jacobsapps

var norm: Float = 0
vDSP_svesq(embedding, 1, &norm, vDSP_Length(count))
norm = sqrt(norm)
if norm > 0 {
    vDSP_vsdiv(embedding, 1, &norm, &embedding, 1, vDSP_Length(count))
}

jacobsapps

func clusterFaces(_ embeddings: [[Float]], threshold: Float) -> [[Int]] {
    var graph = Array(repeating: [Int](), count: embeddings.count)

    for i in embeddings.indices {
        for j in (i + 1)..<embeddings.count {
            if dot(embeddings[i], embeddings[j]) >= threshold {
                graph[i].append(j)
                graph[j].append(i)
            }
        }

jacobsapps

func dot(_ a: [Float], _ b: [Float]) -> Float {
    zip(a, b).reduce(0) { $0 + $1.0 * $1.1 }
}

jacobsapps

func computeEmbedding(
    face: VNFaceObservation,
    image: CGImage,
    model: MLModel
) async throws -> [Float]? {
    // 1. crop the face out of the original image
    guard let crop = cropFace(observation: face, from: image) else { return nil }

    // 2. resize the face to the model's input size
    let pixelBuffer = try makePixelBuffer(from: crop, size: 160)

jacobsapps

let qualityFaces = faces.filter { observation in
    let faceWidth = observation.boundingBox.width * CGFloat(cgImage.width)
    let faceHeight = observation.boundingBox.height * CGFloat(cgImage.height)
    return faceWidth >= 40 && faceHeight >= 40 && observation.confidence >= 0.5
}

jacobsapps

func detectFaces(in image: CGImage) async throws -> [VNFaceObservation] {
    try await withCheckedThrowingContinuation { continuation in
        let request = VNDetectFaceRectanglesRequest { request, error in
            if let error {
                continuation.resume(throwing: error)
                return
            }
            let faces = request.results as? [VNFaceObservation] ?? []
            continuation.resume(returning: faces)
        }

jacobsapps

@main
struct FakeTwitterApp: App {
    @UIApplicationDelegateAdaptor(FakeTwitterAppDelegate.self) private var appDelegate

    private let modelContainer: ModelContainer
    private let level4Engine: UploadJobEngine

    init() {
        let schema = Schema([PersistedUploadJob.self])
        let configuration = ModelConfiguration(schema: schema, isStoredInMemoryOnly: false)

jacobsapps

private func processQueueIfNeeded() async {
    guard !isProcessing else { return }
    isProcessing = true
    defer { isProcessing = false }

    while let nextJob = fetchNextOutstandingJobSnapshot() {
        do {
            try withJob(nextJob.id) { _, job in
                job.state = .uploading
                job.attempts += 1

jacobsapps

func postTweet(
    text: String,
    strategy _: RetryStrategy,
    retryOptions _: RetryOptions
) async throws {
    await engine.enqueue(text: text)
}

func enqueue(text: String) async {
    let context = ModelContext(container)

jacobsapps

enum UploadJobState: String, Codable {
    case pending
    case uploading
    case succeeded
    case failed
}

@Model
final class PersistedUploadJob {
    @Attribute(.unique) var id: UUID