-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path随机布局.py
175 lines (155 loc) · 7.75 KB
/
随机布局.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
import random
from mathutils import Vector
import bpy
ele_obj = ['product', 'product.001', 'product.002']
floor_obj = ['物件37', '物件28']
max_iterations = 1000 # 最大循环
loop_iterations = 0 # 当前循环
random_count = len(ele_obj) # 定位立方体数量
floor = bpy.data.objects['floor'] # 地板
floor_location = floor.location # 地板位置
floor_dimensions = floor.dimensions # 地板尺寸
# 地板4个顶点 中心点在中心
floor_vertices = [floor.matrix_world @ i.co for i in floor.data.vertices]
direction = 'z' # 在地板得哪个面放置物体
random_x_l_range = [floor_vertices[0][0], floor_vertices[1][0]] # x轴取值
random_y_l_range = [floor_vertices[0][1], floor_vertices[2][1]] # y轴取值
all_locations = [] # 所有定位块
all_obj = []
def get_pd_box(obj, pd_box_list):
"""获取cube或者组合对象得边框包围"""
if obj.type == 'MESH':
pd_box_list.extend([obj.matrix_world @ Vector(pdBvert) for pdBvert in obj.bound_box])
for i in obj.children:
pd_box_list = get_pd_box(i, pd_box_list)
return pd_box_list
def get_box_list(pd):
pd_box_list = []
get_pd_box(pd, pd_box_list)
max_x = max([v[0] for v in pd_box_list])
min_x = min([v[0] for v in pd_box_list])
max_y = max([v[1] for v in pd_box_list])
min_y = min([v[1] for v in pd_box_list])
max_z = max([v[2] for v in pd_box_list])
min_z = min([v[2] for v in pd_box_list])
pd_box = []
pd_box.append(Vector((min_x, min_y, min_z)))
pd_box.append(Vector((min_x, min_y, max_z)))
pd_box.append(Vector((min_x, max_y, max_z)))
pd_box.append(Vector((min_x, max_y, min_z)))
pd_box.append(Vector((max_x, min_y, min_z)))
pd_box.append(Vector((max_x, min_y, max_z)))
pd_box.append(Vector((max_x, max_y, max_z)))
pd_box.append(Vector((max_x, max_y, min_z)))
# 产品尺寸
pd_d_x = abs(pd_box[0][0] - pd_box[4][0])
pd_d_y = abs(pd_box[0][1] - pd_box[2][1])
pd_d_z = abs(pd_box[0][2] - pd_box[1][2])
dimensions = [pd_d_x, pd_d_y, pd_d_z]
return pd_box, dimensions
for i in ele_obj:
try:
pd = bpy.data.objects[i]
except:
continue
pd_box, dimensions = get_box_list(pd)
all_obj.append({'name': pd, 'pd_box': pd_box, 'dimensions': dimensions})
def overlap_interval(check_list):
"""校验区间重叠"""
# 排序
a_list = sorted(check_list, key=lambda l: l[0])
for i in range(0, len(a_list) - 1):
if a_list[i + 1][0] <= a_list[i][1]:
return True
return False
def is_intersect(all_locations, dimensions, location):
located_flag = False
obj_flag = False
for i in all_locations:
obj = bpy.data.objects[i]
obj_x_range = [obj.location.x - obj.dimensions.x, obj.location.x + obj.dimensions.x]
o_x_range = [location[0] - dimensions[0], location[0] + dimensions[0]]
check_x = overlap_interval([obj_x_range, o_x_range])
obj_y_range = [obj.location.y - obj.dimensions.y, obj.location.y + obj.dimensions.y]
o_y_range = [location[1] - dimensions[1], location[1] + dimensions[1]]
check_y = overlap_interval([obj_y_range, o_y_range])
# obj_z_range = [obj.location.z - obj.dimensions.z, obj.location.z + obj.dimensions.z]
# o_z_range = [location[2] - dimensions[2], location[2] + dimensions[2]]
# check_z = overlap_interval([obj_z_range, o_z_range])
if check_x or check_y:
located_flag = True
break
for i in floor_obj:
try:
pd = bpy.data.objects[i]
except:
continue
pd_box, dimensions = get_box_list(pd)
obj_x_range = [pd_box[0][0], pd_box[4][0]]
o_x_range = [location[0] - dimensions[0], location[0] + dimensions[0]]
check_x = overlap_interval([obj_x_range, o_x_range])
obj_y_range = [pd_box[0][1], pd_box[2][1]]
o_y_range = [location[1] - dimensions[1], location[1] + dimensions[1]]
check_y = overlap_interval([obj_y_range, o_y_range])
if check_x or check_y:
obj_flag = True
break
return located_flag or obj_flag
def test(pd_box, pd, lp, obj_dimensions):
origin_pd_x_range = [pd_box[0][0], pd_box[4][0]] # 组合对象外包围框 x轴范围
origin_pd_y_range = [pd_box[0][1], pd_box[2][1]] # 组合对象外包围框 y轴范围
origin_pd_z_range = [pd_box[0][2], pd_box[1][2]] # 组合对象外包围框 z轴范围
centre_pd_x = round((origin_pd_x_range[0] + origin_pd_x_range[1]) / 2, 4) # 组合对象外包围框 x轴中心
centre_pd_y = round((origin_pd_y_range[0] + origin_pd_y_range[1]) / 2, 4) # 组合对象外包围框 y轴中心
centre_pd_z = round((origin_pd_z_range[0] + origin_pd_z_range[1]) / 2, 4) # 组合对象外包围框 z轴中心
deviation_pd_x = round((pd.location.x - centre_pd_x), 4) # x原点偏移量
deviation_pd_y = round((pd.location.y - centre_pd_y), 4) # y原点偏移量
deviation_pd_z = round((pd.location.z - centre_pd_z), 4) # z原点偏移量
lp_box = [lp.matrix_world @ Vector(lpBvert) for lpBvert in lp.bound_box] # pd 外边框 8个顶点得xyz全局坐标系
# 这儿会牵扯到 原点位置信息 导致计算位移不准确
pd.location.x = (lp_box[0][0] + lp_box[4][0]) / 2 - deviation_pd_x
pd.location.y = (lp_box[0][1] + lp_box[2][1]) / 2 - deviation_pd_y
# pd.location.z = lp_box[0][2] # 原点在底部
pd.location.z = lp_box[0][2] + obj_dimensions[2] / 2 - deviation_pd_z # 原点在 中心
def generate_located(all_locations):
global loop_iterations
# while len(all_locations) < random_count:
while len(all_locations) < random_count and loop_iterations < max_iterations:
data = all_obj[0]
pd = data['name']
obj_dimensions = data['dimensions']
pd_box = data['pd_box']
loop_iterations += 1
dimensions_x = round(random.uniform(obj_dimensions[0], obj_dimensions[0] + 0.5), 4) # 随机 立方体 x 尺寸
dimensions_y = round(random.uniform(obj_dimensions[1], obj_dimensions[1] + 0.5), 4) # 随机 立方体 y 尺寸
dimensions_z = round(random.uniform(obj_dimensions[2], obj_dimensions[2] + 0.5), 4) # 随机 立方体 z 尺寸
location_x = round(
random.uniform(random_x_l_range[0] + dimensions_x / 2, random_x_l_range[1] - dimensions_x / 2),
4)
location_y = round(
random.uniform(random_y_l_range[0] + dimensions_y / 2, random_y_l_range[1] - dimensions_y / 2),
4)
location_z = dimensions_z / 2 + floor_location[2]
dimensions = [dimensions_x, dimensions_y, dimensions_z]
location = [location_x, location_y, location_z]
flag = is_intersect(all_locations, dimensions, location)
if not flag:
name = 'located_{}'.format(len(all_locations))
try:
lp = bpy.data.objects[name]
lp.location = location
lp.dimensions = dimensions
bpy.context.view_layer.update()
except:
bpy.ops.mesh.primitive_cube_add(location=location, scale=(1, 1, 1))
lp = bpy.context.object
lp.name = name
lp.display_type = 'BOUNDS'
lp.dimensions = dimensions
all_locations.append(name)
test(pd_box, pd, lp, obj_dimensions)
all_obj.remove(data)
generate_located(all_locations)
# //TODO 模型z轴摆放设置原点位置问题，在底部得话，设置z轴为定位块下部顶点得z坐标， 在中心得话，设置定位块下部顶点得z坐标 + 模型得z轴寸尺得一半
# //TODO 地板可能因为其中一个定位块占据中间，而导致其他定位块放不进去, 可能有无限循环问题
# //TODO 地板可能本身已有模型，随机定位块，需要防止定位块和已有模型冲突