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| import numpy as np | |
| import pymeshlab as pml | |
| def poisson_mesh_reconstruction(points, normals=None): | |
| # points/normals: [N, 3] np.ndarray | |
| import open3d as o3d | |
| pcd = o3d.geometry.PointCloud() | |
| pcd.points = o3d.utility.Vector3dVector(points) | |
| # outlier removal | |
| pcd, ind = pcd.remove_statistical_outlier(nb_neighbors=20, std_ratio=10) | |
| # normals | |
| if normals is None: | |
| pcd.estimate_normals() | |
| else: | |
| pcd.normals = o3d.utility.Vector3dVector(normals[ind]) | |
| # visualize | |
| o3d.visualization.draw_geometries([pcd], point_show_normal=False) | |
| mesh, densities = o3d.geometry.TriangleMesh.create_from_point_cloud_poisson( | |
| pcd, depth=9 | |
| ) | |
| vertices_to_remove = densities < np.quantile(densities, 0.1) | |
| mesh.remove_vertices_by_mask(vertices_to_remove) | |
| # visualize | |
| o3d.visualization.draw_geometries([mesh]) | |
| vertices = np.asarray(mesh.vertices) | |
| triangles = np.asarray(mesh.triangles) | |
| print( | |
| f"[INFO] poisson mesh reconstruction: {points.shape} --> {vertices.shape} / {triangles.shape}" | |
| ) | |
| return vertices, triangles | |
| def decimate_mesh( | |
| verts, faces, target, backend="pymeshlab", remesh=False, optimalplacement=True | |
| ): | |
| # optimalplacement: default is True, but for flat mesh must turn False to prevent spike artifect. | |
| _ori_vert_shape = verts.shape | |
| _ori_face_shape = faces.shape | |
| if backend == "pyfqmr": | |
| import pyfqmr | |
| solver = pyfqmr.Simplify() | |
| solver.setMesh(verts, faces) | |
| solver.simplify_mesh(target_count=target, preserve_border=False, verbose=False) | |
| verts, faces, normals = solver.getMesh() | |
| else: | |
| m = pml.Mesh(verts, faces) | |
| ms = pml.MeshSet() | |
| ms.add_mesh(m, "mesh") # will copy! | |
| # filters | |
| # ms.meshing_decimation_clustering(threshold=pml.Percentage(1)) | |
| ms.meshing_decimation_quadric_edge_collapse( | |
| targetfacenum=int(target), optimalplacement=optimalplacement | |
| ) | |
| if remesh: | |
| # ms.apply_coord_taubin_smoothing() | |
| ms.meshing_isotropic_explicit_remeshing( | |
| iterations=3, targetlen=pml.Percentage(1) | |
| ) | |
| # extract mesh | |
| m = ms.current_mesh() | |
| verts = m.vertex_matrix() | |
| faces = m.face_matrix() | |
| print( | |
| f"[INFO] mesh decimation: {_ori_vert_shape} --> {verts.shape}, {_ori_face_shape} --> {faces.shape}" | |
| ) | |
| return verts, faces | |
| def clean_mesh( | |
| verts, | |
| faces, | |
| v_pct=1, | |
| min_f=64, | |
| min_d=20, | |
| repair=True, | |
| remesh=True, | |
| remesh_size=0.01, | |
| ): | |
| # verts: [N, 3] | |
| # faces: [N, 3] | |
| _ori_vert_shape = verts.shape | |
| _ori_face_shape = faces.shape | |
| m = pml.Mesh(verts, faces) | |
| ms = pml.MeshSet() | |
| ms.add_mesh(m, "mesh") # will copy! | |
| # filters | |
| ms.meshing_remove_unreferenced_vertices() # verts not refed by any faces | |
| if v_pct > 0: | |
| ms.meshing_merge_close_vertices( | |
| threshold=pml.Percentage(v_pct) | |
| ) # 1/10000 of bounding box diagonal | |
| ms.meshing_remove_duplicate_faces() # faces defined by the same verts | |
| ms.meshing_remove_null_faces() # faces with area == 0 | |
| if min_d > 0: | |
| ms.meshing_remove_connected_component_by_diameter( | |
| mincomponentdiag=pml.Percentage(min_d) | |
| ) | |
| if min_f > 0: | |
| ms.meshing_remove_connected_component_by_face_number(mincomponentsize=min_f) | |
| if repair: | |
| # ms.meshing_remove_t_vertices(method=0, threshold=40, repeat=True) | |
| ms.meshing_repair_non_manifold_edges(method=0) | |
| ms.meshing_repair_non_manifold_vertices(vertdispratio=0) | |
| if remesh: | |
| # ms.apply_coord_taubin_smoothing() | |
| ms.meshing_isotropic_explicit_remeshing( | |
| iterations=3, targetlen=pml.AbsoluteValue(remesh_size) | |
| ) | |
| # extract mesh | |
| m = ms.current_mesh() | |
| verts = m.vertex_matrix() | |
| faces = m.face_matrix() | |
| print( | |
| f"[INFO] mesh cleaning: {_ori_vert_shape} --> {verts.shape}, {_ori_face_shape} --> {faces.shape}" | |
| ) | |
| return verts, faces | |