将 CoreML 与 React Native 结合使用

Question

我收到了错误

参数标签 '(image:)' 不匹配任何可用的重载

我遵循了本教程here 和苹果的文档，但是当我尝试将框架桥接到 React Native 的图像之外时，我开始收到此错误。 Swift 和 Reac Native 之间的桥梁正在发挥作用，只有当我开始尝试使用 coreML 时才会出现错误

我认为这与新的 swift 语法有关，但我不知道如何修复它，我还没有看到有人将 CoreML 与 React Native 一起使用

这是我的全部功能：

import Foundation
import CoreML

@objc(Printer)
class Printer: NSObject {

  @objc func imageRec(_ image:CGImage) -> CVPixelBuffer? {
let model = Inceptionv3();

  UIGraphicsBeginImageContextWithOptions(CGSize(width: 299, height: 299), true, 1.0)
//image.draw(in: CGRect(x: 0, y: 0, width: 299, height: 299))
let newImage = UIGraphicsGetImageFromCurrentImageContext()!
UIGraphicsEndImageContext()

let attrs = [kCVPixelBufferCGImageCompatibilityKey: kCFBooleanTrue, kCVPixelBufferCGBitmapContextCompatibilityKey: kCFBooleanTrue] as CFDictionary
var pixelBuffer : CVPixelBuffer?
let status = CVPixelBufferCreate(kCFAllocatorDefault, Int(newImage.size.width), Int(newImage.size.height), kCVPixelFormatType_32ARGB, attrs, &pixelBuffer)
guard (status == kCVReturnSuccess) else {
  return nil
}

CVPixelBufferLockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))
let pixelData = CVPixelBufferGetBaseAddress(pixelBuffer!)

let rgbColorSpace = CGColorSpaceCreateDeviceRGB()
let context = CGContext(data: pixelData, width: Int(newImage.size.width), height: Int(newImage.size.height), bitsPerComponent: 8, bytesPerRow: CVPixelBufferGetBytesPerRow(pixelBuffer!), space: rgbColorSpace, bitmapInfo: CGImageAlphaInfo.noneSkipFirst.rawValue)

context?.translateBy(x: 0, y: newImage.size.height)
context?.scaleBy(x: 1.0, y: -1.0)

UIGraphicsPushContext(context!)
newImage.draw(in: CGRect(x: 0, y: 0, width: newImage.size.width, height: newImage.size.height))
UIGraphicsPopContext()
CVPixelBufferUnlockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))

guard let prediction = try? model.prediction(image: newImage) else {
}

}
}

Answer 1

你必须初始化modelInput（这是一个当你添加和数据模型时自动生成的类）类，然后将modelInput发送到预测。

以下是可能有帮助的代码 sn-p：

        // create indupt data model
        // in your case this must be taking image as argument
        let input = ProfitPredictorInput.init(R_D_Spend: 
          Double(rndInv)!, Administration: Double(adminInv)!, 
           Marketing_Spend: Double(marketingInv)!)

        // give input data model to your mlmodel
        let outData = try mlModel?.prediction(input: input)

您可以参考this。