计算 AVCaptureVideoDataOutput 馈送平均 RGB 像素值的最快方法 - CPU/GPU

Question

我想要来自 AVCaptureVideoDataOutput 的提要中整个图像的平均像素值，我目前正在捕捉图像并循环遍历像素以求和它们。

我想知道是否有更有效的方法来使用 GPU/openGL 来做到这一点，因为这是一个可并行化的图像处理任务。（也许是严重的高斯模糊，并读取中心像素值？）

一个特定要求是获得高精度结果，利用高水平的平均。请注意下面的 CGFloat 结果。

当前的 swift 2 代码：

编辑：添加了 CIAreaAverage 的实现，如下面 Simon 的建议。它由useGPUbool分隔。

func captureOutput(captureOutput: AVCaptureOutput!, didOutputSampleBuffer sampleBuffer: CMSampleBuffer!, fromConnection connection: AVCaptureConnection!) {

    var redmean:CGFloat = 0.0;
    var greenmean:CGFloat = 0.0;
    var bluemean:CGFloat = 0.0;

    if (useGPU) {
            let pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer)
            let cameraImage = CIImage(CVPixelBuffer: pixelBuffer!)
            let filter = CIFilter(name: "CIAreaAverage")
            filter!.setValue(cameraImage, forKey: kCIInputImageKey)
            let outputImage = filter!.valueForKey(kCIOutputImageKey) as! CIImage!

            let ctx = CIContext(options:nil)
            let cgImage = ctx.createCGImage(outputImage, fromRect:outputImage.extent)

            let rawData:NSData = CGDataProviderCopyData(CGImageGetDataProvider(cgImage))!
            let pixels = UnsafePointer<UInt8>(rawData.bytes)
            let bytes = UnsafeBufferPointer<UInt8>(start:pixels, count:rawData.length)
            var BGRA_index = 0
            for pixel in UnsafeBufferPointer(start: bytes.baseAddress, count: bytes.count) {
                switch BGRA_index {
                case 0:
                    bluemean = CGFloat (pixel)
                case 1:
                    greenmean = CGFloat (pixel)
                case 2:
                    redmean = CGFloat (pixel)
                case 3:
                    break
                default:
                    break
                }
                BGRA_index++

            }
     } else {
            let imageBuffer = CMSampleBufferGetImageBuffer(sampleBuffer)
            CVPixelBufferLockBaseAddress(imageBuffer!, 0)

            let baseAddress = CVPixelBufferGetBaseAddressOfPlane(imageBuffer!, 0)
            let bytesPerRow = CVPixelBufferGetBytesPerRow(imageBuffer!)
            let width = CVPixelBufferGetWidth(imageBuffer!)
            let height = CVPixelBufferGetHeight(imageBuffer!)
            let colorSpace = CGColorSpaceCreateDeviceRGB()

            let bitmapInfo = CGBitmapInfo(rawValue: CGImageAlphaInfo.PremultipliedFirst.rawValue).rawValue | CGBitmapInfo.ByteOrder32Little.rawValue

            let context = CGBitmapContextCreate(baseAddress, width, height, 8, bytesPerRow, colorSpace, bitmapInfo)
            let imageRef = CGBitmapContextCreateImage(context)
            CVPixelBufferUnlockBaseAddress(imageBuffer!, 0)
            let data:NSData = CGDataProviderCopyData(CGImageGetDataProvider(imageRef))!
            let pixels = UnsafePointer<UInt8>(data.bytes)
            let bytes = UnsafeBufferPointer<UInt8>(start:pixels, count:data.length)
            var redsum:CGFloat = 0
            var greensum:CGFloat  = 0
            var bluesum:CGFloat  = 0
            var BGRA_index = 0
            for pixel in UnsafeBufferPointer(start: bytes.baseAddress, count: bytes.count) {
            switch BGRA_index {
            case 0:
                bluesum += CGFloat (pixel)
            case 1:
                greensum += CGFloat (pixel)
            case 2:
                redsum += CGFloat (pixel)
            case 3:
                //alphasum += UInt64(pixel)
                break
            default:
                break
            }

            BGRA_index += 1
            if BGRA_index == 4 { BGRA_index = 0 }
        }
        redmean = redsum / CGFloat(bytes.count)
        greenmean = greensum / CGFloat(bytes.count)
        bluemean = bluesum / CGFloat(bytes.count)            
        }

print("R:\(redmean) G:\(greenmean) B:\(bluemean)")

Answer 1

CIAreaAverage 过滤器性能不佳的问题和原因是缺少输入范围的定义。因此，过滤器的输出与输入图像具有相同的大小，因此您可以遍历完整的图像而不是 1×1 像素的图像。因此，执行所需的时间与您的初始版本相同。

如CIAreaAverage文档中所述，您可以指定inputExtent参数。可以在类似问题的答案中找到如何快速完成此操作：

    let cameraImage = CIImage(CVPixelBuffer: pixelBuffer!)
    let extent = cameraImage.extent
    let inputExtent = CIVector(x: extent.origin.x, y: extent.origin.y, z: extent.size.width, w: extent.size.height)
    let filter = CIFilter(name: "CIAreaAverage", withInputParameters: [kCIInputImageKey: cameraImage, kCIInputExtentKey: inputExtent])!
    let outputImage = filter.outputImage!

如果你想挤出更多的性能，你可以确保你重用你的 CIContext，而不是为每个捕获的帧重新创建它。