WildStudio

@IBAction func onTapButton(_ sender: Any) {
     presentAnimationController.selectedCardFrame = imageView.frame
     self.performSegue(withIdentifier: "showDetail", sender: nil)
 }

WildStudio

@IBAction func onTapButton(_ sender: Any) {
     presentAnimationController.selectedCardFrame = imageView.frame
     self.performSegue(withIdentifier: "showDetail", sender: nil)
 }

WildStudio

@IBAction func onTapButton(_ sender: Any) {
     presentAnimationController.selectedCardFrame = imageView.frame
     self.performSegue(withIdentifier: "showDetail", sender: nil)
 }

WildStudio

extension MainViewController: UIViewControllerTransitioningDelegate {
    
    func animationController(forPresented presented: UIViewController,
                             presenting: UIViewController,
                             source: UIViewController) -> UIViewControllerAnimatedTransitioning? {
        return presentAnimationController
    }
}

WildStudio

override func prepare(for segue: UIStoryboardSegue, sender: Any?) {
        let destinationViewController = segue.destination
        destinationViewController.transitioningDelegate = self
}

WildStudio

let controller = Pager.PageContainerViewController.instantiate()
present(controller, animated: true)

let controllers = dataSource.map { _ in PageDetailViewController.instantiate() ?? PageDetailViewController() }
controller.configure(with: dataSource, controllers: controllers)

WildStudio

func handleClassification(request: VNRequest, error: Error?) {
        guard let observations = request.results as? [VNClassificationObservation]
            else { fatalError("unexpected result type from VNCoreMLRequest") }
        guard let best = observations.first
            else { fatalError("can't get best result") }

        DispatchQueue.main.async {
            self.classificationLabel.text = "Classification: \"\(best.identifier)\" Confidence: \(best.confidence)"
        }
    }

WildStudio

   let handler = VNImageRequestHandler(ciImage: ciImage, orientation:orientation)
        DispatchQueue.global(qos: .userInteractive).async {
            do {
                try handler.perform([self.classificationRequest])
            } catch {
                print(error)
            }
        }

WildStudio

lazy var classificationRequest: VNCoreMLRequest = {
        do {
            let model = try VNCoreMLModel(for: ImageClassifier().model)
            return VNCoreMLRequest(model: model, completionHandler: self.handleClassification)
        } catch {
            fatalError("can't load Vision ML model: \(error)")
        }
    }()

WildStudio

import CreateMLUI
 
let builder = MLImageClassifierBuilder()
builder.showInLiveView()