qualityFilter = QualityFilter.Auto
            detectionAttributes = listOf(Attribute.Default)
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val facesResponse = rekClient.indexFaces(request)

        // Display the results.
        println("Results for the image")
        println("\n Faces indexed:")
        facesResponse.faceRecords?.forEach { faceRecord ->
            println("Face ID: ${faceRecord.face?.faceId}")
            println("Location: ${faceRecord.faceDetail?.boundingBox}")
        }

        println("Faces not indexed:")
        facesResponse.unindexedFaces?.forEach { unindexedFace ->
            println("Location: ${unindexedFace.faceDetail?.boundingBox}")
            println("Reasons:")

            unindexedFace.reasons?.forEach { reason ->
                println("Reason:  $reason")
            }
        }
    }
}

suspend fun listAllCollections() {
    val request =
        ListCollectionsRequest {
            maxResults = 10
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.listCollections(request)
        response.collectionIds?.forEach { resultId ->
            println(resultId)
        }
    }
}

suspend fun listFacesCollection(collectionIdVal: String?) {
    val request =
        ListFacesRequest {
            collectionId = collectionIdVal
            maxResults = 10
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.listFaces(request)
        response.faces?.forEach { face ->
            println("Confidence level there is a face: ${face.confidence}")
            println("The face Id value is ${face.faceId}")
        }
    }
}

suspend fun recognizeAllCelebrities(sourceImage: String?) {
    val souImage =
        Image {
            bytes = (File(sourceImage).readBytes())
        }

    val request =
        RecognizeCelebritiesRequest {
            image = souImage
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val response = rekClient.recognizeCelebrities(request)
        response.celebrityFaces?.forEach { celebrity ->
            println("Celebrity recognized: ${celebrity.name}")
            println("Celebrity ID:${celebrity.id}")
            println("Further information (if available):")
            celebrity.urls?.forEach { url ->
                println(url)
            }
        }
        println("${response.unrecognizedFaces?.size} face(s) were unrecognized.")
    }
}

Mostra come sviluppare un'applicazione per la gestione delle risorse fotografiche che rileva le etichette nelle immagini utilizzando Amazon Rekognition e le archivia per recuperarle in seguito.

Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, guarda l'esempio completo su. GitHub

Per approfondire l'origine di questo esempio, consulta il post su AWS  Community.

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

suspend fun startFaceDetection(
    channelVal: NotificationChannel?,
    bucketVal: String,
    videoVal: String,
) {
    val s3Obj =
        S3Object {
            bucket = bucketVal
            name = videoVal
        }
    val vidOb =
        Video {
            s3Object = s3Obj
        }

    val request =
        StartFaceDetectionRequest {
            jobTag = "Faces"
            faceAttributes = FaceAttributes.All
            notificationChannel = channelVal
            video = vidOb
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val startLabelDetectionResult = rekClient.startFaceDetection(request)
        startJobId = startLabelDetectionResult.jobId.toString()
    }
}

suspend fun getFaceResults() {
    var finished = false
    var status: String
    var yy = 0
    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        var response: GetFaceDetectionResponse? = null

        val recognitionRequest =
            GetFaceDetectionRequest {
                jobId = startJobId
                maxResults = 10
            }

        // Wait until the job succeeds.
        while (!finished) {
            response = rekClient.getFaceDetection(recognitionRequest)
            status = response.jobStatus.toString()
            if (status.compareTo("SUCCEEDED") == 0) {
                finished = true
            } else {
                println("$yy status is: $status")
                delay(1000)
            }
            yy++
        }

        // Proceed when the job is done - otherwise VideoMetadata is null.
        val videoMetaData = response?.videoMetadata
        println("Format: ${videoMetaData?.format}")
        println("Codec: ${videoMetaData?.codec}")
        println("Duration: ${videoMetaData?.durationMillis}")
        println("FrameRate: ${videoMetaData?.frameRate}")

        // Show face information.
        response?.faces?.forEach { face ->
            println("Age: ${face.face?.ageRange}")
            println("Face: ${face.face?.beard}")
            println("Eye glasses: ${face?.face?.eyeglasses}")
            println("Mustache: ${face.face?.mustache}")
            println("Smile: ${face.face?.smile}")
        }
    }
}

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

suspend fun startModerationDetection(
    channel: NotificationChannel?,
    bucketVal: String?,
    videoVal: String?,
) {
    val s3Obj =
        S3Object {
            bucket = bucketVal
            name = videoVal
        }
    val vidOb =
        Video {
            s3Object = s3Obj
        }
    val request =
        StartContentModerationRequest {
            jobTag = "Moderation"
            notificationChannel = channel
            video = vidOb
        }

    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        val startModDetectionResult = rekClient.startContentModeration(request)
        startJobId = startModDetectionResult.jobId.toString()
    }
}

suspend fun getModResults() {
    var finished = false
    var status: String
    var yy = 0
    RekognitionClient { region = "us-east-1" }.use { rekClient ->
        var modDetectionResponse: GetContentModerationResponse? = null

        val modRequest =
            GetContentModerationRequest {
                jobId = startJobId
                maxResults = 10
            }

        // Wait until the job succeeds.
        while (!finished) {
            modDetectionResponse = rekClient.getContentModeration(modRequest)
            status = modDetectionResponse.jobStatus.toString()
            if (status.compareTo("SUCCEEDED") == 0) {
                finished = true
            } else {
                println("$yy status is: $status")
                delay(1000)
            }
            yy++
        }

        // Proceed when the job is done - otherwise VideoMetadata is null.
        val videoMetaData = modDetectionResponse?.videoMetadata
        println("Format: ${videoMetaData?.format}")
        println("Codec: ${videoMetaData?.codec}")
        println("Duration: ${videoMetaData?.durationMillis}")
        println("FrameRate: ${videoMetaData?.frameRate}")

        modDetectionResponse?.moderationLabels?.forEach { mod ->
            val seconds: Long = mod.timestamp / 1000
            print("Mod label: $seconds ")
            println(mod.moderationLabel)
        }
    }
}

Mostra come usare Amazon Rekognition Kotlin per creare un'app che utilizzi Amazon API Rekognition per identificare gli oggetti per categoria nelle immagini che si trovano in un bucket Amazon Simple Storage Service (Amazon S3). L'app invia all'amministratore una notifica e-mail con i risultati utilizzando Amazon Simple Email Service (AmazonSES).

Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, guarda l'esempio completo su GitHub.