117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
import numpy as np
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import pymeshlab as pml
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def poisson_mesh_reconstruction(points, normals=None):
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# points/normals: [N, 3] np.ndarray
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import open3d as o3d
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pcd = o3d.geometry.PointCloud()
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pcd.points = o3d.utility.Vector3dVector(points)
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# outlier removal
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pcd, ind = pcd.remove_statistical_outlier(nb_neighbors=20, std_ratio=10)
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# normals
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if normals is None:
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pcd.estimate_normals()
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else:
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pcd.normals = o3d.utility.Vector3dVector(normals[ind])
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# visualize
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o3d.visualization.draw_geometries([pcd], point_show_normal=False)
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mesh, densities = o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(pcd, depth=9)
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vertices_to_remove = densities < np.quantile(densities, 0.1)
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mesh.remove_vertices_by_mask(vertices_to_remove)
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# visualize
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o3d.visualization.draw_geometries([mesh])
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vertices = np.asarray(mesh.vertices)
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triangles = np.asarray(mesh.triangles)
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print(f'[INFO] poisson mesh reconstruction: {points.shape} --> {vertices.shape} / {triangles.shape}')
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return vertices, triangles
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def decimate_mesh(verts, faces, target, backend='pymeshlab', remesh=False, optimalplacement=True):
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# optimalplacement: default is True, but for flat mesh must turn False to prevent spike artifect.
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_ori_vert_shape = verts.shape
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_ori_face_shape = faces.shape
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if backend == 'pyfqmr':
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import pyfqmr
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solver = pyfqmr.Simplify()
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solver.setMesh(verts, faces)
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solver.simplify_mesh(target_count=target, preserve_border=False, verbose=False)
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verts, faces, normals = solver.getMesh()
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else:
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m = pml.Mesh(verts, faces)
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ms = pml.MeshSet()
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ms.add_mesh(m, 'mesh') # will copy!
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# filters
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# ms.meshing_decimation_clustering(threshold=pml.Percentage(1))
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ms.meshing_decimation_quadric_edge_collapse(targetfacenum=int(target), optimalplacement=optimalplacement)
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if remesh:
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# ms.apply_coord_taubin_smoothing()
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ms.meshing_isotropic_explicit_remeshing(iterations=3, targetlen=pml.Percentage(1))
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# extract mesh
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m = ms.current_mesh()
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verts = m.vertex_matrix()
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faces = m.face_matrix()
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print(f'[INFO] mesh decimation: {_ori_vert_shape} --> {verts.shape}, {_ori_face_shape} --> {faces.shape}')
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return verts, faces
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def clean_mesh(verts, faces, v_pct=1, min_f=8, min_d=5, repair=True, remesh=True, remesh_size=0.01):
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# verts: [N, 3]
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# faces: [N, 3]
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_ori_vert_shape = verts.shape
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_ori_face_shape = faces.shape
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m = pml.Mesh(verts, faces)
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ms = pml.MeshSet()
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ms.add_mesh(m, 'mesh') # will copy!
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# filters
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ms.meshing_remove_unreferenced_vertices() # verts not refed by any faces
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if v_pct > 0:
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ms.meshing_merge_close_vertices(threshold=pml.Percentage(v_pct)) # 1/10000 of bounding box diagonal
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ms.meshing_remove_duplicate_faces() # faces defined by the same verts
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ms.meshing_remove_null_faces() # faces with area == 0
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if min_d > 0:
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ms.meshing_remove_connected_component_by_diameter(mincomponentdiag=pml.Percentage(min_d))
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if min_f > 0:
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ms.meshing_remove_connected_component_by_face_number(mincomponentsize=min_f)
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if repair:
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# ms.meshing_remove_t_vertices(method=0, threshold=40, repeat=True)
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ms.meshing_repair_non_manifold_edges(method=0)
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ms.meshing_repair_non_manifold_vertices(vertdispratio=0)
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if remesh:
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# ms.apply_coord_taubin_smoothing()
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ms.meshing_isotropic_explicit_remeshing(iterations=3, targetlen=pml.AbsoluteValue(remesh_size))
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# extract mesh
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m = ms.current_mesh()
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verts = m.vertex_matrix()
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faces = m.face_matrix()
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print(f'[INFO] mesh cleaning: {_ori_vert_shape} --> {verts.shape}, {_ori_face_shape} --> {faces.shape}')
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return verts, faces |