59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
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import mesh2sdf.core
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import numpy as np
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import skimage.measure
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import trimesh
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def normalize_vertices(vertices, scale=0.9):
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bbmin, bbmax = vertices.min(0), vertices.max(0)
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center = (bbmin + bbmax) * 0.5
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scale = 2.0 * scale / (bbmax - bbmin).max()
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vertices = (vertices - center) * scale
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return vertices, center, scale
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def export_to_watertight(normalized_mesh, octree_depth: int = 7):
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"""
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Convert the non-watertight mesh to watertight.
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Args:
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input_path (str): normalized path
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octree_depth (int):
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Returns:
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mesh(trimesh.Trimesh): watertight mesh
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"""
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size = 2 ** octree_depth
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level = 2 / size
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scaled_vertices, to_orig_center, to_orig_scale = normalize_vertices(normalized_mesh.vertices)
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sdf = mesh2sdf.core.compute(scaled_vertices, normalized_mesh.faces, size=size)
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vertices, faces, normals, _ = skimage.measure.marching_cubes(np.abs(sdf), level)
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# watertight mesh
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vertices = vertices / size * 2 - 1 # -1 to 1
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vertices = vertices / to_orig_scale + to_orig_center
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# vertices = vertices / to_orig_scale + to_orig_center
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mesh = trimesh.Trimesh(vertices, faces, normals=normals)
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return mesh
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def process_mesh_to_pc(mesh_list, marching_cubes = False, sample_num = 4096):
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# mesh_list : list of trimesh
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pc_normal_list = []
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return_mesh_list = []
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for mesh in mesh_list:
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if marching_cubes:
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mesh = export_to_watertight(mesh)
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print("MC over!")
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return_mesh_list.append(mesh)
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points, face_idx = mesh.sample(sample_num, return_index=True)
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normals = mesh.face_normals[face_idx]
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pc_normal = np.concatenate([points, normals], axis=-1, dtype=np.float16)
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pc_normal_list.append(pc_normal)
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print("process mesh success")
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return pc_normal_list, return_mesh_list
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