Xcode9学习笔记77 - iOS11新特性 - CoreML机器学习框架

首先到https://developer.apple.com/machine-learning/ 下载一个Resnet50.mlmodel文件，将它拖动到XCode项目文件夹：

编写代码如下：

import UIKit
import CoreML

class ViewController: UIViewController {

    override func viewDidLoad() {
        super.viewDidLoad()
        // Do any additional setup after loading the view, typically from a nib.
        
        let image = UIImage(named: "sample")
        
        let width: CGFloat = 224.0
        let height: CGFloat = 224.0
        
        //获得一个基于位图的上下文，并设置其为当前的上下文
        UIGraphicsBeginImageContext(CGSize(width: width, height: height))
        //将从项目中加载的图像，绘制在上下文的指定区域
        image?.draw(in: CGRect(x: 0, y: 0, width: width, height: height))
        //从上下文中获得格式转换后的图像
        let newImage = UIGraphicsGetImageFromCurrentImageContext()
        //完成图像的格式转换后，关闭当前的上下文
        UIGraphicsEndImageContext()
        
        if #available(iOS 11.0, *) {
            let resnet50 = Resnet50()//初始化机器学习模型的对象
            
            guard let output = try? resnet50.prediction(image: PixelBufferFromImage(newImage!)!) else {
                fatalError("Unexpected Error")
            }
            print(output.classLabel)
        }
    }
    
    func createPixelBufferPool(_ width: Int32, _ height: Int32, _ pixelFormat: FourCharCode, _ maxBufferCount: Int32) -> CVPixelBufferPool? {
        var outputPool: CVPixelBufferPool? = nil
        let sourcePixelBufferOptions: NSDictionary = [kCVPixelBufferPixelFormatTypeKey: pixelFormat,
                                                      kCVPixelBufferWidthKey: width,
                                                      kCVPixelBufferHeightKey: height,
                                                      kCVPixelFormatOpenGLESCompatibility: true,
                                                      kCVPixelBufferIOSurfacePropertiesKey: NSDictionary()]
        
        let pixelBufferPoolOptions: NSDictionary = [kCVPixelBufferPoolMinimumBufferCountKey: maxBufferCount]
        CVPixelBufferPoolCreate(kCFAllocatorDefault, pixelBufferPoolOptions, sourcePixelBufferOptions, &outputPool)
        return outputPool
    }

    func PixelBufferFromImage(_ image: UIImage) -> CVPixelBuffer?{
        let size = image.size
        var pxbuffer : CVPixelBuffer?
        let pixelBufferPool = createPixelBufferPool(224, 224, FourCharCode(kCVPixelFormatType_32BGRA), 2056) // Hard coded values for demo purposes.
        let status = CVPixelBufferPoolCreatePixelBuffer(kCFAllocatorDefault, pixelBufferPool!, &pxbuffer)
        
        guard (status == kCVReturnSuccess) else{
            return nil
        }
        CVPixelBufferLockBaseAddress(pxbuffer!, CVPixelBufferLockFlags(rawValue: 0))
        let pxdata = CVPixelBufferGetBaseAddress(pxbuffer!)
        let rgbColorSpace = CGColorSpaceCreateDeviceRGB()
        let context = CGContext(data: pxdata,
                                width: Int(size.width),
                                height: Int(size.height),
                                bitsPerComponent: 8,
                                bytesPerRow: CVPixelBufferGetBytesPerRow(pxbuffer!),
                                space: rgbColorSpace,
                                bitmapInfo: CGImageAlphaInfo.premultipliedFirst.rawValue)
        
        context?.translateBy(x: 0, y: image.size.height)
        context?.scaleBy(x: 1.0, y: -1.0)
        UIGraphicsPushContext(context!)
        image.draw(in: CGRect(x: 0, y: 0, width: size.width, height: size.height))
        UIGraphicsPopContext()
        CVPixelBufferUnlockBaseAddress(pxbuffer!, CVPixelBufferLockFlags(rawValue: 0))
        return pxbuffer
    }

    override func didReceiveMemoryWarning() {
        super.didReceiveMemoryWarning()
        // Dispose of any resources that can be recreated.
    }


}

我加载了一个煎蛋的图片，它识别成水母。。。还真有点像