如何使用 numpy-stl 在 python 中保存多个网格

Question

我正在编写一段Python代码，它将接收灰度图像，对其进行缩放，并输出一个3D模型，每个像素的高度由灰度值确定。除了 3d 模型的输出之外，我的一切都正常。我使用 numpy-stl 根据从图像派生的值数组来创建它。使用 numpy-stl 库创建一个框，然后根据图像需要多次复制它。然后我将每一个翻译到与图像相对应的位置和高度。这一切都有效。当我尝试将其全部保存为一个 .stl 文件时，问题就出现了。我不知道如何将立方体的所有单独网格组合成一个。

这里只是处理 3d 数组创建的代码。我可以绘制创建的网格但不能保存它们。

from stl import mesh
import math
import numpy

test = [[1,2],[2,1]]

a = [[1,2,3,4],
        [5,6,7,8],
        [9,10,11,12],
        [13,14,15,16]]


# Create 6 faces of a cube, 2 triagles per face
data = numpy.zeros(12, dtype=mesh.Mesh.dtype)
#cube defined in stl format 
# Top of the cube
data['vectors'][0] = numpy.array([[0, 1, 1],
                                  [1, 0, 1],
                                  [0, 0, 1]])
data['vectors'][1] = numpy.array([[1, 0, 1],
                                  [0, 1, 1],
                                  [1, 1, 1]])
# Right face
data['vectors'][2] = numpy.array([[1, 0, 0],
                                  [1, 0, 1],
                                  [1, 1, 0]])
data['vectors'][3] = numpy.array([[1, 1, 1],
                                  [1, 0, 1],
                                  [1, 1, 0]])
# Left face
data['vectors'][4] = numpy.array([[0, 0, 0],
                                  [1, 0, 0],
                                  [1, 0, 1]])
data['vectors'][5] = numpy.array([[0, 0, 0],
                                  [0, 0, 1],
                                  [1, 0, 1]])
# Bottem of the cube
data['vectors'][6] = numpy.array([[0, 1, 0],
                                  [1, 0, 0],
                                  [0, 0, 0]])
data['vectors'][7] = numpy.array([[1, 0, 0],
                                  [0, 1, 0],
                                  [1, 1, 0]])
# Right back
data['vectors'][8] = numpy.array([[0, 0, 0],
                                  [0, 0, 1],
                                  [0, 1, 0]])
data['vectors'][9] = numpy.array([[0, 1, 1],
                                  [0, 0, 1],
                                  [0, 1, 0]])
# Left back 
data['vectors'][10] = numpy.array([[0, 1, 0],
                                  [1, 1, 0],
                                  [1, 1, 1]])
data['vectors'][11] = numpy.array([[0, 1, 0],
                                  [0, 1, 1],
                                  [1, 1, 1]])


# Generate 4 different meshes so we can rotate them later
meshes = [mesh.Mesh(data.copy()) for _ in range(16)]

#iterates through the array and translates cube in the x and y direction according 
#to position in array and in the z direction according to eh value stored in the array
def ArrayToSTL(array, STLmesh):
  y_count = 0
  x_count = 0
  count = 0
  for row in array:
    x_count = 0
    for item in row:
      meshes[count].x += x_count
      meshes[count].y += y_count
      meshes[count].z += item
      x_count +=1
      count += 1
    y_count += 1

ArrayToSTL(a, meshes)



# Optionally render the rotated cube faces
from matplotlib import pyplot
from mpl_toolkits import mplot3d

# Create a new plot
figure = pyplot.figure()
axes = mplot3d.Axes3D(figure)

# Render the cube faces
for m in meshes:
    axes.add_collection3d(mplot3d.art3d.Poly3DCollection(m.vectors))

# Auto scale to the mesh size
scale = numpy.concatenate([m.points for m in meshes]).flatten(-1)
axes.auto_scale_xyz(scale, scale, scale)

# Show the plot to the screen
pyplot.show()

Answer 1

这效果很好：

import numpy as np
import stl
from stl import mesh
import os

def combined_stl(meshes, save_path="./combined.stl"):
    combined = mesh.Mesh(np.concatenate([m.data for m in meshes]))
    combined.save(save_path, mode=stl.Mode.ASCII)

加载存储的 stl 文件并对它们进行网格划分，使用它。

direc = "path_of_directory"
paths = [os.path.join(direc, i) for i in os.listdir(direc)]
meshes = [mesh.Mesh.from_file(path) for path in paths]
combined_stl(meshes)