CameraVC-Emoji-Vision-CoreML.swift

lazy var classificationRequest: VNCoreMLRequest = {
        do {
            let model = try VNCoreMLModel(for: MobileNet().model)
            
            let request = VNCoreMLRequest(model: model, completionHandler: { [weak self] request, error in
                self?.processClassifications(for: request, error: error)
            })
            request.imageCropAndScaleOption = .centerCrop
            return request
        } catch {
            fatalError("Failed to load Vision ML model: \(error)")
        }
    }()
    
func captureOutput(
        _ output: AVCaptureOutput,
        didOutput sampleBuffer: CMSampleBuffer,
        from connection: AVCaptureConnection) {
        
        guard let frame = CMSampleBufferGetImageBuffer(sampleBuffer) else {
            debugPrint("unable to get image from sample buffer")
            return
        }
        
        self.updateClassifications(in: frame)
    }    
    

func updateClassifications(in image: CVPixelBuffer) {

        DispatchQueue.global(qos: .userInitiated).async {
            let handler = VNImageRequestHandler(cvPixelBuffer: image, orientation: .right, options: [:])
            do {
                try handler.perform([self.classificationRequest])
            } catch {
                print("Failed to perform classification.\n\(error.localizedDescription)")
            }
        }
    }
    
func processClassifications(for request: VNRequest, error: Error?) {
    DispatchQueue.main.async {
        guard let results = request.results else {
            return
        }
        let classifications = results as! [VNClassificationObservation]

        if !classifications.isEmpty {
            if classifications.first!.confidence > 0.5{
                let identifier = classifications.first?.identifier ?? ""

                if identifier.contains(self.emojiString){
                    self.delegate?.emojiWasFound(result: true)
                }
            }
        }
    }
}