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meshutils.py
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meshutils.py
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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=8, min_d=5, 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