PoseEstimationViewController.swift

extension PoseEstimationViewController: AVCaptureVideoDataOutputSampleBufferDelegate {

    func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {
        // FritzVisionImage objects offer convient ways to manipulate
        // images used as input to machine learning models.
        // You can resize, crop, and scale images to your needs.
        let image = FritzVisionImage(sampleBuffer: sampleBuffer, connection: connection)

        // Set options for our pose estimation model using the constants
        // we initialized earlier in the ViewController.
        let options = FritzVisionPoseModelOptions()
        options.minPoseThreshold = poseThreshold

        // Run the model itself on an input image.
        guard let poseResult = try? visionModel.predict(image, options: options) else { 
            if let rotated = image.rotate() {
                let img = UIImage(pixelBuffer: rotated)
                DispatchQueue.main.async {
                    self?.cameraView.image = img
                }
            }
            return 
        }
        let poses = poseResult.poses()
        
        DispatchQueue.main.async {
            self.cameraView.image = image.draw(poses: poses)   
        }
    }
}