private List <Vector2> ApproximateCurveAxis(List <Line2> skel_lines)
{
Image <Rgb, byte> curveaxis_img = body_img.Copy().Convert <Rgb, byte>();
List <Vector2> skel_points = new List <Vector2>();
//Image<Gray, byte> temp = face_img[0].Copy();
//var element = CvInvoke.GetStructuringElement(ElementShape.Cross, new Size(3, 3), new Point(-1, -1));
//CvInvoke.Dilate(temp, temp, element, new Point(-1, -1), 10, BorderType.Reflect, default(MCvScalar));
//CvInvoke.Subtract(ori_prune_img, temp, ori_prune_img);
skel_points = IExtension.GetMaskPoints(ori_prune_img);
for (int i = 0; i < skel_points.Count; i++)
{
if (ori_prune_img[(int)skel_points[i].y, (int)skel_points[i].x].Equals(new Gray(128)))
{
this.end_points.Add(i);
}
}
List <Vector2> path_points = new List <Vector2>();
List <Vector2> top_mask_point = IExtension.GetMaskPoints(this.face_img[0]);
Vector2 top_center = Utility.Average(top_mask_point);
//double guess_radius = Math.Sqrt(top_mask_point.Count / Math.PI);
Vector2 start_point = top_center;
List <Vector2> attach_boundary = new List <Vector2>();
if (noface)
{
// Vector2 attach_center = Utility.Average(IExtension.GetBoundary(this.attach_img));
// start_point = attach_center;
attach_boundary = IExtension.GetBoundary(this.attach_img);
}
// closest to top face center
int startidx = 0;
double mindis_topcenter = double.MaxValue;
for (int i = 0; i < end_points.Count; i++)
{
double dis = double.MaxValue;
if (noface)
{
dis = Utility.DistancePoint2Set(skel_points[end_points[i]], attach_boundary);
}
else
{
dis = Vector2.Distance(skel_points[end_points[i]], start_point);
}
if (dis < mindis_topcenter)
{
mindis_topcenter = dis;
startidx = end_points[i];
}
}
path_points = FindLongestPath(skel_points, startidx);
double diss = Vector2.Distance(path_points.First(), start_point);
double dise = Vector2.Distance(path_points.Last(), start_point);
if (dise < diss)
{
path_points.Reverse();
}
path_points = IExtension.ResetPath(path_points, 20);
// add first point
if (!noface)
{
path_points.Insert(0, top_center);
// extend ending
Line2 endray = new Line2(path_points[path_points.Count - 2], path_points[path_points.Count - 1]);
path_points.Add(endray.GetPointwithT((float)endray.Length() * 10));
//reset path to 3
path_points = IExtension.ResetPath(path_points, 3);
}
else
{
path_points = IExtension.ResetPath(path_points, 3);
path_points.RemoveRange(0, (int)(0.05 * path_points.Count));
//path_points.Insert(0, top_center);
}
#region visualize
curveaxis_img = body_img.Copy().Convert <Rgb, byte>();
for (int i = 0; i < path_points.Count; i++)
{
curveaxis_img.Draw(new CircleF(new PointF(path_points[i].x, path_points[i].y), 2.0f), new Rgb(255, 0, i * 2), 1);
}
curveaxis_img.Draw(new CircleF(new PointF(path_points[0].x, path_points[0].y), 2.0f), new Rgb(0, 255, 0), 1);
curveaxis_img.Save(index_forname.ToString() + this.label_forname.ToString() + "_axis_curve.png");
#endregion
return(path_points);
}
private Line2 ApproximateFromTop()
{
//guess axis with top face(s)
Line2 main_axis = null;
face_center = new List <Vector2>();
List <Vector2> normal = new List <Vector2>();
List <double> minoraxislength = new List <double>();
foreach (Image <Gray, byte> fimg in face_img)
{
Vector2 mean = new Vector2();
List <Vector2> points = IExtension.GetMaskPoints(fimg);
foreach (Vector2 p in points)
{
mean += p;
}
mean /= points.Count;
face_center.Add(mean);
float W = points.Count;
float[,] C = new float[2, 2];
foreach (Vector2 point in points)
{
C[0, 0] += (point.x - mean.x) * (point.x - mean.x);
C[0, 1] += (point.x - mean.x) * (point.y - mean.y);
C[1, 0] += (point.y - mean.y) * (point.x - mean.x);
C[1, 1] += (point.y - mean.y) * (point.y - mean.y);
}
C[0, 0] /= W;
C[0, 1] /= W;
C[1, 0] /= W;
C[1, 1] /= W;
Matrix2d CM = new Matrix2d(C);
NumericalRecipes.SVD svd = new NumericalRecipes.SVD(C);
//svd.w - eigenvalue, start from 1
//svd.u - eigenvector, start from 1
int max = 1, min = 2;
if (svd.w[max] < svd.w[min])
{
int temp = max;
max = min;
min = temp;
}
float major = 2 * Mathf.Sqrt(svd.w[max]);
Vector2 majoraxis = new Vector2(svd.u[1, max], svd.u[2, max]);
majoraxis.Normalize();
float minor = 2 * Mathf.Sqrt(svd.w[min]);
Vector2 minoraxis = new Vector2(svd.u[1, min], svd.u[2, min]);
minoraxis.Normalize();
Vector2 majorendp = mean + majoraxis * major;
Vector2 majorstartp = mean - majoraxis * major;
Vector2 minorendp = mean + minoraxis * minor;
Vector2 minorstartp = mean - minoraxis * minor;
//minoraxislength.Add(Vector2.Distance(minorendp, minorstartp));
minoraxislength.Add((double)minor * 2);
normal.Add(Utility.PerpendicularRight(majoraxis));
//normal.Add(majoraxis);
}
if (face_center.Count > 1)
{
//Vector2 mean_normal = normal.First();
Line2 best_top_normal_line = new Line2(face_center.First(), normal.First(), true);
double maxdis = 0;
int farthesttopidx = 0;
for (int i = 1; i < face_center.Count; i++)
{
double tofirstcenterdis = Vector2.Distance(face_center[0], face_center[i]);
if (tofirstcenterdis > maxdis)
{
maxdis = tofirstcenterdis;
farthesttopidx = i;
}
double dis = best_top_normal_line.DistanceToLine(face_center[i]);
if (dis > 10)
{
main_axis = null;
}
}
main_axis = new Line2(face_center.First(), face_center[farthesttopidx]);
}
else
{
Line2 top_normal_line = new Line2(face_center.First(), normal.First(), true);
Vector2 online_point = top_normal_line.GetPointwithT((float)minoraxislength[0]);
if (online_point.x >= 0 && online_point.y >= 0 && online_point.x < body_img.Width && online_point.y < body_img.Height)
{
if (!this.body_img[(int)online_point.y, (int)online_point.x].Equals(new Gray(255)))
{
top_normal_line.Flip();
}
}
else
{
top_normal_line.Flip();
}
main_axis = top_normal_line;
}
return(main_axis);
}
private List <Vector2> ApproximateStraightAxis(List <Line2> skel_lines)
{
// from skeleton lines(aka. thining image lines) (find lines that have the same direction with guessed axis <- when top face is known)
// ransac, fit one line as main axis
// update end points
// set top circle center as start point
// extend end point
Line2 new_main_axis = null;
Image <Rgb, byte> mainaxis_img = body_img.Copy().Convert <Rgb, byte>();
Line2 main_axis = null;
if (iscube)
{
main_axis = ApproximateFromCubeTop();
}
else
{
main_axis = ApproximateFromTop();
}
if (main_axis == null)
{
return(null);
}
if (noface)
{
NumericalRecipes.RansacLine2d rcl = new NumericalRecipes.RansacLine2d();
List <Vector2> thin_points = IExtension.GetMaskPoints(this.ori_thin_img);
List <Vector2> linepoints = new List <Vector2>();
for (int i = 0; i < skel_lines.Count; i++)
{
linepoints.AddRange(skel_lines[i].SamplePoints());
}
//Line2 bestline = rcl.Estimate(linepoints);
Line2 bestline = rcl.Estimate(thin_points);
double diss = Vector2.Distance(bestline.start, face_center[0]);
double dise = Vector2.Distance(bestline.end, face_center[0]);
if (dise < diss)
{
bestline.Flip();
}
new_main_axis = bestline;
}
else
{
// use ori thinning image as guidance
LineSegment2D[] lines = ori_thin_img.HoughLinesBinary(
1, //Distance resolution in pixel-related units
Math.PI / 180.0, //Angle resolution measured in radians.
3, //threshold
4, //min Line width
1 //gap between lines
)[0]; //Get the lines from the first channel
skel_lines.Clear();
foreach (LineSegment2D line in lines)
{
skel_lines.Add(new Line2(new Vector2(line.P1.X, line.P1.Y), new Vector2(line.P2.X, line.P2.Y)));
}
Line2 bestline = FitSimilarLine(skel_lines, main_axis);
if (Line2.IsParallel(bestline, main_axis, 5))
{
new_main_axis = bestline;
}
else
{
new_main_axis = main_axis;
}
}
// update end
List <Vector2> ori_skel_points = IExtension.GetMaskPoints(ori_thin_img);
for (int i = 0; i < ori_skel_points.Count; i++)
{
new_main_axis.UpdateEnd(ori_skel_points[i]);
}
new_main_axis.start = new_main_axis.ProjToLine(face_center.First());
new_main_axis.start = new_main_axis.GetPointwithT(4);
List <Vector2> axis_points = new List <Vector2>();
// axis_points.Add(face_center.First());
axis_points.AddRange(new_main_axis.SamplePoints());
axis_points.Add(new_main_axis.GetPointwithT((float)new_main_axis.Length() * 1.2f));
axis_points = IExtension.ResetPath(axis_points, 3);
#region visualize
Image <Rgb, byte> mainaxis_point_img = body_img.Copy().Convert <Rgb, byte>();
foreach (Vector2 v in axis_points)
{
mainaxis_point_img.Draw(new CircleF(new PointF(v.x, v.y), 2.0f), new Rgb(255, 0, 0), 1);
}
mainaxis_point_img.Draw(new CircleF(new PointF(axis_points.First().x, axis_points.First().y), 3.0f), new Rgb(0, 255, 0), 1);
mainaxis_point_img.Save(index_forname.ToString() + this.label_forname.ToString() + "_axis_straight.png");
#endregion
return(axis_points);
}
private Line2 ApproximateFromCubeTop()
{
#region get corner points
// get corner points
VectorOfVectorOfPoint con = new VectorOfVectorOfPoint();
Image <Gray, byte> img_copy = this.face_img[0].Copy();
CvInvoke.FindContours(img_copy, con, img_copy, RetrType.Ccomp, ChainApproxMethod.ChainApproxSimple);
int maxcomp = 0, max_con_idx = -1;
for (int i = 0; i < con.Size; i++)
{
if (con[i].Size > maxcomp)
{
maxcomp = con[i].Size;
max_con_idx = i;
}
}
// found max component's contour
// simplify contours
VectorOfPoint con2 = new VectorOfPoint();
con2 = con[max_con_idx];
double alpha = 0.01; // 越小越接近曲线
int iter = 0;
List <Vector2> corner_points = new List <Vector2>();
while (con2.Size != 4)
{
if (iter++ > 200)
{
break;
}
double epsilon = alpha * CvInvoke.ArcLength(con[max_con_idx], true);
CvInvoke.ApproxPolyDP(con[max_con_idx], con2, epsilon, true);
if (con2.Size > 4)
{
alpha += 0.01;
corner_points.Clear();
for (int i = 0; i < con2.Size; i++)
{
corner_points.Add(new Vector2(con2[i].X, con2[i].Y));
}
}
if (con2.Size < 4)
{
alpha -= 0.003;
}
}
if (con2.Size == 4)
{
corner_points.Clear();
for (int i = 0; i < con2.Size; i++)
{
corner_points.Add(new Vector2(con2[i].X, con2[i].Y));
}
}
else
{
int removei = corner_points.Count - 4;
for (int i = 0; i < removei; i++)
{
corner_points.RemoveAt(1);
}
}
face_center = new List <Vector2>();
face_center.Add(Utility.Average(corner_points));
List <Vector2> boundary2_face = IExtension.GetBoundary(this.face_img[0]);
List <Vector2> boundary2_body = ExtractOutline(this.body_img, boundary2_face);
int[] i_corner = SelectTwoCorners(corner_points, boundary2_body, this.body_img);
#endregion
// body img fit line
Image <Gray, byte> temp = body_img.Copy();
Image <Gray, byte> body_bound = temp.Canny(60, 100);
LineSegment2D[] lines = body_bound.HoughLinesBinary(
1, //Distance resolution in pixel-related units
Math.PI / 180.0, //Angle resolution measured in radians.
3, //threshold
4, //min Line width
1 //gap between lines
)[0]; //Get the lines from the first channel
var element = CvInvoke.GetStructuringElement(ElementShape.Cross, new Size(3, 3), new Point(-1, -1));
CvInvoke.Dilate(this.face_img[0], temp, element, new Point(-1, -1), 30, BorderType.Reflect, default(MCvScalar));
//temp.Save("face_dilate.png");
Image <Gray, byte> lineimg = temp.CopyBlank();
List <Line2> body_lines = new List <Line2>();
foreach (LineSegment2D line in lines)
{
if (!temp[line.P1.Y, line.P1.X].Equals(new Gray(255)) && !temp[line.P2.Y, line.P2.X].Equals(new Gray(255)))
{
body_lines.Add(new Line2(new Vector2(line.P1.X, line.P1.Y), new Vector2(line.P2.X, line.P2.Y)));
lineimg.Draw(line, new Gray(255), 2);
}
}
//lineimg.Save("body_line.png");
/// use corner points to find lines
double mindis0 = double.MaxValue, mindis1 = double.MaxValue;
int line0 = -1, line1 = -1;
for (int i = 0; i < body_lines.Count; i++)
{
double dis0 = Mathf.Min(Vector2.Distance(corner_points[i_corner[0]], body_lines[i].start), Vector2.Distance(corner_points[i_corner[0]], body_lines[i].end));
double dis1 = Mathf.Min(Vector2.Distance(corner_points[i_corner[1]], body_lines[i].start), Vector2.Distance(corner_points[i_corner[1]], body_lines[i].end));
if (dis0 < mindis0)
{
mindis0 = dis0;
line0 = i;
}
if (dis1 < mindis1)
{
mindis1 = dis1;
line1 = i;
}
}
// find similar
// straight line
Line2 body_line0 = FitCloseLine(body_lines, body_lines[line0], 50);
Line2 body_line1 = FitCloseLine(body_lines, body_lines[line1], 50);
if (Vector2.Distance(corner_points[i_corner[0]], body_line0.start) < Vector2.Distance(corner_points[i_corner[0]], body_line0.end))
{
body_line0.Flip();
}
if (Vector2.Distance(corner_points[i_corner[1]], body_line1.start) < Vector2.Distance(corner_points[i_corner[1]], body_line1.end))
{
body_line1.Flip();
}
Vector2 meandir = (body_line0.dir + body_line1.dir).normalized;
Line2 top_normal_line = new Line2(face_center.First(), meandir, true);
Vector2 online_point = top_normal_line.GetPointwithT(Vector2.Distance(corner_points[0], corner_points[1]));
if (online_point.x >= 0 && online_point.y >= 0 && online_point.x < body_img.Width && online_point.y < body_img.Height)
{
if (!this.body_img[(int)online_point.y, (int)online_point.x].Equals(new Gray(255)))
{
top_normal_line.Flip();
}
}
else
{
top_normal_line.Flip();
}
top_normal_line.UpdateEnd(new Vector2(500, 500));
top_normal_line.UpdateEnd(new Vector2(0, 0));
if (debug)
{
Image <Rgb, byte> cube_outline = this.body_img.Copy().Convert <Rgb, byte>();
cube_outline.Draw(new CircleF(new PointF(corner_points[i_corner[0]].x, corner_points[i_corner[0]].y), 10.0f), new Rgb(255, 0, 0), 1);
cube_outline.Draw(new CircleF(new PointF(corner_points[i_corner[1]].x, corner_points[i_corner[1]].y), 10.0f), new Rgb(255, 0, 0), 1);
cube_outline.Draw(new CircleF(new PointF(corner_points[0].x, corner_points[0].y), 8), new Rgb(0, 0, 255), 1);
cube_outline.Draw(new CircleF(new PointF(corner_points[1].x, corner_points[1].y), 8), new Rgb(0, 0, 255), 1);
cube_outline.Draw(new CircleF(new PointF(corner_points[2].x, corner_points[2].y), 8), new Rgb(0, 0, 255), 1);
cube_outline.Draw(new CircleF(new PointF(corner_points[3].x, corner_points[3].y), 8), new Rgb(0, 0, 255), 1);
cube_outline.Draw(body_lines[line0].ToLineSegment2D(), new Rgb(0, 255, 0), 3);
cube_outline.Draw(body_lines[line1].ToLineSegment2D(), new Rgb(0, 255, 0), 3);
cube_outline.Draw(body_line0.ToLineSegment2D(), new Rgb(0, 255, 255), 3);
cube_outline.Draw(body_line1.ToLineSegment2D(), new Rgb(0, 0, 255), 3);
cube_outline.Save("cube_outline.png");
Image <Gray, byte> approx_top = this.body_img.Copy();
foreach (Vector2 v in top_normal_line.SamplePoints())
{
approx_top.Draw(new CircleF(new PointF(v.x, v.y), 2.0f), new Gray(0), 1);
}
approx_top.Save("approx.png");
}
return(top_normal_line);
}
