您好，請問這張圖上的點雲可以進行Delaunay三角化嗎？
def boundary_extract(points, err=10e-3): pts = np.copy(points) tree = KDTree(pts, leaf_size=2) # adapt_R = adaptive_alpha(tree, 21) tri = Delaunay(pts) #在這一步報錯 s = tri.simplices N = s.shape[0] i = 0 edges = [] centers = [] while i <= N - 1: if s[i, 0] == -1: i = i + 1 continue p3 = s[i] e1 = np.array([points[p3[0], :], points[p3[1], :]]) e2 = np.array([points[p3[1], :], points[p3[2], :]]) e3 = np.array([points[p3[0], :], points[p3[2], :]]) e = [e1, e2, e3] for j in range(3): flag, center = edge_check_valid(e[j], tree, adapt_R[i], err) if flag: edges.append(e[j]) centers.append(center) nb = tri.neighbors[i] nb_valid = nb[nb != -1] # nb_valid_num = nb_valid.shape[0] # s[nb_valid] = -1 i = i + 1 return edges, centersTraceback (most recent call last): File "D:/pythonProjectForOpen3D/src/basic/area/AlphaShape.py", line 149, in <module> edges, centers = boundary_extract(final_pointCloud_array, err=10e-5) File "D:/pythonProjectForOpen3D/src/basic/area/AlphaShape.py", line 66, in boundary_extract tri = Delaunay(pts) File "qhull.pyx", line 1840, in scipy.spatial.qhull.Delaunay.__init__ File "qhull.pyx", line 356, in scipy.spatial.qhull._Qhull.__init__scipy.spatial.qhull.QhullError: QH6154 Qhull precision error: Initial simplex is flat (facet 1 is coplanar with the interior point)While executing: | qhull d Qz Qt Qc Qbb Q12Options selected for Qhull 2019.1.r 2019/06/21: run-id 1401204984 delaunay Qz-infinity-point Qtriangulate Qcoplanar-keep Qbbound-last Q12-allow-wide _pre-merge _zero-centrum Qinterior-keep Pgood _max-width 40 Error-roundoff 4e-14 _one-merge 3.6e-13 Visible-distance 2.4e-13 U-max-coplanar 2.4e-13 Width-outside 4.8e-13 _wide-facet 1.4e-12 _maxoutside 4.8e-13precision problems (corrected unless 'Q0' or an error) 142 zero divisors during gaussian eliminationThe input to qhull appears to be less than 4 dimensional, or acomputation has overflowed.Qhull could not construct a clearly convex simplex from points:- p0(v5): 19 4.5 0 2.2- p36(v4): 0.095 20 0 3- p110(v3): -0.033 -20 0 3.1- p140(v2): 20 -0.14 0 3- p78(v1): -20 0.77 0 1.7The center point is coplanar with a facet, or a vertex is coplanarwith a neighboring facet. The maximum round off error forcomputing distances is 4e-14. The center point, facets and distancesto the center point are as follows:center point 3.912 1.025 0 2.595facet p36 p110 p140 p78 distance= 0facet p0 p110 p140 p78 distance= 0facet p0 p36 p140 p78 distance= 0facet p0 p36 p110 p78 distance= 0facet p0 p36 p110 p140 distance= 0These points either have a maximum or minimum x-coordinate, orthey maximize the determinant for k coordinates. Trial pointsare first selected from points that maximize a coordinate.The min and max coordinates for each dimension are: 0: -19.87 19.97 difference= 39.84 1: -19.97 19.97 difference= 39.94 2: 0 0 difference= 0 3: 0 19.97 difference= 19.97If the input should be full dimensional, you have several options thatmay determine an initial simplex: - use 'QJ' to joggle the input and make it full dimensional - use 'QbB' to scale the points to the unit cube - use 'QR0' to randomly rotate the input for different maximum points - use 'Qs' to search all points for the initial simplex - use 'En' to specify a maximum roundoff error less than 4e-14. - trace execution with 'T3' to see the determinant for each point.If the input is lower dimensional: - use 'QJ' to joggle the input and make it full dimensional - use 'Qbk:0Bk:0' to delete coordinate k from the input. You should pick the coordinate with the least range. The hull will have the correct topology. - determine the flat containing the points, rotate the points into a coordinate plane, and delete the other coordinates. - add one or more points to make the input full dimensional.Process finished with exit code 1目前還沒找到解決辦法
希望可以找到報錯的原因並解決問題
