public void Start(DetectionAlgorithm algorithm)
{
if (algorithm == DetectionAlgorithm.AUTOCORRELATION)
{
ptracker = new PitchTracker();
ptracker.PitchDetected += ptracker_PitchDetected;
ptracker.SampleRate = _microphone.SampleRate;
}
else if (algorithm == DetectionAlgorithm.YIN)
{
yin = new Yin(_microphone.SampleRate, _bufferSize/4);
}
_microphone.Start();
}
public void Start(DetectionAlgorithm algorithm)
{
if (algorithm == DetectionAlgorithm.AUTOCORRELATION)
{
ptracker = new PitchTracker();
ptracker.PitchDetected += ptracker_PitchDetected;
ptracker.SampleRate = _microphone.SampleRate;
}
else if (algorithm == DetectionAlgorithm.YIN)
{
yin = new Yin(_microphone.SampleRate, _bufferSize / 4);
}
_microphone.Start();
}
public List <ImageDetection> RunDetector(Func <FitsImage, List <ImageDetection> > Detector, FitsImage Image, string DetectorName, DetectionAlgorithm Algo)
{
var Detections = Detector(Image);
if (Detections.Count > MaxDetections)
{
LogMessage(DetectorName, "Too many detections. Check detector settings.");
return(new List <ImageDetection>());
}
foreach (var d in Detections)
{
if (d.TryFetchProperty(out PairingProperties pp))
{
pp.Algorithm = Algo;
}
else
{
d.AppendProperty(new PairingProperties()
{
Algorithm = Algo
});
}
}
AllDetections.AddRange(Detections);
AllDetectionCenters.AddRange(Detections.Select((x) => x.Barycenter.EP));
LogHookDetection(DetectorName, Detections.Count);
return(Detections);
}
