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我正在尝试为两个参数函数（点数据云）构建网格，并使用 Python 将其保存为 .ply 文件。

输入：3D 空间(x,y,z)中的数百万个数据点， 其中z可以视为数学函数z=f(x,y)的值

  1. 如何构建表示该点云的 3D 绘图表面的网格？
  2. 并将其导出为 3D 模型？

所需输出：包含网格的.PLY文件。

对于第 2 步，我有以下功能：

def savePoly(filename, arrayOfXYZ):
    xyz = np.array(arrayOfXYZ)
    x_points = xyz[:, 0]
    y_points = xyz[:, 1]
    z_points = xyz[:, 2]
    # Write header of .ply file
    fid = open(filename, 'wb')
    fid.write(bytes('ply\n', 'utf-8'))
    fid.write(bytes('format binary_little_endian 1.0\n', 'utf-8'))
    fid.write(bytes('element vertex %d\n' % x_points.shape[0], 'utf-8'))
    fid.write(bytes('property float x\n', 'utf-8'))
    fid.write(bytes('property float y\n', 'utf-8'))
    fid.write(bytes('property float z\n', 'utf-8'))
    fid.write(bytes('property uchar red\n', 'utf-8'))
    fid.write(bytes('property uchar green\n', 'utf-8'))
    fid.write(bytes('property uchar blue\n', 'utf-8'))
    fid.write(bytes('end_header\n', 'utf-8'))

    rgb_points = np.ones(x_points.shape).astype(np.uint8) * 255

    # Write 3D points to .ply file
    for i in range(x_points.shape[0]):

        fid.write(bytearray(struct.pack("fffccc",
                                        x_points[i],
                                        y_points[i],
                                        z_points[i],
                                        rgb_points[i].tobytes(),
                                        rgb_points[i].tobytes(),
                                        rgb_points[i].tobytes()
                                        )))
    fid.close()

    print(fid)

但是那个只保存顶点，没有表面。

以下代码将三角形保存到 .ply 但我不确定tris如何首先构建三角形：

"""
plyfun
@author:wronk
Write surface to a .ply (Stanford 3D mesh file) in a way that preserves
vertex order in the MNE sense. Extendable for colors or other vertex/face properties.
.ply format: https://en.wikipedia.org/wiki/PLY_(file_format)
"""

import mne
import numpy as np
from os import path as op
import os
from os import environ


def write_surf2ply(rr, tris, save_path):
    out_file = open(save_path, 'w')

    head_strs = ['ply\n', 'format ascii 1.0\n']
    ele_1 = ['element vertex ' + str(len(rr)) + '\n',
             'property float x\n',
             'property float y\n',
             'property float z\n']
    ele_2 = ['element face ' + str(len(tris)) + '\n',
             'property list uchar int vertex_index\n']
    tail_strs = ['end_header\n']

    # Write Header
    out_file.writelines(head_strs)
    out_file.writelines(ele_1)
    out_file.writelines(ele_2)
    out_file.writelines(tail_strs)

    ##############
    # Write output
    ##############
    # First, write vertex positions
    for vert in rr:
        out_file.write(str(vert[0]) + ' ')
        out_file.write(str(vert[1]) + ' ')
        out_file.write(str(vert[2]) + '\n')

    # Second, write faces using vertex indices
    for face in tris:
        out_file.write(str(3) + ' ')
        out_file.write(str(face[0]) + ' ')
        out_file.write(str(face[1]) + ' ')
        out_file.write(str(face[2]) + '\n')

    out_file.close()


if __name__ == '__main__':
    struct_dir = op.join(environ['SUBJECTS_DIR'])
    subject = 'AKCLEE_139'

    surf_fname = op.join(struct_dir, subject, 'surf', 'lh.pial')
    save_path = op.join('/media/Toshiba/Blender/Brains', subject,
                        'lh.pial_reindex.ply')

    rr, tris = mne.read_surface(surf_fname)
    write_surf2ply(rr, tris, save_path)

对于第 1 步：

以下文章生成网格，但 (a) 它是一个通用的点数据云，而 z=f(x,y) 在这里就足够了，(b) 它假设输入中有一个法线数组：https：/ /towardsdatascience.com/5-step-guide-to-generate-3d-meshes-from-point-clouds-with-python-36bad397d8ba仍然需要构建。

总而言之：

有没有一种简单的方法可以使用 Python 为大量点云数据构建网格，其中 z 坐标是 (x,y) 的函数，并将此网格导出到 .ply 文件？

4

1 回答 1

0

Solution:

  1. Imports
import numpy as np
import scipy.spatial
import pandas as pd
  1. Load csv file with point cloud data:
df = pd.read_csv("data.csv")

print(df.columns)

x = df['column 0']
y = df['column 1']
z = df['column z values']
  1. If necessary normalise the data to make sure the mesh is properly located in the axis origin:
x0 = x[0]
y0 = y[0]
z0 = z[0]
pointslist = []
for i in range(len(x)):
    xi = (x[i] - x0) / 100
    yi = (y[i] - y0) / 4
    zi = (z[i] - z0) / 8
    pointslist.append([xi, yi, zi]) # array of triplets 
xyz = np.array(pointslist)
  1. Since z = f(x,y) we no need to use general-purpose triangulation, and can use the Delaunay-algo for 2D-data point sets.
# xyz = np.random.random((12, 3))  # arbitrary 3D data set
# xyz = np.array([[0, 0,1], [0, 1,1], [1, 0.5,0], [1, 0,0]]) # smaller data set for testing 
# print(data)

mesh = scipy.spatial.Delaunay(xyz[:, :2])  # take the first two dimensions

# print(mesh.points)
# print(mesh.convex_hull)
# print(mesh.vertex_to_simplex)
#
# x = xyz[:, 0]
# y = xyz[:, 1]
# z = xyz[:, 2]
  1. Mesh is ready, triangles are stored as vertex indices in the mesh.simplices. Save all to .PLY-file using the following function:
writeSurface2PLY(xyz, mesh.simplices, "output.ply")

def writeSurface2PLY(vertices, meshanglesAsVertexIndices, save_path):
    out_file = open(save_path, 'w')

    head_strs = ['ply\n', 'format ascii 1.0\n']
    ele_1 = ['element vertex ' + str(len(vertices)) + '\n',
             'property float x\n',
             'property float y\n',
             'property float z\n']
    ele_2 = ['element face ' + str(len(meshanglesAsVertexIndices)) + '\n',
             'property list uchar int vertex_index\n']
    tail_strs = ['end_header\n']

    # Write Header
    out_file.writelines(head_strs)
    out_file.writelines(ele_1)
    out_file.writelines(ele_2)
    out_file.writelines(tail_strs)

    ##############
    # Write output
    ##############
    # First, write vertex positions
    for vert in vertices:
        out_file.write(str(vert[0]) + ' ')
        out_file.write(str(vert[1]) + ' ')
        out_file.write(str(vert[2]) + '\n')

    # Second, write faces using vertex indices
    for face in meshanglesAsVertexIndices:
        out_file.write(str(3) + ' ')
        out_file.write(str(face[0]) + ' ')
        out_file.write(str(face[1]) + ' ')
        out_file.write(str(face[2]) + '\n')

    out_file.close()
于 2020-11-11T10:24:56.533 回答