由于相机安装问题，导致点云数据两边翘起来，为了计算把翘起来的部分拉平整 

import time
import open3d as o3d;
import numpy as np;
import matplotlib.pyplot as plt
from scipy.signal import find_peaks
import pandas as pdOriginalPly = o3d.io.read_point_cloud("source/Glue4.ply") #对点云进行变形后校准
tic = time.time() # 将点云转换为NumPy数组
points = np.asarray(OriginalPly.points)# 创建一个新的数组来存放调整后的点
new_points =np.asarray(OriginalPly.points) # np.zeros_like(points)for x in np.unique(points[:, 0]): x_indices = np.where(points[:, 0] == x) min_z = np.min(points[x_indices, 2])new_points[x_indices, 2]   = new_points[x_indices, 2] +100-min_z # 将调整后的点重新赋值给点云对象toc = 1000 * (time.time() - tic)
print("点云校准耗时 {:.0f} [ms]".format(toc))
calibrationPly = o3d.geometry.PointCloud()
calibrationPly.points = o3d.utility.Vector3dVector(new_points) o3d.visualization.draw_geometries([ calibrationPly],window_name="calibrationPly 校准") 

校正前 红色是比较高的地方

拉平后的点云