public static Results <PointT> ProcessMostInliers <PointT>(IRansacModel <PointT> model, int maxIterations, int sampleSize, int minGoodPoints, double threshold, double initialModel)
{
Random random = new Random((int)DateTime.Now.Ticks);
object bestModel = initialModel;
List <PointT> bestInliers = new List <PointT>();
for (int i = 0; i < maxIterations; ++i)
{
NextSample(model, sampleSize, threshold, random, out object sampleModel, out List <PointT> inliers);
if (inliers.Count > bestInliers.Count)
{
bestInliers = inliers;
bestModel = sampleModel;
}
}
double bestError = 0.0;
foreach (var point in model.AllPoints)
{
bestError += model.PointError(point, bestModel);
}
return(new Results <PointT>()
{
BestModel = bestModel,
BestError = bestError,
Inliers = bestInliers
});
}
public bool Test(IRansacModel model) {
PlaneModel r = model as PlaneModel;
bool no_parallel_found = true;
foreach (Plane p in _b.ReferencePlanes) {
double d = Vector.ScalarProduct(r.Plane.Normal, p.Normal);
if ((1.0 - Math.Abs(d)) < 1e-2) {
no_parallel_found = false;
break;
}
}
return no_parallel_found;
}
private static void NextSample <PointT>(IRansacModel <PointT> model, int sampleSize, double threshold, Random random, out object sampleModel, out List <PointT> inliers)
{
IEnumerable <PointT> sample = PickRandomSample(model.AllPoints, sampleSize, random);
sampleModel = model.FindModel(sample);
inliers = new List <PointT>(model.AllPoints.Count);
foreach (var point in model.AllPoints)
{
if (model.PointError(point, sampleModel) < threshold)
{
inliers.Add(point);
}
}
}
public bool Test(IRansacModel model)
{
PlaneModel r = model as PlaneModel;
bool no_parallel_found = true;
foreach (Plane p in _b.ReferencePlanes)
{
double d = Vector.ScalarProduct(r.Plane.Normal, p.Normal);
if ((1.0 - Math.Abs(d)) < 1e-2)
{
no_parallel_found = false;
break;
}
}
return(no_parallel_found);
}
public static Results <PointT> Process <PointT>(IRansacModel <PointT> model, int maxIterations, int sampleSize, int minGoodPoints, double threshold, object initialModel)
{
Random random = new Random((int)DateTime.Now.Ticks);
object bestModel = initialModel;
double bestError = 10e8;
for (int i = 0; i < maxIterations; ++i)
{
NextSample(model, sampleSize, threshold, random, out object sampleModel, out List <PointT> inliers);
if (bestModel == null || inliers.Count >= minGoodPoints)
{
sampleModel = model.FindModel(inliers);
double error = 0.0;
foreach (var point in model.AllPoints)
{
error += model.PointError(point, sampleModel);
}
if (error < bestError)
{
bestError = error;
bestModel = sampleModel;
}
}
}
var bestInliers = model.AllPoints
.Where((point) => model.PointError(point, bestModel) < threshold)
.ToList();
return(new Results <PointT>()
{
BestModel = bestModel,
BestError = bestError,
Inliers = bestInliers
});
}
