ML Kit iOS 人臉檢測錯誤

Question

我一直在嘗試使用Google ML 人臉檢測 iOS 庫，但存在一個問題，它不能與前置攝像頭配合使用，只有當我在手機上使用后置攝像頭時才能檢測到人臉。 我打印了方向，正面和背面之間的所有內容都匹配。 它似乎適用於我的 iPhone X 的正面和背面，但是當我在 iPhone 11 和 iPhone X max 上對其進行測試時，它僅適用於后置攝像頭。 我不確定是什么導致了這種不一致。 我使用的代碼如下，注意所有傳入 photoVerification 函數的圖像首先通過 fixedOrientation 函數運行以確保一致性：

 func photoVerification(image: UIImage?) {
    guard let imageFace = image else { return }
    //Enhanced Face Detection
    let options = FaceDetectorOptions()
    options.performanceMode = .accurate
    //Initialize face detector with given options
    let faceDetector = FaceDetector.faceDetector(options: options)
    // Initialize a VisionImage object with the given UIImage.
    let visionImage = VisionImage(image: imageFace)
    visionImage.orientation = imageFace.imageOrientation
    print("$$The Images Orientation is: ",imageFace.imageOrientation.rawValue)
    faceDetector.process(visionImage) { faces, error in
        guard error == nil, let faces = faces, !faces.isEmpty else {
          // [START_EXCLUDE]
          let errorString = error?.localizedDescription ?? "NO Results Possible"
            print("Error: ",errorString)
          //No face detected provide error on image
          print("No face detected!")
          self.userVerified = false
          self.addVerifiedTag(isVerified: false)
          // [END_EXCLUDE]
          return
        }

        // Faces detected
        // [START_EXCLUDE]
        //Face Has been detected Offer Verified Tag to user
        print("Face detected!")
        self.userVerified = true
        self.addVerifiedTag(isVerified: true)
    }
}


func fixedOrientation(image:UIImage) -> UIImage?{
    guard image.imageOrientation != .up else{
        //Orientation is correct
        return image
    }
    guard let cgImage = image.cgImage else{
        //CGimage not available
        return nil
    }
    guard let colorSpace = cgImage.colorSpace, let ctx = CGContext(data: nil, width: Int(image.size.width), height: Int(image.size.height), bitsPerComponent: cgImage.bitsPerComponent, bytesPerRow: 0, space: colorSpace, bitmapInfo: CGImageAlphaInfo.premultipliedLast.rawValue) else{
        return nil
    }
    var  transform:CGAffineTransform = CGAffineTransform.identity
    
    switch image.imageOrientation {
    case .down, .downMirrored:
        transform = transform.translatedBy(x: image.size.width, y: image.size.height)
        transform = transform.rotated(by: CGFloat.pi)
    case .left, .leftMirrored:
        transform = transform.translatedBy(x: image.size.width, y: 0)
        transform = transform.rotated(by: CGFloat.pi / 2.0)
    case .right, .rightMirrored:
        transform = transform.translatedBy(x: 0, y: image.size.height)
        transform = transform.rotated(by: CGFloat.pi / -2.0)
    case .up, .upMirrored:
        break
    @unknown default:
        break
    }

    // Flip image one more time if needed to, this is to prevent flipped image
    switch image.imageOrientation {
    case .upMirrored, .downMirrored:
        transform = transform.translatedBy(x: image.size.width, y: 0)
        transform = transform.scaledBy(x: -1, y: 1)
    case .leftMirrored, .rightMirrored:
        transform = transform.translatedBy(x: image.size.height, y: 0)
        transform = transform.scaledBy(x: -1, y: 1)
    case .up, .down, .left, .right:
        break
    @unknown default:
        break
    }

    ctx.concatenate(transform)

    switch image.imageOrientation {
    case .left, .leftMirrored, .right, .rightMirrored:
        ctx.draw(cgImage, in: CGRect(x: 0, y: 0, width: image.size.height, height: image.size.width))
    default:
        ctx.draw(cgImage, in: CGRect(x: 0, y: 0, width: image.size.width, height: image.size.height))
        break
    }

    guard let newCGImage = ctx.makeImage() else { return nil }
    return UIImage.init(cgImage: newCGImage, scale: 1, orientation: .up)
}

Answer 1

您帖子中的 Google ML Kit Face Detection SDK 適用於 iPhone 11 上的前置和后置攝像頭（我的運行的是 iOS 13.4，我使用的是 Xcode 11.6）。 您可以查看 iOS 快速入門示例應用程序（在 Swift 和 Objective-C 中），它演示了如何使用前置和后置攝像頭拍攝照片（或預覽實時視頻）來執行面部檢測（和其他功能）：

https://github.com/googlesamples/mlkit/tree/master/ios/quickstarts/vision