public override IObservable <TArray> Process <TArray>(IObservable <Tuple <TArray, TArray> > source)
{
var outputFactory = ArrFactory <TArray> .TemplateFactory;
return(source.Select(input =>
{
var first = input.Item1;
var second = input.Item2;
var output = outputFactory(first);
CV.AbsDiff(first, second, output);
return output;
}));
}
public override IObservable <IplImage> Process(IObservable <IplImage> source)
{
return(Observable.Defer(() =>
{
int averageCount = 0;
IplImage image = null;
IplImage difference = null;
IplImage background = null;
return source.Select(input =>
{
if (background == null || background.Size != input.Size)
{
averageCount = 0;
image = new IplImage(input.Size, IplDepth.F32, input.Channels);
difference = new IplImage(input.Size, IplDepth.F32, input.Channels);
background = new IplImage(input.Size, IplDepth.F32, input.Channels);
background.SetZero();
}
var output = new IplImage(input.Size, IplDepth.U8, input.Channels);
if (averageCount < BackgroundFrames)
{
averageCount++;
output.SetZero();
CV.Acc(input, background);
if (averageCount == BackgroundFrames)
{
CV.ConvertScale(background, background, 1.0 / averageCount, 0);
}
}
else
{
CV.Convert(input, image);
switch (SubtractionMethod)
{
case SubtractionMethod.Bright:
CV.Sub(image, background, difference);
break;
case SubtractionMethod.Dark:
CV.Sub(background, image, difference);
break;
case SubtractionMethod.Absolute:
default:
CV.AbsDiff(image, background, difference);
break;
}
if (AdaptationRate > 0)
{
CV.RunningAvg(image, background, AdaptationRate);
}
CV.Threshold(difference, output, ThresholdValue, 255, ThresholdType);
}
return output;
});
}));
}
