import os
import shutil
import time
import random
import matplotlib.pyplot as plt
import open3d as o3d
import numpy as np



# ply_read_path="/data/datasets_20t/type_setting_test_data/print_bounds_compact_data/88884_253283_P65951_6cm_x1=7.811+11.043+25.699.ply"
# # 读取点云
# pcd = o3d.io.read_point_cloud(ply_read_path)
#
# # 获取点云的点数据
# points = np.asarray(pcd.points)
#
# # 计算质心
# centroid = np.mean(points, axis=0)
#
# # 计算 Y 轴最小值
# min_y_value = np.min(points[:, 1])  # Y 轴最小值
# max_y_value = np.max(points[:, 1])
#
# # 计算 X 轴最小值
# min_x_value = np.min(points[:, 0])  # X 轴最小值
#
# print(f'min_x_value{min_x_value}')
# min_x_value -385.08287729332403
#
ply_read_path="/data/datasets_20t/type_setting_test_data/print_bounds_compact_data/456450_260316_P65976_2.66cm_x1=21.778+22.904+26.333.ply"
# 读取点云
pcd = o3d.io.read_point_cloud(ply_read_path)

# 获取点云的点数据
points = np.asarray(pcd.points)

# 计算质心
centroid = np.mean(points, axis=0)

# 计算 Y 轴最小值
min_y_value = np.min(points[:, 1])  # Y 轴最小值
max_y_value = np.max(points[:, 1])

# 计算 X 轴最小值
min_x_value = np.min(points[:, 0])  # X 轴最小值

print(f'min_x_value{min_x_value}')
# min_x_value -385.08287729332403
print(f'min_y_value{min_y_value}')

# -339