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import open3d as o3d
import numpy as np
import copy
import time
import argparse
from general import *
# ------------------------ 开始:对外接口,获取bbox数据 --------------------
"""
对外部提供的获取bbox数据的接口
compute_bbox_out
参数:
obj_path, 模型数据路径
返回:
total_matrix: 旋转矩阵, 16位浮点型, 例如, [[ 0.13644984 0.99064698 0. -49.71074343]
[ -0.99064698 0.13644984 0. -28.80249299]
[ 0. 0. 1. 3.26326203]
[ 0. 0. 0. 1. ]]
z_max : z最高点, 1位浮点型, 例如, 1.0
min_bound : bbox最低点, 3位浮点型, 例如, [-1.0, -1.0, 0.0]
max_bound : bbox最低点, 3位浮点型, 例如, [0.0, 0.0, 1.0]
ply_name : ply的名字, 字符串, 例如, 857420_268473_P85240_5cm_x1=9.41+49.997+49.997.ply
"""
def compute_bbox_out(mesh_obj):
return compute_bbox_ext(mesh_obj)
# -------------------------- 结束:对外接口,获取bbox数据 ----------------
# -------------------------- 开始:获取z值最低 --------------------------
def get_lowest_position_of_z_ext(mesh_obj):
total_matrix = np.eye(4)
voxel_size = 3
# print(f"obj_path={obj_path}, get_lowest_position_of_center voxel_size={voxel_size}")
start_time1 = time.time()
vertices = np.asarray(mesh_obj.vertices)
# 确保网格有顶点
if len(vertices) == 0:
# raise ValueError(f"Mesh has no vertices: {obj_path}")
print(f"Warning: Mesh has no vertices: {mesh_obj}")
return None
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(vertices)
# print("voxel_size",voxel_size,obj_path, len(pcd.points), len(mesh_obj.vertices))
# 对点云进行下采样(体素网格法)
#"""
pcd_downsampled = down_sample(pcd, voxel_size)
pcd_downsampled.paint_uniform_color([0, 0, 1])
if len(np.asarray(pcd_downsampled.points)) <= 0:
bbox = pcd.get_axis_aligned_bounding_box()
volume = bbox.volume()
# print(f"len(pcd.points)={len(pcd.points)}, volume={volume}")
# 处理体积为零的情况
if volume <= 0:
# 计算点云的实际范围
points = np.asarray(pcd.points)
if len(points) > 0:
min_bound = np.min(points, axis=0)
max_bound = np.max(points, axis=0)
extent = max_bound - min_bound
# 确保最小维度至少为0.01
min_dimension = max(0.01, np.min(extent))
volume = min_dimension ** 3
else:
volume = 1.0 # 最后的安全回退
print(f"Warning: Zero volume detected, using approximated volume {volume:.6f} for {obj_path}")
# 安全计算密度 - 防止除零错误
if len(pcd.points) > 0 and volume > 0:
original_density = len(pcd.points) / volume
voxel_size = max(0.01, min(10.0, 0.5 / (max(1e-6, original_density) ** 0.33)))
else:
# 当点数为0或体积为0时使用默认体素大小
voxel_size = 1.0 # 默认值
print(f"Recalculated voxel_size: {voxel_size} for {obj_path}")
pcd_downsampled = down_sample(pcd, voxel_size)
pcd_downsampled.paint_uniform_color([0, 0, 1])
original_num = len(pcd.points)
target_samples = 1000
num_samples = min(target_samples, original_num)
# print("get_lowest_position_of_center1 time", time.time()-start_time1)
start_time2 = time.time()
# 确保下采样后有点云
if len(np.asarray(pcd_downsampled.points)) == 0:
# 使用原始点云作为后备
pcd_downsampled = pcd
print(f"Warning: Using original point cloud for {obj_path} as downsampling produced no points")
points = np.asarray(pcd_downsampled.points)
# 初始化最小重心Y的值
max_z_of_mass_y = float('inf')
best_angle_x, best_angle_y, best_angle_z = 0, 0, 0
best_angle_x, best_angle_y, best_angle_z, max_z_of_mass_y = parallel_rotation(points, angle_step=3)
# 使用最佳角度进行旋转并平移obj
pcd_transformed = copy.deepcopy(mesh_obj)
# 最佳角度旋转
R_x = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([1, 0, 0]) * np.radians(best_angle_x))
pcd_transformed.rotate(R_x)
R_y = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 1, 0]) * np.radians(best_angle_y))
pcd_transformed.rotate(R_y)
R_z = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 0, 1]) * np.radians(best_angle_z))
pcd_transformed.rotate(R_z)
T_x = np.eye(4)
T_x[:3, :3] = R_x
center_point = compute_mesh_center(mesh_obj.vertices)
T_center_to_origin = np.eye(4)
T_center_to_origin[:3, 3] = -center_point
T_origin_to_center = np.eye(4)
T_origin_to_center[:3, 3] = center_point
T_rot_center = T_origin_to_center @ T_x @ T_center_to_origin
total_matrix = T_rot_center @ total_matrix
T_y = np.eye(4)
T_y[:3, :3] = R_y
center_point = compute_mesh_center(mesh_obj.vertices)
T_center_to_origin = np.eye(4)
T_center_to_origin[:3, 3] = -center_point
T_origin_to_center = np.eye(4)
T_origin_to_center[:3, 3] = center_point
T_rot_center = T_origin_to_center @ T_y @ T_center_to_origin
total_matrix = T_rot_center @ total_matrix
T_z = np.eye(4)
T_z[:3, :3] = R_z
center_point = compute_mesh_center(mesh_obj.vertices)
T_center_to_origin = np.eye(4)
T_center_to_origin[:3, 3] = -center_point
T_origin_to_center = np.eye(4)
T_origin_to_center[:3, 3] = center_point
T_rot_center = T_origin_to_center @ T_z @ T_center_to_origin
total_matrix = T_rot_center @ total_matrix
#试着旋转180,让脸朝上
vertices = np.asarray(pcd_transformed.vertices)
# 计算平移向量,将最小Y值平移到0
min_z = np.min(vertices[:, 2])
translation_vector = np.array([0,0,-min_z,])
pcd_transformed.translate(translation_vector)
T_trans1 = np.eye(4)
T_trans1[:3, 3] = translation_vector
total_matrix = T_trans1 @ total_matrix
# 计算 z 坐标均值
vertices = np.asarray(pcd_transformed.vertices)
z_mean1 = np.mean(vertices[:, 2])
z_max1 = np.max(vertices[:, 2])
start_time_v1 = time.time()
volume_centroid = get_volume_centroid(pcd_transformed)
z_volume_center1 = volume_centroid[2]
delta = time.time() - start_time_v1
# print(f"get_volume_centroid time={delta}")
angle_rad = np.pi
#print("旋转前质心:", pcd_transformed.get_center())
#print("旋转前点示例:", np.asarray(pcd_transformed.vertices)[:3])
R_y = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 1, 0]) * angle_rad)
pcd_transformed.translate(-center_point)
pcd_transformed.rotate(R_y, center=(0, 0, 0))
pcd_transformed.translate(center_point)
aabb = pcd_transformed.get_axis_aligned_bounding_box()
# center_point = aabb.get_center()
center_point = compute_mesh_center(mesh_obj.vertices)
# 构建绕中心点旋转的变换矩阵[3](@ref)
T_center_to_origin = np.eye(4)
T_center_to_origin[:3, 3] = -center_point
R_y180 = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 1, 0]) * angle_rad)
T_rotate = np.eye(4)
T_rotate[:3, :3] = R_y180
T_origin_to_center = np.eye(4)
T_origin_to_center[:3, 3] = center_point
T_rot_center = T_origin_to_center @ T_rotate @ T_center_to_origin
total_matrix = T_rot_center @ total_matrix
#print("旋转后质心:", pcd_transformed.get_center())
#print("旋转后点示例:", np.asarray(pcd_transformed.vertices)[:3])
#
vertices = np.asarray(pcd_transformed.vertices)
# 计算平移向量,将最小Y值平移到0
min_z = np.min(vertices[:, 2])
max_z = np.max(vertices[:, 2])
# print("min_z1", min_z, obj_path)
translation_vector = np.array([0,0,-min_z,])
# translation_vector = np.array([0,0,-min_z + (min_z-max_z),])
# print("translation_vector1",translation_vector)
pcd_transformed.translate(translation_vector)
T_trans2 = np.eye(4)
T_trans2[:3, 3] = translation_vector
translation = total_matrix[:3, 3]
# print("translation_vector2",translation_vector)
# print(1,translation)
total_matrix = T_trans2 @ total_matrix
translation = total_matrix[:3, 3]
# print(2,translation)
# 计算 z 坐标均值
vertices = np.asarray(pcd_transformed.vertices)
z_mean2 = np.mean(vertices[:, 2])
z_max2 = np.max(vertices[:, 2])
volume_centroid = get_volume_centroid(pcd_transformed)
z_volume_center2 = volume_centroid[2]
# print(f"get_lowest_position_of_center z_max1={z_max1}, z_max2={z_max2}, len={len(pcd_transformed.vertices)}, obj_path={obj_path}")
# print(f"z_mean1={z_mean1}, z_mean2={z_mean2}")
# if (z_mean2 > z_mean1):
# print(f"z_volume_center1={z_volume_center1}, z_volume_center2={z_volume_center2}")
if (z_volume_center2 > z_volume_center1):
R_y = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 1, 0]) * -angle_rad)
centroid = pcd_transformed.get_center()
aabb = pcd_transformed.get_axis_aligned_bounding_box()
# center_point = aabb.get_center()
center_point = compute_mesh_center(mesh_obj.vertices)
pcd_transformed.translate(-center_point)
pcd_transformed.rotate(R_y, center=(0, 0, 0))
pcd_transformed.translate(center_point)
T_center_to_origin = np.eye(4)
T_center_to_origin[:3, 3] = -center_point
T_origin_to_center = np.eye(4)
T_origin_to_center[:3, 3] = center_point
# 构建反向旋转矩阵
R_y = pcd_transformed.get_rotation_matrix_from_axis_angle(np.array([0, 1, 0]) * -angle_rad)
T_rotate_inv = np.eye(4)
T_rotate_inv[:3, :3] = R_y
# 完整的反向绕中心旋转矩阵
T_rot_center_inv = T_origin_to_center @ T_rotate_inv @ T_center_to_origin
total_matrix = T_rot_center_inv @ total_matrix
vertices = np.asarray(pcd_transformed.vertices)
# 计算平移向量,将最小Y值平移到0
min_z = np.min(vertices[:, 2])
# print("min_z2", min_z, obj_path)
translation_vector = np.array([0,0,-min_z,])
pcd_transformed.translate(translation_vector)
T_trans3 = np.eye(4)
T_trans3[:3, 3] = translation_vector
total_matrix = T_trans3 @ total_matrix
# z_mean_min = min(z_mean1, z_mean2)
z_max = min(z_max1, z_max2)
# print("get_lowest_position_of_center2 time", time.time()-start_time2)
return total_matrix, z_max
def get_lowest_position_of_center_ext(mesh_obj, total_matrix):
print(f"get_lowest_position_of_center_ext mesh_obj={mesh_obj}")
temp_matrix, z_max = get_lowest_position_of_z_ext(mesh_obj)
total_matrix = temp_matrix @ total_matrix
return total_matrix, z_max
def calculate_rotation_and_top_of_mass(angle_x, angle_y, angle_z, points):
"""计算某一组旋转角度后的重心"""
# 计算绕X轴、Y轴和Z轴的旋转矩阵
R_x = np.array([
[1, 0, 0],
[0, np.cos(np.radians(angle_x)), -np.sin(np.radians(angle_x))],
[0, np.sin(np.radians(angle_x)), np.cos(np.radians(angle_x))]
])
R_y = np.array([
[np.cos(np.radians(angle_y)), 0, np.sin(np.radians(angle_y))],
[0, 1, 0],
[-np.sin(np.radians(angle_y)), 0, np.cos(np.radians(angle_y))]
])
R_z = np.array([
[np.cos(np.radians(angle_z)), -np.sin(np.radians(angle_z)), 0],
[np.sin(np.radians(angle_z)), np.cos(np.radians(angle_z)), 0],
[0, 0, 1]
])
# 综合旋转矩阵
R = R_z @ R_y @ R_x
# 执行旋转
rotated_points = points @ R.T
# 计算最小z值
min_z = np.min(rotated_points[:, 2])
# 计算平移向量,将最小Z值平移到0
translation_vector = np.array([0, 0, -min_z])
rotated_points += translation_vector
top_of_mass = np.max(rotated_points, axis=0)
return top_of_mass[2], angle_x, angle_y, angle_z
def parallel_rotation(points, angle_step=4):
"""仅绕 Y 轴旋转(假设 X/Z 轴不影响目标函数)"""
max_top = float('inf')
for angle_x in range(-90, 90, angle_step):
for angle_y in range(0, 360, angle_step):
max_z, ax, ay, _ = calculate_rotation_and_top_of_mass(angle_x, angle_y, 0, points)
if max_z < max_top:
max_top = max_z
best_angle_x = ax
best_angle_y = ay
return (best_angle_x, best_angle_y, 0, max_top)
def compute_mesh_center(vertices):
if len(vertices) == 0:
raise ValueError("顶点数组不能为空")
# 确保vertices是NumPy数组
vertices_np = np.asarray(vertices)
# 使用NumPy的mean函数直接计算均值(向量化操作)
centroid = np.mean(vertices_np, axis=0)
return centroid
# -------------------------- 结束:获取z值最低 --------------------------
# -------------------------- 开始:bbox --------------------------
def get_models_bbox(dict_pcd_fix):
"""
单独提取:从dict_fix中解析所有模型的包围盒(bbox)尺寸信息
:param dict_fix: 包含PLY文件名和对应点云的字典
:return: 模型列表(包含name和dimensions)
"""
all_models = []
extend_dist = 2 # 尺寸扩展量(单位:厘米)
for ply_file in dict_pcd_fix:
# 解析PLY文件名中的尺寸信息(格式:"模型ID=维度1+维度2+维度3.ply")
bbox_with_text = ply_file.split("=")
bbox_with = bbox_with_text[-1]
split_text = bbox_with.replace(".ply", "").split("+")
# 转换单位:米 → 厘米 → 加扩展量 → 转回米(int取整避免浮点数精度问题)
x_length = int(float(split_text[2]) * 100) + extend_dist # 第三个维度→x方向
y_length = int(float(split_text[0]) * 100) + extend_dist # 第一个维度→y方向
z_length = int(float(split_text[1]) * 100) + extend_dist # 第二个维度→z方向
all_models.append({
'name': ply_file,
'dimensions': (int(x_length / 100), int(z_length / 100), int(y_length / 100)) # 单位:米
})
return all_models
def arrange_models_on_platform(models, machine_size):
"""
单独提取:将模型在打印平台上进行排版布局
:param models: 由get_models_bbox返回的模型列表(包含name和dimensions)
:param machine_size: 打印机尺寸 (width, depth, height)
:return: (placed_models, unplaced_models) - 已放置和未放置的模型列表
"""
# 初始化打印平台
platform = Platform(
int(machine_size[0]),
int(machine_size[1]),
int(machine_size[2])
)
print("开始计算排序...")
platform.arrange_models(models)
platform.print_results()
return platform.get_result()
import os
def compute_bbox_all_ext(base_original_obj_dir,compact_min_dis=True):
obj_id_list = [aa.split(".o")[0] for aa in os.listdir(base_original_obj_dir) if aa.endswith(".obj")]
obj_id_list = obj_id_list
dict_mesh_obj = {}
for pid_t_y in obj_id_list:
obj_name = pid_t_y+".obj"
obj_path = os.path.join(base_original_obj_dir,obj_name)
mesh_obj = read_mesh(obj_path)
if mesh_obj is None:
continue
dict_mesh_obj[obj_name] = mesh_obj
return compute_bbox_all(dict_mesh_obj,compact_min_dis)
def compute_bbox_all(dict_mesh_obj,is_downsample):
dict_total_matrix= {}
dict_pcd_fix= {}
for key, value in dict_mesh_obj.items():
start_time = time.time()
obj_name = key
mesh_obj = value
total_matrix, pcd_fix, ply_name = compute_bbox(mesh_obj,obj_name,is_downsample)
dict_total_matrix[obj_name] = total_matrix
dict_pcd_fix[ply_name] = pcd_fix
print(f"compute_bbox obj_name={obj_name} ply_name={ply_name} time={time.time()-start_time}")
# dict_mesh_obj.clear()
# del dict_mesh_obj
all_models = get_models_bbox(dict_pcd_fix)
return dict_total_matrix,all_models
def compute_bbox(mesh_obj, obj_name="", is_downsample=True):
# return compute_bbox_ext(mesh_obj, obj_name, is_downsample)
mesh_obj_origin = copy.deepcopy(mesh_obj)
total_matrix, z_max, min_bound, max_bound, ply_name = compute_bbox_ext(mesh_obj, obj_name, is_downsample)
transformed_vertices = mesh_transform_by_matrix(np.asarray(mesh_obj_origin.vertices), total_matrix)
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(transformed_vertices)
if is_downsample:
pcd_downsampled = down_sample(pcd, voxel_size, False)
pcd_fix = pcd_downsampled
else:
pcd_fix = pcd
return total_matrix, pcd_fix, ply_name
def compute_bbox_ext(mesh_obj, obj_name="", is_downsample=True):
total_matrix = np.eye(4)
total_matrix, z_max= get_lowest_position_of_center_ext(mesh_obj, total_matrix)
transformed_vertices = mesh_transform_by_matrix(np.asarray(mesh_obj.vertices), total_matrix)
obj_transformed = copy.deepcopy(mesh_obj)
obj_transformed.vertices = o3d.utility.Vector3dVector(transformed_vertices)
voxel_size = 3 # 设置体素的大小,决定下采样的密度
# 将点云摆正和X轴平衡
obj_transformed_second,total_matrix = arrange_box_correctly(obj_transformed,voxel_size,total_matrix)
total_matrix, min_bound, max_bound, ply_name, pcd_fix = get_new_bbox(obj_transformed_second,obj_name,voxel_size,is_downsample,total_matrix)
del obj_transformed
del obj_transformed_second
# return total_matrix, z_max, min_bound, max_bound, ply_name, pcd_fix
return total_matrix, z_max, min_bound, max_bound, ply_name
def arrange_box_correctly(obj_transformed, voxel_size,total_matrix):
vertices = np.asarray(obj_transformed.vertices)
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(vertices)
# 降采样与特征计算
pcd_downsampled = down_sample(pcd, voxel_size)
points = np.asarray(pcd_downsampled.points)
cov = np.cov(points.T)
center = obj_transformed.get_center()
# 特征分解与方向约束(关键修改点)
eigen_vals, eigen_vecs = np.linalg.eigh(cov)
max_axis = eigen_vecs[:, np.argmax(eigen_vals)]
# print("max_axis", max_axis)
# 强制主方向向量X分量为正(指向右侧)
if max_axis[0] < 0 or (max_axis[0] == 0 and max_axis[1] < 0):
max_axis = -max_axis
target_dir = np.array([1, 0]) # 目标方向为X正轴
current_dir = max_axis[:2] / np.linalg.norm(max_axis[:2])
dot_product = np.dot(current_dir, target_dir)
# print("dot_product", dot_product)
if dot_product < 0.8: # 阈值控制方向敏感性(建议0.6~0.9)
max_axis = -max_axis # 强制翻转方向
# 计算旋转角度
angle_z = np.arctan2(max_axis[1], max_axis[0]) % (2 * np.pi)
if max_axis[0] <= 0 and max_axis[1] <= 0:
angle_z += np.pi
R = o3d.geometry.get_rotation_matrix_from_axis_angle([0, 0, -angle_z])
T = np.eye(4)
T[:3, :3] = R
T[:3, 3] = center - R.dot(center) # 保持中心不变
obj_transformed.transform(T)
total_matrix = T @ total_matrix
return obj_transformed, total_matrix
def get_new_bbox(obj_transformed_second,obj_name,voxel_size,is_downsample,total_matrix):
# 计算点云的边界
points = np.asarray(obj_transformed_second.vertices)
min_bound = np.min(points, axis=0) # 获取点云的最小边界
max_bound = np.max(points, axis=0) # 获取点云的最大边界
# print(f"get_new_bbox1: min_bound={min_bound}, max_bound={max_bound}")
# 确保包围盒的Y坐标不低于0
min_bound[2] = max(min_bound[2], 0) # 确保Y坐标的最小值不低于0
# 重新计算包围盒的中心和半长轴
bbox_center = (min_bound + max_bound) / 2 # 计算包围盒的中心点
bbox_extent = (max_bound - min_bound) # 计算包围盒的半长轴(尺寸)
# 创建包围盒,确保尺寸正确
new_bbox = o3d.geometry.OrientedBoundingBox(center=bbox_center,
R=np.eye(3), # 旋转矩阵,默认没有旋转
extent=bbox_extent)
# 获取包围盒的长、宽和高
x_length = round(bbox_extent[0],3) # X 方向的长
y_length = round(bbox_extent[1],3) # Y 方向的宽
z_length = round(bbox_extent[2],3) # Z 方向的高
bbox_points = np.array([
[min_bound[0], min_bound[1], min_bound[2]],
[max_bound[0], min_bound[1], min_bound[2]],
[max_bound[0], max_bound[1], min_bound[2]],
[min_bound[0], max_bound[1], min_bound[2]],
[min_bound[0], min_bound[1], max_bound[2]],
[max_bound[0], min_bound[1], max_bound[2]],
[max_bound[0], max_bound[1], max_bound[2]],
[min_bound[0], max_bound[1], max_bound[2]]
])
first_corner = bbox_points[2]
translation_vector = -first_corner
obj_transformed_second.translate(translation_vector)
T_trans = np.eye(4)
T_trans[:3, 3] = translation_vector # 设置平移分量 [2,3](@ref)
total_matrix = T_trans @ total_matrix # 矩阵乘法顺序:最新变换左乘[4,5](@ref)
new_bbox.translate(translation_vector)
vertices = np.asarray(obj_transformed_second.vertices)
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(vertices)
if is_downsample:
pcd_downsampled = down_sample(pcd, voxel_size, False)
pcd_fix = pcd_downsampled
else:
pcd_fix = pcd
min_bound = np.min(pcd.points, axis=0) # 获取点云的最小边界
max_bound = np.max(pcd.points, axis=0) # 获取点云的最大边界
# print(f"get_new_bbox2: min_bound={min_bound}, max_bound={max_bound}")
if (not obj_name == ""):
ply_print_pid = obj_name.replace(".obj","")
ply_name = f"{ply_print_pid}={z_length}+{y_length}+{x_length}.ply"
else:
ply_name = ""
return total_matrix, min_bound, max_bound, ply_name, pcd_fix
class Platform:
def __init__(self, width, depth, height):
self.width = width
self.depth = depth
self.height = height
self.placed_models = [] # 已放置的模型
self.unplaced_models = [] # 未能放置的模型
self.first_line = True
self.remove_multiobj_name = ""
def is_cross_border(self, x, y, z, model):
mx, my, mz = model['dimensions']
return is_cross_border_c(x, y, z, mx, my, mz, self.width, self.depth, self.height)
def check_multiobj_cross_pre(self, name, pre_model):
if (pre_model==None):
return
if not is_same_obj(name, pre_model['name']):
return
self.unplaced_models.append(pre_model)
if pre_model in self.placed_models:
self.placed_models.remove(pre_model)
if "pre_model" in pre_model:
self.pre_model = pre_model["pre_model"]
self.check_multiobj_cross_pre(name, self.pre_model)
def check_multiobj_cross(self, model):
if not is_multi_obj(model['name']):
return False
self.unplaced_models.append(model)
if "pre_model" in model:
self.pre_model = model["pre_model"]
self.check_multiobj_cross_pre(model['name'], self.pre_model)
return True
def can_place(self, x, y, z, model, is_print=False):
mx, my, mz = model['dimensions']
if self.is_cross_border(x, y, z, model):
print(f"can_place False 1 cross_border {x}, {y}, {z}, {model}, {self.width}, {self.depth}, {self.height}")
return False
# 碰撞检测(正确逻辑与间距处理)
for placed in self.placed_models:
px, py, pz = placed['position']
pdx, pdy, pdz = placed['dimensions']
# 使用AABB碰撞检测算法[4](@ref)
if (x > px - pdx - extend_dist_model_x and
x - mx - extend_dist_model_x < px and
y > py - pdy - extend_dist_model_y and
y - my - extend_dist_model_y < py and
z < pz + pdz and
z + mz > pz):
print("can_place False 2",False,model,x,y,z,px,pdx,extend_dist_model_x,py,pdy,extend_dist_model_y,my,pz,pdz,pz)
return False
return True
def place_model(self, model, pre_model):
mx, my, mz = model['dimensions']
if mz > self.height:
self.unplaced_models.append(model)
return False
if is_same_obj(model['name'], self.remove_multiobj_name):
self.unplaced_models.append(model)
return False
z = 0
if pre_model is None:
if self.first_line:
model['position'] = (mx + extend_dist_border_x_min, self.depth - extend_dist_border_y_max, 0)
print(f"First Model {model['name']}")
model['first_line'] = True
else:
model['position'] = (self.width - extend_dist_border_x_max, self.depth - extend_dist_border_y_max, 0)
model['first_line'] = False
print("model position1", model['name'], model['position'])
self.placed_models.append(model)
return True
pre_px, pre_py, pre_pz = pre_model['position']
pre_mx, pre_my, pre_mz = pre_model['dimensions']
if self.first_line:
px = pre_px + mx + extend_dist_model_x
model['first_line'] = True
else:
px = pre_px - pre_mx - extend_dist_model_x
model['first_line'] = False
print(model['name'], "px", px, pre_px, pre_mx)
reach_limit_x = False
if self.first_line:
if px > self.width:
reach_limit_x = True
else:
if px - mx < 0:
reach_limit_x = True
if reach_limit_x:
self.first_line = False
px = self.width - extend_dist_border_x_max
start_y = my + extend_dist_border_y_min
final_y = self.depth
print("reach_limit_x final_y1", model['name'], my, final_y, my, extend_dist_border_x_max, px)
for y in range(start_y, final_y, +1):
# print("y",y)
if self.can_place(px, y, z, model, True)==False:
y -= 1
if self.is_cross_border(px, y, z, model):
print(f"cross border : {model['name']}")
if self.check_multiobj_cross(model):
self.remove_multiobj_name = model['name']
return False
model['position'] = (px, y, z)
print("model position2", model['name'], model['position'])
self.placed_models.append(model)
return True
else:
start_y = my + extend_dist_border_y_min
final_y = self.depth
print("final_y2", model['name'], start_y, final_y, my, extend_dist_border_y_max, px)
for y in range(start_y, final_y, +1):
if self.can_place(px, y, z, model)==False:
y -= 1
if self.is_cross_border(px, y, z, model):
print(f"cross border : {model['name']}")
if self.check_multiobj_cross(model):
self.remove_multiobj_name = model['name']
return False
model['position'] = (px, y, z)
print("model position2", model['name'], model['position'])
self.placed_models.append(model)
return True
if 'position' in model:
print("model position3", model['name'], model['position'])
else:
print("model position3 no exist position", model['name'])
self.unplaced_models.append(model)
return False
def arrange_models(self, models):
"""对所有模型进行排布(单层)"""
print(" 单层放置模式:所有模型只能放在平台底面(Z=0)")
# 按高度和面积排序,优先放大模型
models = sorted(models, key=lambda m: (-m['dimensions'][2], -m['dimensions'][0] * m['dimensions'][1]))
self.pre_model = None
for model in models:
print(f"arrange_models {model['name']}")
pre_model_temp = self.pre_model
if self.place_model(model, self.pre_model):
self.pre_model = model
model["pre_model"] = pre_model_temp
def print_results(self):
"""打印排布结果"""
print("Placed Models:")
for model in self.placed_models:
print(f" - {model['name']} at {model['position']} with dimensions {model['dimensions']}")
print("Unplaced Models:")
for model in self.unplaced_models:
print(f" - {model['name']} with dimensions {model['dimensions']}")
def get_result(self):
return self.placed_models, self.unplaced_models
# -------------------------- 结束:bbox --------------------------
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--obj_path", type=str, required=True, help="batchobj_path_id")
args = parser.parse_args()
obj_path = args.obj_path
max, z = get_lowest_position_of_z_ext(obj_path)