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I am trying to improve the performance of drawing the skeleton with body tracking as I am getting noticeable lag even when further than 5 metres away, and with stable iPhone XS camera. The tracking is not close to the showcased performance in WWDC-10043 demo video. I have also tried using: let request = VNDetectHumanBodyPoseRequest(completionHandler: ) ... however the results were the same, and I also tried using revision 1 of the algorithm: let request = VNDetectHumanBodyPoseRequest( ) request.revision = VNDetectHumanBodyPoseRequestRevision1 ... and this didn't help either. Here's my current code: /// Extracts poses from a frame. class Predictor {   func processFrame(_ samplebuffer: CMSampleBuffer) throws -> [VNRecognizedPointsObservation] {     // Perform Vision body pose request     let framePoses = extractPoses(from: samplebuffer)          // Select the most promiment person.     guard let pose = framePoses.first else {       return []     }          return framePoses   }      func extractPoses(from sampleBuffer: CMSampleBuffer) -> [VNRecognizedPointsObservation] {     let requestHandler = VNImageRequestHandler(cmSampleBuffer: sampleBuffer, orientation: .down)          let request = VNDetectHumanBodyPoseRequest()          do {       // Perform the body pose-detection request.       try requestHandler.perform([request])     } catch {       print("Unable to perform the request: \(error).\n")     }          return bodyPoseHandler(request: request, error: nil)   }   func bodyPoseHandler(request: VNRequest, error: Error?) -> [VNRecognizedPointsObservation] {     guard let observations =             request.results as? [VNRecognizedPointsObservation] else {       print("Empty observations.\n\n")       return []     }     return observations   } } class CameraViewController: AVCaptureVideoDataOutputSampleBufferDelegate { func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {     let observations = try? predictor.processFrame(sampleBuffer)     observations?.forEach { processObservation($0) } } func processObservation(_ observation: VNRecognizedPointsObservation) {          // Retrieve all torso points.     guard let recognizedPoints =             try? observation.recognizedPoints(forGroupKey: .all) else {       return     }          let storedPoints = Dictionary(uniqueKeysWithValues: recognizedPoints.compactMap { (key, point) -> (String, CGPoint)? in       return (key.rawValue, point.location)     })          DispatchQueue.main.sync {       let mappedPoints = Dictionary(uniqueKeysWithValues: recognizedPoints.compactMap { (key, point) -> (String, CGPoint)? in         guard point.confidence > 0.1 else { return nil }         let norm = VNImagePointForNormalizedPoint(point.location,                                                   Int(drawingView.bounds.width),                                                   Int(drawingView.bounds.height))         return (key.rawValue, norm)       })              let time = 1000 * observation.timeRange.start.seconds              // Draw the points onscreen.       DispatchQueue.main.async {         self.drawingView.draw(points: mappedPoints)       }     }   } } Thanks in advance, I hope you can help me out! :)

Is it possible to improve the security of the apple-app-site-association file? I don't want testers to access the file and learn about how to find hidden routes or build a word list for further testing. I also would be exposing my app identifier, which I am not fully comfortable doing.

I saw these 2 new architectures which work great for SwiftUI - ELM and the composable architecture (see PointFree for more info). I know that UIKit apps in general has MVC, MVVM, MVVM-C, ELM, VIPER and probably many more. SwiftUI seems more like a MVVM model, ELM or Composable. I am building an AR app which has a menu home screen, calendar screen, tracking metrics screen, as well as a camera capture scene. I know that ideally capture sessions shouldn't be started when not in use, so only when needed to avoid use of expensive computations. But I don't know how best to architect my app i.e which architecture to use for a mixed ARKit and SwiftUI app with many screens not just for camera capture. What are the best practices for building mixed AR apps?