feat: 算法升级、整车配准集成与性能分析文档

算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3
适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新
后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动
前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复
文档: 新增5份算法性能分析报告
This commit is contained in:
2026-06-25 08:22:20 +00:00
parent cec0766e67
commit 29f1d45d66
266 changed files with 1311475 additions and 2846 deletions

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import open3d as o3d
import numpy as np
from scipy.spatial import KDTree
from plyfile import PlyData
def chamfer_distance(pcd1, pcd2):
"""
计算两个点云之间的 CD 距离(Chamfer Distance)
Args:
pcd1: Open3D 点云对象1
pcd2: Open3D 点云对象2
Returns:
cd: Chamfer Distance 值
cd1: 点云1 到 点云2 的平均距离
cd2: 点云2 到 点云1 的平均距离
"""
# 获取点坐标
points1 = np.asarray(pcd1.points)
points2 = np.asarray(pcd2.points)
# 构建 KD-Tree 加速最近邻搜索
tree1 = KDTree(points1)
tree2 = KDTree(points2)
# 计算 points1 中每个点到 points2 的最近距离
dist1, _ = tree2.query(points1, k=1)
cd1 = np.mean(dist1 ** 2) # 平方距离的平均值
# 计算 points2 中每个点到 points1 的最近距离
dist2, _ = tree1.query(points2, k=1)
cd2 = np.mean(dist2 ** 2) # 平方距离的平均值
# 总 CD 距离(双向平均)
cd = cd1 + cd2
return cd, cd1, cd2
pcd = o3d.io.read_point_cloud("E:\point_distance\data\part_car_head.ply")
colors = np.tile([1, 0, 0], (len(pcd.points), 1))
pcd.colors = o3d.utility.Vector3dVector(colors)
# ply_data = PlyData.read(r"E:\point_distance\data\part_car_head.ply")
# colors=np.asarray(ply_data.colors)
# with open("E:\point_distance\data\part_car_head.ply", 'r',encoding="utf-8") as f:
# lines = f.readlines()
# for line in lines[:30]: # 打印头部
# print(line.strip())
# o3d.visualization.draw_geometries([pcd])
# points = np.asarray(pcd.points)
# colors = np.asarray(pcd.colors)
# normals = np.asarray(pcd.normals)
cl, ind = pcd.remove_statistical_outlier(nb_neighbors=20, std_ratio=50.0)
inlier_cloud = pcd.select_by_index(ind)
colors=np.tile([0,1,0],(len(inlier_cloud.points),1))
inlier_cloud.colors=o3d.utility.Vector3dVector(colors)
o3d.visualization.draw_geometries([inlier_cloud])
o3d.visualization.draw_geometries([pcd])
o3d.visualization.draw_geometries()
cd,cd1,cd2=chamfer_distance(pcd1=pcd,pcd2=inlier_cloud)
print(cd)