Dispatch Queue with CoreML

I am a newcomer to Swift and iOS development, so apologies upfront for this. I would like to ask for help around queuing and the UI (at least I think this is my problem!)

I am trying to enable the camera, via AVFoundation, in order to get a near real-time stream of images that I can pass on for CoreML analysis.

Currently, I am at the debugging / data learning stage. Essentially, I would like to take sample footage and save it all to an on-device CoreData [SQLite] database, that I can then analyse further offline. I can then learn from the results to fine tune / filter images / etc.

If I supply an individual image, the image model is able to provide descending order of “confidence” with up to 1000 rows. I recorded all this as part of the analysis by adding an extra counter integer to the [VNClassificationObservation] array and adding this to the CoreData database.

This doesn’t work with the stream from the camera. The counter doesnt seem to work, with everything having a counter value of 1000…

The tap gesture in viewDidLoad() function has also stopped working with these changes. I wonder if its related to the queuing stuff, as the text label doesnt properly reset either though I can see it updating for a millisecond or so...

func setupCameraSession() {
  <<bunch of stuff to initialise devices, etc>>

  cameraLayer = AVCaptureVideoPreviewLayer(session: cameraSession)
  cameraLayer.frame = layer.frame
  layer.addSublayer(cameraLayer)
  cameraSession.startRunning()
  cameraOutput.setSampleBufferDelegate(self, queue: DispatchQueue(label: "videoQueue"))
}

func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {     
  processCameraBuffer(sampleBuffer: sampleBuffer)
}

func processCameraBuffer(sampleBuffer: CMSampleBuffer) {
      
        let coreMLModel = Inceptionv3()
      
        if let model = try? VNCoreMLModel(for: coreMLModel.model) {
            let request = VNCoreMLRequest(model: model, completionHandler: { (request, error) in
                if let results = request.results as? [VNClassificationObservation] {
                    var counter = 1
                    for classification in results {
                        DispatchQueue.main.async(execute: {
                            let timestamp = NSDate().timeIntervalSince1970
                          
                            let appDelegate = UIApplication.shared.delegate as! AppDelegate
                            let context = appDelegate.persistentContainer.viewContext
                          
                            let newItem = NSEntityDescription.insertNewObject(forEntityName: "Predictions", into: context)
                            newItem.setValue(classification.confidence, forKey: "confidence")
                            newItem.setValue(classification.identifier, forKey: "identifier")
                            newItem.setValue(counter, forKey: "index")
                            newItem.setValue(timestamp, forKey: "timestamp")
                            let confidence = String(format: "%.2f", classification.confidence * 100)
                            self.labelPrediction.text = "\(confidence)%"
                          
                            do {
                                try context.save()
                            } catch {
                                print("CoreData Save error")
                            }
                        })
                      
                        counter += 1
                    }
                }
            })
                if let pixelBuffer: CVPixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer) {
                    let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer, options: [:])
                    try? handler.perform([request])
                }
        }
    }

override func viewDidLoad() {
        super.viewDidLoad()
      
        imagePicker.delegate = self
      
        if let imageIcon = UIImage(named: "icon_512") {
            layer.contentsGravity = kCAGravityResizeAspect
            layer.contents = imageIcon.cgImage
        }
      
        let tap = UITapGestureRecognizer(target: self, action: #selector(ViewController.releaseCamera))
        viewCamera.addGestureRecognizer(tap)
    }

I would like to understand more about the queuing process in order to achieve this, so that I can record every "confidence" row from the CoreML model and to always have the camera disable when the "tap" function is pressed (i.e. the screen is touched).

Thanks