如何将 3D 点云 (.ply) 转换为网格（具有面和顶点）？

Question

我有一个包含 100 万个点的 3-D 点云文件，我需要将其转换为 trimesh 中的网格文件。这里的最终目标是获取一个点云并确定该点云是凸面还是凹面（trimesh 允许我在将云转换为网格后这样做）。我愿意接受其他图书馆来解决这个问题。

我已经尝试使用 scipy 进行 Delaunay 三角剖分，但似乎无法将我的点云转换为正确的格式，以便trimesh 可以读取它。

import open3d as o3d
import numpy as np
import trimesh
from scipy.spatial import Delaunay


pointcloud = o3d.io.read_triangle_mesh("pointcloud.ply")
points = np.array(pointcloud.points)
triangle_mesh = Delaunay(points)
#  How do i include triangle_mesh from Delaunay triangulation into processing the mesh file?
mesh = trimesh.load("pointcloud.ply")
print(trimesh.convex.is_convex(mesh))

错误

geometry::TriangleMesh appears to be a geometry::PointCloud (only contains vertices, but no triangles).
geometry::TriangleMesh with 1390073 points and 0 triangles.
expected = (faces.shape[0], faces.shape[1] * 2)
AttributeError: 'NoneType' object has no attribute 'shape'

Answer 1

Open3d 0.8.0.0 现在已经实现了滚球枢轴算法以从点云重建网格。

我使用以下方法解决了从点云生成网格的问题：

import open3d as o3d
import trimesh
import numpy as np

pcd = o3d.io.read_point_cloud("pointcloud.ply")
pcd.estimate_normals()

# estimate radius for rolling ball
distances = pcd.compute_nearest_neighbor_distance()
avg_dist = np.mean(distances)
radius = 1.5 * avg_dist   

mesh = o3d.geometry.TriangleMesh.create_from_point_cloud_ball_pivoting(
           pcd,
           o3d.utility.DoubleVector([radius, radius * 2]))

# create the triangular mesh with the vertices and faces from open3d
tri_mesh = trimesh.Trimesh(np.asarray(mesh.vertices), np.asarray(mesh.triangles),
                          vertex_normals=np.asarray(mesh.vertex_normals))

trimesh.convex.is_convex(tri_mesh)