直接从 numpy 数据创建搅拌机网格？

Question

是否可以直接从高效的 numpy 数组创建 Blender 网格，而无需通过（缓慢且浪费空间的）POD python 数据类型？这是一个说明我的意思的脚本。我需要在我的 numpy 数据上调用 .tolist() 以使脚本正常工作。还有其他更高效的 API 吗？

# Create a mesh from numpy arrays. Can you do this without tolist()?
import bpy
import numpy as np

verts = np.array([
  (1, 1, 1),
  (-1, 1, -1),
  (-1, -1, 1),
  (1, -1, -1),
], dtype=np.float32)

faces = np.array([[0, 1, 2], [0, 2, 3], [0, 3, 1], [2, 1, 3]],
                 dtype=int)

mesh = bpy.data.meshes.new('TetraMesh')   
obj = bpy.data.objects.new('Tetra', mesh) 

# Must call tolist() to pass to from_pydata()!
mesh.from_pydata(verts.tolist(),[],faces.tolist())   
mesh.update(calc_edges=True)              # Update mesh with new data
bpy.context.collection.objects.link(obj)  # Link to scene

Answer 1

这个使用 foreach_set 对我有用。 您不必将 numpy 数组转换为列表。 我评论了每一行，应该清楚它是如何工作的。

import bpy
import numpy

# the numpy array must be in this form
vertices = numpy.array([
                        1, 1, 1,       # vertex 0
                        -1, 1, -1,     # vertex 1
                        -1, -1, 1,     # vertex 2
                        1, -1, -1      # vertex 3
                        ], dtype=numpy.float32)

# vertices for each polygon
vertex_index = numpy.array([
                            0, 1, 2,   #  first polygon starting at 0
                            0, 2, 3,   # second polygon starting at 3
                            0, 3, 1,   #  third polygon starting at 6
                            2, 1, 3    #  forth polygon starting at 9
                            ], dtype=numpy.int32)


# every polygon start at a specific index in vertex_index array
loop_start = numpy.array([
                          0, # polygon start at 0 --> 0, 1, 2
                          3, # polygon start at 3 --> 0, 2, 3
                          6, # polygon start at 6 --> 0, 3, 1
                          9  # polygon start at 9 --> 2, 1, 3
                          ], dtype=numpy.int32)
                          
# lenght of the loop
num_loops = loop_start.shape[0]


# Length of each polygon in number of vertices
loop_total = numpy.array([3,3,3,3], dtype=numpy.int32)


# Create mesh object based on the arrays above
mesh = bpy.data.meshes.new(name='created mesh')

# Number of vertices in vertices array (12 // 3)
num_vertices = vertices.shape[0] // 3

# add the amount of vertices, in this case 4.
mesh.vertices.add(num_vertices)

# use the vertices numpy array
mesh.vertices.foreach_set("co", vertices)

# total indexes in vertex_index
num_vertex_indices = vertex_index.shape[0]

# add the amount of the vertex_index array, in this case 12
mesh.loops.add(num_vertex_indices)

# set the vertx_index
mesh.loops.foreach_set("vertex_index", vertex_index)

# add the length of loop_start array
mesh.polygons.add(num_loops)

# generate the polygons
mesh.polygons.foreach_set("loop_start", loop_start)
mesh.polygons.foreach_set("loop_total", loop_total)

# validate your mesh
mesh.update()
mesh.validate()

# create the object with the mesh just created
obj = bpy.data.objects.new('created object', mesh)

# add the Oject to the scene
scene = bpy.context.scene
scene.collection.objects.link(obj)

如果你想了解更多，还有另一个更一致的例子here

Answer 2

Blender 最近在 master 分支中修复了这个问题 https://developer.blender.org/rBacf1374495c19d7b600ad12f12a01d6e8dfe7900

当前的解决方法是使用覆盖 __bool__ 方法的类查看数组，这样当 Blender 检查数组的布尔值时，它实际上会执行 Blender 开发人员打算做的事情（检查数组的长度是否为 > 0)

class ndarray_pydata(np.ndarray):
    def __bool__(self) -> bool:
        return len(self) > 0

edges = edges_np.view(ndarray_pydata)
faces = faces_np.view(ndarray_pydata)
mesh.from_pydata(vertices, edges, faces)

完整的工作示例： https://gist.github.com/iyadahmed/7c7c0fae03c40bd87e75dc7059e35377