private void fitCircleToolStripMenuItem_Click(object sender, EventArgs e)
{
List <Vector2> gaussian_i_pts = new List <Vector2>();
foreach (Vector2 pt in gmm.pts)
{
if (pt.gaussian_idx[manual_level - 1] == selected_gaussian_idx)
{
gaussian_i_pts.Add(pt);
}
}
if (gaussian_i_pts.Count < 3)
{
return;
}
BaseModel circleModel = new CircleModel();
circleModel = RANSAC.Fit(gaussian_i_pts, circleModel, 3, circle_res);
gmm.baseModels.Add(circleModel);
drawingGaussians[selected_gaussian_idx].dropped = true;
drawingGaussians[selected_gaussian_idx].selected = false;
gmm.gaussian_list[selected_gaussian_idx].dropped = true;
gmm.gaussian_list[selected_gaussian_idx].selected = false;
this.Refresh();
// TODO: deep copy of gmm.gaussian_list
//gmm.gaussian_list[selected_gaussian_idx].dropped = false;
}
public void DetectLastLevel(int level)
{
IEnumerable <int> level_gaussians = GetLevel(level - 1);
foreach (int i in level_gaussians)
{
List <Vector2> gaussian_i_pts = new List <Vector2>();
foreach (Vector2 pt in pts)
{
if (pt.gaussian_idx[level - 1] == i)
{
gaussian_i_pts.Add(pt);
}
}
if (gaussian_i_pts.Count < 2)
{
continue;
}
BaseModel lineModel = new LineModel();
lineModel = RANSAC.Fit(gaussian_i_pts, lineModel, 2, 2.00F);
baseModels.Add(lineModel);
}
}
private List <Gaussian_2D> ClusteringInitGMM(int level, int init_type)
{
List <Gaussian_2D> cluster_list = new List <Gaussian_2D>();
if (level != 0)
{
IEnumerable <int> parent_level_gaussians = GetLevel(level - 1);
foreach (int i in parent_level_gaussians)
{
List <Vector2> parent_pts = new List <Vector2>();
List <Gaussian_2D> cluster_list_i = new List <Gaussian_2D>();
foreach (Vector2 pt in pts)
{
if (pt.gaussian_idx[level - 1] == i)
{
parent_pts.Add(pt);
}
}
//if there are fewer points than num_gaussian * 2 in the parent gaussian, stop partition
//if (parent_pts.Count <= num_gaussian * 2 || gaussian_list[i].partition == false)
if (parent_pts.Count < num_gaussian || gaussian_list[i].partition == false)
{
Console.WriteLine("===========Stopping at gaussian {0}==============", i);
//gaussian_list[i].partition = false;
for (int j = 0; j < num_gaussian; j++)
{
Gaussian_2D gau = new Gaussian_2D();
gau.partition = false;
gau.dropped = true;
cluster_list_i.Add(gau);
}
cluster_list = cluster_list.Concat(cluster_list_i).ToList();
if (parent_pts.Count > 2 && gaussian_list[i].dropped == false)
{
BaseModel lineModel = new LineModel();
lineModel = RANSAC.Fit(parent_pts, lineModel, 2, 2.00F);
baseModels.Add(lineModel);
}
continue;
}
if (init_type == 1)
{
cluster_list_i = FuzzyCMeans.fit(parent_pts, num_gaussian);
}
else if (init_type == 0)
{
cluster_list_i = KMeans.fit(parent_pts, num_gaussian);
}
cluster_list = cluster_list.Concat(cluster_list_i).ToList();
}
}
else
{
if (init_type == 1)
{
cluster_list = FuzzyCMeans.fit(pts, num_gaussian);
}
else if (init_type == 0)
{
cluster_list = KMeans.fit(pts, num_gaussian);
}
}
return(cluster_list);
}
