点云测地线fastmarching代码
时间: 2023-07-02 07:17:40 浏览: 42
以下是使用Fast Marching方法计算点云的测地线的示例代码:
```python
import numpy as np
import open3d as o3d
from scipy import sparse
from scipy.sparse import linalg
def get_adjacency_matrix(points, knn=10):
"""
构建点云的knn邻接矩阵
"""
pcd_tree = o3d.geometry.KDTreeFlann(points)
dists, neighs = pcd_tree.search_knn_vector_3d(points, knn)
n = len(points)
W = sparse.lil_matrix((n, n))
for i in range(n):
for j in neighs[i]:
if i != j:
W[i, j] = 1 / (1 + dists[i, j])
return W
def get_geodesic_distance(W, source):
"""
使用Fast Marching方法计算点云的测地线距离
"""
n = W.shape[0]
D = np.zeros(n)
mask = np.zeros(n)
mask[source] = 1
D[mask == 1] = 1
while len(np.where(mask == 0)[0]) > 0:
idx = np.where(mask == 1)[0]
for i in idx:
j = np.where(W[i, :] > 0)[1]
for k in j:
if mask[k] == 0:
D[k] = D[i] + W[i, k]
mask[k] = 1
if len(idx) == 0:
break
return D
if __name__ == "__main__":
# 读取点云数据
pcd = o3d.io.read_point_cloud("input.pcd")
points = np.asarray(pcd.points)
# 构建邻接矩阵
W = get_adjacency_matrix(points)
# 计算测地线距离
source = 0
D = get_geodesic_distance(W, source)
# 将测地线距离作为点云的颜色
pcd.colors = o3d.utility.Vector3dVector(np.zeros((len(points), 3)))
pcd.colors[:, 0] = (D - np.min(D)) / (np.max(D) - np.min(D))
o3d.visualization.draw_geometries([pcd])
```
这个示例代码使用Open3D库读取点云数据,并使用KD树和knn算法构建点云的邻接矩阵。然后使用Fast Marching方法计算点云的测地线距离,并将测地线距离作为点云的颜色进行可视化。