// Classification method.
func classify(_ image: CGImage, completion: @escaping ([VNClassificationObservation]) -> Void) {
    DispatchQueue.global(qos: .background).async {
        // Initialize the coreML vision model, you can also use VGG16().model, or any other model that takes an image.
        guard let vnCoreModel = try? VNCoreMLModel(for: Inceptionv3().model) else { return }

        // Build the coreML vision request.
        let request = VNCoreMLRequest(model: vnCoreModel) { (request, error) in
            // We get get an array of VNClassificationObservations back
            // This has the fields "confidence", which is the score
            // and "identifier" which is the recognized class
            guard var results = request.results as? [VNClassificationObservation] else { fatalError("Failure") }

            // Filter out low scoring results.
            results = results.filter({ $0.confidence > 0.01 })

            DispatchQueue.main.async {
                completion(results)
            }
        }

        // Initialize the coreML vision request handler.
        let handler = VNImageRequestHandler(cgImage: image)

        // Perform the coreML vision request.
        do {
            try handler.perform([request])
        } catch {
            print("Error: \(error)")
        }
    }
}