PointCloudVolume/mission_stock_pile_triangularization_true_data.py

import open3d as o3d
import numpy as np
import math
from scipy.spatial import Delaunay
import math
from functools import reduce
import sys

# pcd = o3d.io.read_point_cloud("data/2box-SG-t-MnQ0zoEQIBX.ply")
# pcd = o3d.io.read_point_cloud("data/4box-1-SG-t-AsSRO3iA0XT.ply")
# pcd = o3d.io.read_point_cloud("data/4box-2-SG-t-cp3kSewxMKi.ply")
pcd = o3d.io.read_point_cloud("data/4box-3-SG-t-kuuv0moEP0C.ply")
print(pcd)

axes = o3d.geometry.TriangleMesh.create_coordinate_frame()

# 找出地面所在平面
plane_model, inliers = pcd.segment_plane(distance_threshold=0.01,
                                         ransac_n=3,
                                         num_iterations=10000)


# # 把地面上的点和其他点分开
# [a, b, c, d] = plane_model
# plane_pcd = pcd.select_by_index(inliers)
# plane_pcd.paint_uniform_color([1.0, 0, 0])
# stockpile_pcd = pcd.select_by_index(inliers, invert=True)
# stockpile_pcd.paint_uniform_color([0, 0, 1.0])
# o3d.visualization.draw_geometries([plane_pcd, stockpile_pcd, axes])

# 移动到原点
plane_pcd = plane_pcd.translate((0,0,d/c))
stockpile_pcd = stockpile_pcd.translate((0,0,d/c))

# 旋转至与坐标轴对齐
cos_theta = c / math.sqrt(a**2 + b**2 + c**2)
sin_theta = math.sqrt((a**2+b**2)/(a**2 + b**2 + c**2))
u_1 = b / math.sqrt(a**2 + b**2 )
u_2 = -a / math.sqrt(a**2 + b**2)
rotation_matrix = np.array([[cos_theta + u_1**2 * (1-cos_theta), u_1*u_2*(1-cos_theta), u_2*sin_theta],
                            [u_1*u_2*(1-cos_theta), cos_theta + u_2**2*(1- cos_theta), -u_1*sin_theta],
                            [-u_2*sin_theta, u_1*sin_theta, cos_theta]])
plane_pcd.rotate(rotation_matrix)
stockpile_pcd.rotate(rotation_matrix)
# o3d.visualization.draw_geometries([plane_pcd, stockpile_pcd, axes])

# 去除噪点
cl, ind = stockpile_pcd.remove_statistical_outlier(nb_neighbors=30,
                                                    std_ratio=2.0)
stockpile_pcd = stockpile_pcd.select_by_index(ind)
# o3d.visualization.draw_geometries([stockpile_pcd])

# # 降采样
# downpcd = stockpile_pcd.voxel_down_sample(voxel_size=0.05)
# print(downpcd)
downpcd = stockpile_pcd

# 三角剖分
xyz = np.asarray(downpcd.points)
xy_catalog = []
for point in xyz:
    xy_catalog.append([point[0], point[1]])
tri = Delaunay(np.array(xy_catalog))

surface = o3d.geometry.TriangleMesh()
surface.vertices = o3d.utility.Vector3dVector(xyz)
surface.triangles = o3d.utility.Vector3iVector(tri.simplices)
surface.paint_uniform_color([0, 0, 1.0])
# o3d.visualization.draw_geometries([surface], mesh_show_wireframe=True)

def get_triangles_vertices(triangles, vertices):
    triangles_vertices = []
    for triangle in triangles:
        new_triangles_vertices = [vertices[triangle[0]], vertices[triangle[1]], vertices[triangle[2]]]
        triangles_vertices.append(new_triangles_vertices)
    return np.array(triangles_vertices)

def volume_under_triangle(triangle):
    p1, p2, p3 = triangle
    x1, y1, z1 = p1
    x2, y2, z2 = p2
    x3, y3, z3 = p3
    return abs((z1+z2+z3)*(x1*y2-x2*y1+x2*y3-x3*y2+x3*y1-x1*y3)/6)

print('sdfjsfksldfj')
volume = reduce(lambda a, b:  a + volume_under_triangle(b), get_triangles_vertices(surface.triangles, surface.vertices), 0)
print(f"The volume of the stockpile is: {round(volume, 4)} m3")