first commit

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