26 lines
962 B
Python
26 lines
962 B
Python
import trimesh
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import numpy as np
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import open3d as o3d
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import time
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# 1. 读取数据
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mesh_trimesh = trimesh.load("E:\point_distance\data\\40.stl")
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pcd_o3d = o3d.io.read_point_cloud("E:\point_distance\data\\40_noisy.ply")
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points = np.asarray(pcd_o3d.points)
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start_time = time.time()
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# ========== 1. 读取数据 ==========
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t0 = time.time()
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# 2. 使用 trimesh 计算每个点到 Mesh 的最近距离
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# trimesh 的 nearest 方法非常高效且精确
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closest_points, distances, triangle_ids = mesh_trimesh.nearest.on_surface(points)
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t1=time.time()
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# distances 即为所求的距离数组
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print(f"平均距离: {np.mean(distances)}")
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print(f"最大距离: {np.max(distances)}")
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print(f" 距离计算: {t1 - t0:.4f} 秒")
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# 如果需要将结果存回 Open3D 点云进行可视化
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dists_o3d = o3d.utility.DoubleVector(distances.tolist())
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# 注意：Open3D 点云对象本身不直接存储标量距离字段用于内置可视化着色
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