请给出从深度图计算表面法向量的python代码

import numpy as np

def surface_normals(depth_map, fx, fy):
# Compute gradient using central differences
dzdx = np.gradient(depth_map, axis=1)
dzdy = np.gradient(depth_map, axis=0)

# Normalize gradient vectors
norm = np.sqrt(dzdx**2 + dzdy**2 + 1)
nx = -dzdx / norm
ny = -dzdy / norm
nz = np.ones_like(depth_map) / norm

# Convert to world coordinates
x = np.arange(depth_map.shape[1])
y = np.arange(depth_map.shape[0])
x, y = np.meshgrid(x, y)
x = (x - depth_map.shape[1] / 2) / fx
y = (y - depth_map.shape[0] / 2) / fy

nx = nx / fx
ny = ny / fy
nz = nz / (fx * fy)

# Rotate normals to align with camera coordinates
R = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
normals = np.stack([nx, ny, nz], axis=-1)
normals = np.einsum('ij,klj->kli', R, normals)

return normals