为什么iPhone XS在使用相机时的CPU性能会比iPhone 6S Plus更差？

Question

我正在使用实时摄像头输出来更新MTKView上的CIImage。我的主要问题是，虽然我遇到的所有设置都是相同的，但是我有一个较大的，负面的性能差异，其中较旧的iPhone获得比较新的iPhone更好的CPU性能。

这是一篇冗长的帖子，但我决定将这些细节包括在内，因为它们可能对这个问题的原因很重要。请告诉我还能包括哪些内容。

下面，我有一个带有两个调试bool的captureOutput函数，我可以在运行时打开和关闭它。我用它来试图确定问题的原因。

applyLiveFilter - bool是否用CIFilter操纵CIImage。

updateMetalView - bool是否更新MTKView的CIImage。

// live output from camera
func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection){

    /*              
     Create CIImage from camera.
     Here I save a few percent of CPU by using a function 
     to convert a sampleBuffer to a Metal texture, but
     whether I use this or the commented out code 
     (without captureOutputMTLOptions) does not have 
     significant impact. 
    */

    guard let texture:MTLTexture = convertToMTLTexture(sampleBuffer: sampleBuffer) else{
        return
    }

    var cameraImage:CIImage = CIImage(mtlTexture: texture, options: captureOutputMTLOptions)!

    var transform: CGAffineTransform = .identity

    transform = transform.scaledBy(x: 1, y: -1)

    transform = transform.translatedBy(x: 0, y: -cameraImage.extent.height)

    cameraImage = cameraImage.transformed(by: transform)

    /*
    // old non-Metal way of getting the ciimage from the cvPixelBuffer
    guard let pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer) else
    {
        return
    }

    var cameraImage:CIImage = CIImage(cvPixelBuffer: pixelBuffer)
    */

    var orientation = UIImage.Orientation.right

    if(isFrontCamera){
        orientation = UIImage.Orientation.leftMirrored
    }

    // apply filter to camera image
    if debug_applyLiveFilter {
        cameraImage = self.applyFilterAndReturnImage(ciImage: cameraImage, orientation: orientation, currentCameraRes:currentCameraRes!)
    }

    DispatchQueue.main.async(){
        if debug_updateMetalView {
            self.MTLCaptureView!.image = cameraImage
        }
    }

}

下面是两个手机切换上面讨论的不同bool组合的结果图表：

即使没有Metal视图的CIIMage更新并且没有应用过滤器，iPhone XS的CPU比iPhone 6S Plus高2％，这不是一个显着的开销，但让我怀疑相机如何捕获在设备之间是不同的。

• 我的AVCaptureSession的预设在两部手机之间设置相同（AVCaptureSession.Preset.hd1280x720）
• 从captureOutput创建的CIImage与两部手机之间的大小（范围）相同。

我需要在这两个手机AVCaptureDevice的设置之间手动设置任何设置，包括activeFormat属性，以使它们在设备之间相同吗？

我现在的设置是：

if let captureDevice = AVCaptureDevice.default(for:AVMediaType.video) {
    do {
        try captureDevice.lockForConfiguration()
            captureDevice.isSubjectAreaChangeMonitoringEnabled = true
            captureDevice.focusMode = AVCaptureDevice.FocusMode.continuousAutoFocus
            captureDevice.exposureMode = AVCaptureDevice.ExposureMode.continuousAutoExposure
        captureDevice.unlockForConfiguration()

    } catch {
        // Handle errors here
        print("There was an error focusing the device's camera")
    }
}

我的MTKView基于Simon Gladman编写的代码，对性能进行了一些编辑，并在使用Apple建议的Core Animation将其放大到屏幕宽度之前缩放渲染。

class MetalImageView: MTKView
{
    let colorSpace = CGColorSpaceCreateDeviceRGB()

    var textureCache: CVMetalTextureCache?

    var sourceTexture: MTLTexture!

    lazy var commandQueue: MTLCommandQueue =
        {
            [unowned self] in

            return self.device!.makeCommandQueue()
            }()!

    lazy var ciContext: CIContext =
        {
            [unowned self] in

            return CIContext(mtlDevice: self.device!)
            }()


    override init(frame frameRect: CGRect, device: MTLDevice?)
    {
        super.init(frame: frameRect,
                   device: device ?? MTLCreateSystemDefaultDevice())



        if super.device == nil
        {
            fatalError("Device doesn't support Metal")
        }

        CVMetalTextureCacheCreate(kCFAllocatorDefault, nil, self.device!, nil, &textureCache)

        framebufferOnly = false

        enableSetNeedsDisplay = true

        isPaused = true

        preferredFramesPerSecond = 30
    }

    required init(coder: NSCoder)
    {
        fatalError("init(coder:) has not been implemented")
    }

    // The image to display
    var image: CIImage?
    {
        didSet
        {
            setNeedsDisplay()
        }
    }

    override func draw(_ rect: CGRect)
    {
        guard var
            image = image,
            let targetTexture:MTLTexture = currentDrawable?.texture else
        {
            return
        }

        let commandBuffer = commandQueue.makeCommandBuffer()

        let customDrawableSize:CGSize = drawableSize

        let bounds = CGRect(origin: CGPoint.zero, size: customDrawableSize)

        let originX = image.extent.origin.x
        let originY = image.extent.origin.y

        let scaleX = customDrawableSize.width / image.extent.width
        let scaleY = customDrawableSize.height / image.extent.height

        let scale = min(scaleX*IVScaleFactor, scaleY*IVScaleFactor)
        image = image
            .transformed(by: CGAffineTransform(translationX: -originX, y: -originY))
            .transformed(by: CGAffineTransform(scaleX: scale, y: scale))


        ciContext.render(image,
                         to: targetTexture,
                         commandBuffer: commandBuffer,
                         bounds: bounds,
                         colorSpace: colorSpace)


        commandBuffer?.present(currentDrawable!)

        commandBuffer?.commit()

    }

}

我的AVCaptureSession（captureSession）和AVCaptureVideoDataOutput（videoOutput）设置如下：

func setupCameraAndMic(){
    let backCamera = AVCaptureDevice.default(for:AVMediaType.video)

    var error: NSError?
    var videoInput: AVCaptureDeviceInput!
    do {
        videoInput = try AVCaptureDeviceInput(device: backCamera!)
    } catch let error1 as NSError {
        error = error1
        videoInput = nil
        print(error!.localizedDescription)
    }

    if error == nil &&
        captureSession!.canAddInput(videoInput) {

        guard CVMetalTextureCacheCreate(kCFAllocatorDefault, nil, MetalDevice, nil, &textureCache) == kCVReturnSuccess else {
            print("Error: could not create a texture cache")
            return
        }

        captureSession!.addInput(videoInput)            

        setDeviceFrameRateForCurrentFilter(device:backCamera)

        stillImageOutput = AVCapturePhotoOutput()

        if captureSession!.canAddOutput(stillImageOutput!) {
            captureSession!.addOutput(stillImageOutput!)

            let q = DispatchQueue(label: "sample buffer delegate", qos: .default)
            videoOutput.setSampleBufferDelegate(self, queue: q)
            videoOutput.videoSettings = [
                kCVPixelBufferPixelFormatTypeKey as AnyHashable as! String: NSNumber(value: kCVPixelFormatType_32BGRA),
                kCVPixelBufferMetalCompatibilityKey as String: true
            ]
            videoOutput.alwaysDiscardsLateVideoFrames = true

            if captureSession!.canAddOutput(videoOutput){
                captureSession!.addOutput(videoOutput)
            }

            captureSession!.startRunning()

        }

    }

    setDefaultFocusAndExposure()
}

视频和麦克风记录在两个独立的流中。麦克风和录制视频的细节已被遗漏，因为我的重点是现场摄像机输出的性能。

---

更新 - 我在GitHub上有一个简化的测试项目，可以更容易地测试我遇到的问题：https://github.com/PunchyBass/Live-Filter-test-project

Answer 1

从我的脑海中，你不是将梨与梨进行比较，即使你使用2.49 GHz的A12和1.85 GHz的A9运行，相机之间的差异也很大，即使你使用相同的参数XS的相机有几个功能需要更多的CPU资源（双摄像头，稳定，智能HDR等）。

对于这些消息来源感到抱歉，我试图找到这些功能的CPU成本指标，但遗憾的是，根据您的需要，我找不到这些信息与营销无关，当他们将其作为有史以来最好的相机销售时智能手机。

他们将它作为最好的处理器出售，我们不知道使用配备A9处理器的XS相机会发生什么，它可能会崩溃，我们永远不会知道......

PS ....您的指标是针对整个处理器还是针对所使用的核心？对于整个处理器，您还需要考虑设备可以执行的其他任务，对于单核，是200％的21％和600％的39％