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我正在尝试使用 Vision 和 CoreML 在尽可能接近实时的跟踪对象上执行样式转换。我正在使用 AVKit 来捕获视频，并使用 AVCaptureVideoDataOutputSampleBufferDelegate 来获取每一帧。

在高层次上，我的管道是：

1) 检测人脸

2) 更新预览层以在正确的屏幕位置绘制边界框

3）将原始图像裁剪为检测到的人脸

4）通过coreML模型运行人脸图像，得到新的图像作为输出

5）用新图像填充预览层（无论它们在哪里）

我希望在计算边界框后立即放置它们（在主线程上），然后在推理完成后填充它们。但是，我发现将 coreML 推理添加到管道（在 AVCaptureOutputQueue 或 CoreMLQueue 上），边界框在推理完成之前不会更新位置。也许我错过了在闭包中如何处理队列的一些东西。代码的（希望）相关部分如下。

我正在修改来自https://developer.apple.com/documentation/vision/tracking_the_user_s_face_in_real_time的代码。

public func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer,
    from connection: AVCaptureConnection) {
    // omitting stuff that gets pixelBuffers etc formatted for use with Vision
    // and sets up tracking requests

    // Perform landmark detection on tracked faces
    for trackingRequest in newTrackingRequests {

        let faceLandmarksRequest = VNDetectFaceLandmarksRequest(completionHandler: { (request, error) in

            guard let landmarksRequest = request as? VNDetectFaceLandmarksRequest,
                let results = landmarksRequest.results as? [VNFaceObservation] else {
                    return
            }

            // Perform all UI updates (drawing) on the main queue,
            //not the background queue on which this handler is being called.

            DispatchQueue.main.async {
                self.drawFaceObservations(results) //<<- places bounding box on the preview layer
            }

            CoreMLQueue.async{ //Queue for coreML uses

                //get region of picture to crop for CoreML
                let boundingBox = results[0].boundingBox 

                //crop the input frame to the detected object
                let image: CVPixelBuffer = self.cropFrame(pixelBuffer: pixelBuffer, region: boundingBox)

                //infer on region
                let styleImage: CGImage = self.performCoreMLInference(on: image)

                //on the main thread, place styleImage into the bounding box(CAShapeLayer)
                DispatchQueue.main.async{
                    self.boundingBoxOverlayLayer?.contents = styleImage
                }
            }
        })

        do {
            try requestHandler.perform(faceLandmarksRequest)
        } catch let error as NSError {
            NSLog("Failed Request: %@", error)
        }
    }
}

除了队列/同步问题之外，我认为减速的一个原因可能是将像素缓冲区裁剪到感兴趣的区域。我在这里没有想法，任何帮助将不胜感激

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1 回答 1

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我正在使用https://github.com/maxvol/RxAVFoundation和https://github.com/maxvol/RxVision的管道来解决同步问题。

一个基本的例子 -

let textRequest: RxVNDetectTextRectanglesRequest<CVPixelBuffer> = VNDetectTextRectanglesRequest.rx.request(reportCharacterBoxes: true)
var session = AVCaptureSession.rx.session()
var requests = [RxVNRequest<CVPixelBuffer>]()

self.requests = [self.textRequest]
self
  .textRequest
  .observable
  .observeOn(Scheduler.main)
  .subscribe { [unowned self] (event) in
      switch event {
      case .next(let completion):
              self.detectTextHandler(value: completion.value, request: completion.request, error: completion.error)
          default:
          break
      }
  }
  .disposed(by: disposeBag)

self.session
  .flatMapLatest { [unowned self] (session) -> Observable<CaptureOutput> in
      let imageLayer = session.previewLayer
      imageLayer.frame = self.imageView.bounds
      self.imageView.layer.addSublayer(imageLayer)
      return session.captureOutput
  }
  .subscribe { [unowned self] (event) in
      switch event {
      case .next(let captureOutput):
          guard let pixelBuffer = CMSampleBufferGetImageBuffer(captureOutput.sampleBuffer) else {
              return
          }
          var requestOptions: [VNImageOption: Any] = [:]
          if let camData = CMGetAttachment(captureOutput.sampleBuffer, key: kCMSampleBufferAttachmentKey_CameraIntrinsicMatrix, attachmentModeOut: nil) {
              requestOptions = [.cameraIntrinsics: camData]
          }
          let imageRequestHandler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer, orientation: .up, options: requestOptions)
          do {
              try imageRequestHandler.rx.perform(self.requests, with: pixelBuffer)
          } catch {
              os_log("error: %@", "\(error)")
          }
          break
      case .error(let error):
          os_log("error: %@", "\(error)")
          break
      case .completed:
          // never happens
          break
      }
  }
  .disposed(by: disposeBag)
于 2018-10-02T11:18:33.560 回答