点云主曲率Python 代码
时间: 2023-11-19 22:06:59 浏览: 101
以下是使用Python计算点云主曲率的示例代码:
```python
import numpy as np
from sklearn.neighbors import KDTree
def compute_curvature(points, k=20):
"""
计算点云的主曲率
:param points: 点云数组,每行表示一个点的xyz坐标
:param k: 每个点的邻居数量
:return: 主曲率数组
"""
tree = KDTree(points)
N = points.shape[0]
curvature = np.zeros((N,))
for i in range(N):
idx = tree.query(points[i, :].reshape(1,-1), k=k, return_distance=False)[0]
neighbor_pts = points[idx, :]
neighbor_pts -= np.mean(neighbor_pts, axis=0)
cov = np.cov(neighbor_pts, rowvar=False)
evals, evecs = np.linalg.eig(cov)
curvature[i] = np.min(evals) / np.sum(evals)
return curvature
```
使用示例:
```python
import open3d as o3d
# 读取点云文件
pcd = o3d.io.read_point_cloud("point_cloud.ply")
# 获取点云数组
points = np.asarray(pcd.points)
# 计算主曲率
curvature = compute_curvature(points)
# 可视化
pcd.colors = o3d.utility.Vector3dVector(np.zeros_like(points))
pcd.colors[curvature > 0.1] = [1, 0, 0] # 根据曲率值设置颜色
o3d.visualization.draw_geometries([pcd])
```
其中,`k`参数表示每个点的邻居数量,可以根据具体情况进行调整。
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