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286 lines
9.6 KiB
286 lines
9.6 KiB
import open3d as o3d |
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import numpy as np |
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import re |
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from config import * |
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# -------------------------- 开始：运行 ---------------------------------- |
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def is_run_local_data(): |
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if curr_run_mode == run_mode.formal: |
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return False |
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return True |
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def need_upload_result(): |
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if curr_run_mode == run_mode.test: |
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return False |
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return True |
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def is_use_debug_oss(): |
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if curr_run_mode == run_mode.test: |
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return True |
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return False |
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# -------------------------- 结束：运行 ---------------------------------- |
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# -------------------------- 开始：模型 ---------------------------------- |
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def read_mesh(obj_path): |
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mesh_obj = o3d.io.read_triangle_mesh(obj_path) |
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return mesh_obj |
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def down_sample(pcd, voxel_size, farthest_sample = False): |
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original_num = len(pcd.points) |
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target_samples = 1500 # 1000 |
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num_samples = min(target_samples, original_num) |
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# 第一步：使用体素下采样快速减少点数量 |
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# voxel_size = 3 |
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if farthest_sample: |
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pcd_voxel = pcd.farthest_point_down_sample(num_samples=num_samples) |
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else: |
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pcd_voxel = pcd.voxel_down_sample(voxel_size) |
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down_num = len(pcd_voxel.points) |
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# print(f"original_num={original_num}, down_num={down_num}") |
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# 第二步：仅在必要时进行最远点下采样 |
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if len(pcd_voxel.points) > target_samples and False: |
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pcd_downsampled = pcd_voxel.farthest_point_down_sample(num_samples=num_samples) |
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else: |
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pcd_downsampled = pcd_voxel |
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return pcd_downsampled |
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def get_volume_centroid(mesh): |
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"""向量化版本的体积重心计算""" |
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vertices = np.asarray(mesh.vertices) |
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triangles = np.asarray(mesh.triangles) |
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# 一次性获取所有三角形的顶点 [n_triangles, 3, 3] |
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tri_vertices = vertices[triangles] |
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# 分别提取三个顶点 |
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v0 = tri_vertices[:, 0, :] # [n, 3] |
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v1 = tri_vertices[:, 1, :] # [n, 3] |
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v2 = tri_vertices[:, 2, :] # [n, 3] |
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# 向量化计算叉积和点积 |
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cross_vec = np.cross(v1, v2) # [n, 3] |
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dot_results = np.einsum('ij,ij->i', v0, cross_vec) # 批量点积 [n] |
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# 计算每个四面体体积 [n] |
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tetra_volumes = np.abs(dot_results) / 6.0 |
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# 计算每个四面体重心 [n, 3] |
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tetra_centers = (v0 + v1 + v2) / 4.0 |
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# 总体积和加权重心 |
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total_volume = np.sum(tetra_volumes) |
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if total_volume > 0: |
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weighted_center = np.sum(tetra_volumes[:, np.newaxis] * tetra_centers, axis=0) / total_volume |
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return weighted_center |
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else: |
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return np.mean(vertices, axis=0) |
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def mesh_tranform_to_pcd(mesh, transform_matrix): |
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vertices = np.asarray(mesh.vertices) |
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transformed_vertices = mesh_transform_by_matrix(vertices, transform_matrix) |
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mesh.vertices = o3d.utility.Vector3dVector(transformed_vertices) |
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return mesh_to_pcd(mesh) |
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def mesh_to_pcd(mesh, is_down_sample=True): |
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vertices = np.asarray(mesh.vertices) |
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pcd = o3d.geometry.PointCloud() |
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pcd.points = o3d.utility.Vector3dVector(vertices) |
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if is_down_sample: |
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pcd_downsampled = down_sample(pcd, voxel_size, False) |
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return pcd_downsampled |
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else: |
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return pcd |
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def mesh_transform_by_matrix(vertices, transform_matrix): |
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""" |
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手动实现网格变换：对每个顶点应用齐次变换矩阵 |
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参数: |
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vertices: 网格顶点数组 (N, 3) |
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transform_matrix: 4x4 齐次变换矩阵 |
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返回: |
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变换后的顶点数组 (N, 3) |
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""" |
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# 1. 顶点转齐次坐标 (N, 3) → (N, 4) |
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homogeneous_vertices = np.hstack((vertices, np.ones((vertices.shape[0], 1)))) |
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# 2. 应用变换矩阵：矩阵乘法 (4x4) * (4xN) → (4xN) |
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transformed_homogeneous = transform_matrix @ homogeneous_vertices.T |
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# 3. 转回非齐次坐标 (3xN) → (N, 3) |
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transformed_vertices = transformed_homogeneous[:3, :].T |
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return transformed_vertices |
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import os |
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def transform_save_bpy(layout_data, original_obj_pid_dir): |
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# 清除场景 |
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bpy.ops.object.select_all(action='SELECT') |
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bpy.ops.object.delete(use_global=False) |
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## 尺寸调整，环境设置 |
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bpy.ops.object.delete(use_global=False, confirm=False) |
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bpy.context.scene.unit_settings.length_unit = 'CENTIMETERS' |
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bpy.context.scene.unit_settings.scale_length = 0.001 |
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bpy.context.scene.unit_settings.mass_unit = 'GRAMS' |
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meshes = [] |
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need_offset = True |
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for model in layout_data["models"]: |
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transform = model.get('transform', {}) |
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homo_matrix = transform["homo_matrix"] |
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reconstructed_matrix = np.array(homo_matrix, dtype=np.float64) |
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obj_name = model.get('file_name', '') |
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obj_path = os.path.join(original_obj_pid_dir, obj_name) |
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mtl_name_temp = obj_name |
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separator = "_P" |
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index = mtl_name_temp.find(separator) |
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if index != -1: |
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old_mtl_name = mtl_name_temp[:index] |
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else: |
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old_mtl_name = mtl_name_temp # 或者你希望的其他处理逻辑，比如直接使用原字符串或报错 |
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old_mtl_name = f"{old_mtl_name}.mtl" |
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old_mtl_path = os.path.join(original_obj_pid_dir, old_mtl_name) |
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bpy.ops.wm.obj_import(filepath=obj_path) |
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imported_object = bpy.context.object |
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if imported_object is None or imported_object.type != 'MESH': |
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print(f"警告: 未能成功导入网格对象 {obj_name}。跳过。") |
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continue |
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mesh_data = imported_object.data |
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mesh_data.calc_loop_triangles() |
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original_vertices = np.empty(len(mesh_data.vertices) * 3, dtype=np.float64) |
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mesh_data.vertices.foreach_get('co', original_vertices) |
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original_vertices = original_vertices.reshape(-1, 3) |
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transformed_vertices = mesh_transform_by_matrix(original_vertices, reconstructed_matrix) |
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if need_offset: |
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offset = np.array([-small_machine_size[0], -small_machine_size[1], 0]) |
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transformed_vertices += offset |
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print(f"已对模型 {obj_name} 应用偏移: {offset}") |
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flattened_verts = transformed_vertices.reshape(-1) |
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mesh_data.vertices.foreach_set('co', flattened_verts) |
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mesh_data.update() |
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meshes.append(imported_object) |
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# 导出前确保选中当前对象 |
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bpy.ops.object.select_all(action='DESELECT') |
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imported_object.select_set(True) |
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bpy.context.view_layer.objects.active = imported_object |
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bpy.ops.wm.obj_export( |
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filepath=obj_path, |
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export_selected_objects=True, |
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export_materials=True, |
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path_mode='AUTO' |
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) |
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os.remove(old_mtl_path) |
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def transform_save_o3d(layout_data, original_obj_pid_dir): |
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meshes = [] |
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# 小打印机需要偏移[-small_machine_size[0], -small_machine_size[1], 0] |
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need_offset = True |
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for model in layout_data["models"]: |
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transform = model.get('transform', {}) |
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homo_matrix = transform["homo_matrix"] # 获取存储的列表 |
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reconstructed_matrix = np.array(homo_matrix, dtype=np.float64) |
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obj_name = model.get('file_name', '') |
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obj_path = os.path.join(original_obj_pid_dir, obj_name) |
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# 加载网格 |
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try: |
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mesh = o3d.io.read_triangle_mesh(obj_path, enable_post_processing=True) |
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if not mesh.has_vertices(): |
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print(f"警告: 网格无有效顶点 - {obj_path}") |
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continue |
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except Exception as e: |
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print(f"加载模型失败: {obj_path} - {e}") |
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continue |
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original_vertices = np.asarray(mesh.vertices) |
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transformed_vertices = mesh_transform_by_matrix(original_vertices, reconstructed_matrix) |
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# 如果 need_offset 为 True，应用额外的偏移 |
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if need_offset: |
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offset = np.array([-small_machine_size[0], -small_machine_size[1], 0]) |
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transformed_vertices += offset |
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print(f"已对模型 {obj_name} 应用偏移: {offset}") |
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mesh.vertices = o3d.utility.Vector3dVector(transformed_vertices) |
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meshes.append(mesh) |
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obj_path_arrange = os.path.join(original_obj_pid_dir, "arrange") |
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if not os.path.exists(obj_path_arrange): |
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os.mkdir(obj_path_arrange) |
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obj_path_arrange_obj = os.path.join(obj_path_arrange, obj_name) |
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print("obj_path_arrange_obj", obj_path_arrange_obj) |
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mesh.compute_vertex_normals() |
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o3d.io.write_triangle_mesh(obj_path_arrange_obj, mesh,write_triangle_uvs=True) |
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voxel_size = 3 |
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def is_multi_obj(obj_name): |
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pattern = r'_x(\d+)' |
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match = re.search(pattern, obj_name) |
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if match: |
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number = match.group(1) |
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if int(number) > 1 : |
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return True |
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return False |
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def is_same_obj(obj_name1, obj_name2): |
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pre_name1 = obj_name1.split("_x")[0] |
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pre_name2 = obj_name2.split("_x")[0] |
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print(f"pre_name1={pre_name1}, pre_name2={pre_name2}") |
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if (pre_name1==pre_name2): |
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return True |
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return False |
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# -------------------------- 结束：模型 ---------------------------------- |
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# -------------------------- 开始：碰撞检测和越界 -------------------------- |
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extend_dist_border_x_min = 6 |
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extend_dist_border_x_max = 3 |
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extend_dist_border_z_max = 3 |
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extend_dist_border_y_min = 6 |
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extend_dist_border_y_max = 6 |
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extend_dist_model_x = 4 |
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extend_dist_model_y = 2 |
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extend_dist_model_z = 2 |
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extend_dist_box = 1 |
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def is_cross_border_c(x, y, z, mx, my, mz, max_x, max_y, max_z): |
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if (x - mx < extend_dist_border_x_min or |
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y - my < extend_dist_border_y_min or |
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z + mz > max_z - extend_dist_border_z_max or |
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y > max_y - extend_dist_border_y_max): |
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return True |
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return False |
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# -------------------------- 结束：碰撞检测和越界 --------------------------
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