Xcode9学习笔记77

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 UIKitimport CoreMLclass 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