此阶段需要导入必要的Python库:NumPy用于数值运算,Open3D用于点云和网格处理,scikit-image用于Marching Cubes算法的实现,SciPy用于空间数据结构和计算。 importnumpyasnpimportopen3daso3dfromskimageimportmeasurefromscipy.spatialimportcKDTree 收集3D点云数据 在此步骤中,收集需要处理的点云数据。这可能涉及从磁盘读取文件(...
from scipy.spatial import Delaunay from skimage import measure from skimage.measure import marching_cubes 生成网格 verts, faces, normals, values = measure.marching_cubes(points_3D) 解释:该代码将Marching Cubes算法应用于3D点云以生成网格。它返回定义结果3D网格的顶点、面、顶点法线和标量值。 可视化网格 ...
# 需要导入模块: from skimage import measure [as 别名]# 或者: from skimage.measure importmarching_cubes[as 别名]defplot_3d(image, threshold=-300):# Position the scan upright,# so the head of the patient would be at the top facing the camerap = image.transpose(2,1,0)#p = imageverts,...
def compute_marching_cubes_regular_grid(self, level: float, scalar_field, mask_array=None, rescale=False, **kwargs): """Compute the surface (vertices and edges) of a given surface by computing marching cubes (by skimage) Args: level (float): value of the scalar field at the surface sc...
在新版本中，有两个方法marching_cubes_lewiner和marching_cubes_classic。但是classic不带step_size参数。
(voxel, scale_factor=0.5, mode='trilinear', align_corners=True)voxel = np.array(voxel.squeeze(0).squeeze(0))voxel = np.pad(voxel, ((5, 5), (5, 5), (5, 5)), 'constant')vertices_recon, faces_recon, _, _ = skimage.measure.marching_cubes(voxel, level=0)mesh = trimesh.Tri...
(voxel, scale_factor=0.5, mode='trilinear', align_corners=True)voxel = np.array(voxel.squeeze(0).squeeze(0))voxel = np.pad(voxel, ((5, 5), (5, 5), (5, 5)), 'constant')vertices_recon, faces_recon, _, _ = skimage.measure.marching_cubes(voxel,...
verts, faces = measure.marching_cubes(binary,0.5) Three(path, verts, faces) 開發者ID:aaalgo,項目名稱:plumo,代碼行數:7,代碼來源:process.py 示例4: getVFByMarchingCubes ▲點讚 5▼ # 需要導入模塊: from skimage import measure [as 別名]# 或者: from skimage.measure importmarching_cubes[as 別...
1. skimage.measure.marching_cubes():Lewiner推进立方体算法来查找3D体积数据中的曲面。 2. skimage.measure.marching_cubes_classic():经典的游动立方体算法,用于查找3D体积数据中的曲面。 marching_cubes比marching_cubes_classic()算法更快,解决了模糊问题,并保证拓扑结果正确。因此,除非经典算法有特定需求,否则march...
#importing librariesfrom scipy.spatial import Delaunayfrom skimage import measurefrom skimage.measure import marching_cubes 生成网格 verts, faces, normals, values = measure.marching_cubes(points_3D) 解释:该代码将Marching Cubes算法应用于3D点云以生成网格。它返回定义结果3D网格的顶点、面、顶点法线和标量值...