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bulentsiyah/IBMCustomMeyveTrafikViewController.swift

Last active July 2, 2018 20:35
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  1. bulentsiyah revised this gist Jul 2, 2018. No changes.
  2. bulentsiyah created this gist Jul 2, 2018.
    85 changes: 85 additions & 0 deletions IBMCustomMeyveTrafikViewController.swift
    View file
    Original file line number Diff line number Diff line change
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    //
    // IBMCustomMeyveTrafikViewController.swift
    // ML Ornekleri
    //
    // Created by Bülent Siyah on 2.07.2018.
    // Copyright © 2018 Bülent Siyah. All rights reserved.
    //

    import UIKit
    import CoreML
    import Vision

    class IBMCustomMeyveTrafikViewController: UIViewController , UIImagePickerControllerDelegate, UINavigationControllerDelegate {

    var meyveTrueTrafikFalse = true
    @IBOutlet weak var image: UIImageView!
    @IBOutlet weak var result: UILabel!

    var imagePicker: UIImagePickerController!
    var userPickedImage: UIImage?

    override func viewDidLoad() {
    super.viewDidLoad()

    imagePicker = UIImagePickerController()
    imagePicker.delegate = self

    }

    func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {

    if let pickedImage = info[UIImagePickerControllerOriginalImage] as? UIImage {
    image.contentMode = .scaleAspectFit
    image.image = pickedImage
    self.userPickedImage = pickedImage
    }

    dismiss(animated: true, completion: nil)
    }

    func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {
    dismiss(animated: true, completion: nil)
    }

    @IBAction func btnResimSec(_ sender: Any) {
    imagePicker.allowsEditing = false
    imagePicker.sourceType = .photoLibrary
    present(imagePicker, animated: true, completion: nil)
    }

    @IBOutlet var btnAnalizEt: UIView!

    @IBAction func btnAnalizYap(_ sender: Any) {

    do {
    var model : VNCoreMLModel
    if(meyveTrueTrafikFalse){
    model = try VNCoreMLModel(for: ElmaMandalinePortakal().model)
    }else{
    model = try VNCoreMLModel(for: Trafikisaretleri().model)
    }

    let request = VNCoreMLRequest(model: model) { (request, error) in
    if let results = request.results as? [VNClassificationObservation], let result = results.first {
    DispatchQueue.main.async {
    self.result.text = "\(result.identifier) \(result.confidence * 100)%"
    }
    }
    }
    request.imageCropAndScaleOption = .centerCrop
    DispatchQueue.global(qos: DispatchQoS.QoSClass.userInitiated).async {
    let handler = VNImageRequestHandler(cgImage: self.userPickedImage!.cgImage!, options: [:])
    do {
    try handler.perform([request])
    } catch {
    print(error)
    }

    }
    }catch {
    print(error)
    }
    }

    }