import trimesh
import numpy as np
import open3d as o3d
import time
# 1. 读取数据
mesh_trimesh = trimesh.load("E:\point_distance\data\\40.stl")
pcd_o3d = o3d.io.read_point_cloud("E:\point_distance\data\\40_noisy.ply")
points = np.asarray(pcd_o3d.points)
start_time = time.time()

# ========== 1. 读取数据 ==========

t0 = time.time()
# 2. 使用 trimesh 计算每个点到 Mesh 的最近距离
# trimesh 的 nearest 方法非常高效且精确
closest_points, distances, triangle_ids = mesh_trimesh.nearest.on_surface(points)
t1=time.time()

# distances 即为所求的距离数组
print(f"平均距离: {np.mean(distances)}")
print(f"最大距离: {np.max(distances)}")
print(f"  距离计算:   {t1 - t0:.4f} 秒")
# 如果需要将结果存回 Open3D 点云进行可视化
dists_o3d = o3d.utility.DoubleVector(distances.tolist())
# 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