最近学习了下CoreML，然后参照资料做了一个简单的图片识别，然后参照资料做了一个简单的图片识别，虽然网上有很多类似的资料，但是还是自己做一做来的实在。
首先，先简单的介绍下

Core ML简介

Core ML框架
iOS11推出了Core ML框架，极大地降低了开发者在iphone上使用机器学习的门槛。
苹果文档给出了如下的描述：
Core ML is the foundation for domain-specific frameworks and functionality.Core ML supports Vision for image analysis, Foundation for natural language processing (for example, the NSLinguisticTagger class), and GameplayKit for evaluating learned decision trees. Core ML itself builds on top of low-level primitives like Accelerate and BNNS, as well as Metal Performance Shaders.

最后
功能就是选择一张图片或者排照然后对图片进行识别。

github地址

image.png

image.png

import UIKit
import CoreML
import Vision


class ViewController: UIViewController {

    @IBOutlet weak var imageView: UIImageView!
    
    @IBOutlet weak var labelPercent: UILabel!
    
    @IBOutlet weak var labelDesc: UILabel!
    
    
    override func viewDidLoad() {
        super.viewDidLoad()
        imageView.layer.masksToBounds = true
    }

    @IBAction func chooseImage(_ sender: Any) {
        let actionSheet = UIAlertController(title: nil, message: nil, preferredStyle: .actionSheet)
        
        let cameraAction = UIAlertAction(title: "拍照", style: .default) { _ in
            self.takePhoto(from: .camera)
        }
        
        let photoLibray = UIAlertAction(title: "相册", style: .default) { _ in
            self.takePhoto(from: .photoLibray)
        }
        
        let cancel = UIAlertAction(title: "cancel", style: .cancel, handler: nil)
        
        actionSheet.addAction(cameraAction)
        actionSheet.addAction(photoLibray)
        actionSheet.addAction(cancel)
        
        present(actionSheet, animated: true, completion: nil)
    }
    
}

extension ViewController{
    func resize(image:UIImage, newSize:CGSize) -> UIImage?{
        UIGraphicsBeginImageContextWithOptions(newSize, false, 0)
        let size = CGRect(x: 0, y: 0, width: newSize.width, height: newSize.height)
        image.draw(in: size)
        let newImage = UIGraphicsGetImageFromCurrentImageContext()
        UIGraphicsEndImageContext()
        return newImage
    }
}

6.然后是选择图片的方法，就直接调用系统的图片或者拍照。

extension ViewController{
    enum PhotoSource {
        case camera,photoLibray
    }
    
    func takePhoto(from source:PhotoSource){
        let imagePicker = UIImagePickerController()
        
        imagePicker.sourceType = (source == .camera ? .camera : .photoLibrary)
        imagePicker.delegate = self
        imagePicker.allowsEditing = true
        
        present(imagePicker, animated: true, completion: nil)
    }
}

7.最后是图片选择完成时候进行图片猜测。

extension ViewController: UIImagePickerControllerDelegate,UINavigationControllerDelegate{
    func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {
        dismiss(animated: true, completion: nil)
    }
    func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
        dismiss(animated: true, completion: nil)
        if let image = info[UIImagePickerControllerEditedImage] as? UIImage {
            imageView.image = image
            // mlmodel input image 提示支持224*224大小的图片
            let fixSize = CGSize(width: 224, height: 224)
            if let newImage = resize(image: image, newSize: fixSize){
                guess(image: newImage)
            }
        }
    }
    
    
    ///图片猜测方法
    func guess(image:UIImage){
        
        guard let ciImage = CIImage(image:image) else{
            fatalError("不能创建image")
        }
        
        guard let model = try? VNCoreMLModel(for: VGG16().model) else{
            fatalError("不能加载model")
        }
        
        let request = VNCoreMLRequest(model: model) { (request, error) in
            guard let results = request.results as? [VNClassificationObservation], let first = results.first else{
                fatalError("不能匹配结果")
            }
            DispatchQueue.main.async {
                self.labelDesc.text = first.identifier
                self.labelPercent.text = "\(first.confidence * 100)%"
            }
        }

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