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Runtime error
| import os | |
| import trimesh | |
| import numpy as np | |
| from .utils.libmesh import check_mesh_contains | |
| def get_occ_gt( | |
| in_path=None, | |
| vertices=None, | |
| faces=None, | |
| pts_num=1000, | |
| points_sigma=0.01, | |
| with_dp=False, | |
| points=None, | |
| extra_points=None | |
| ): | |
| if in_path is not None: | |
| mesh = trimesh.load(in_path, process=False) | |
| print(type(mesh.vertices), mesh.vertices.shape, mesh.faces.shape) | |
| mesh = trimesh.Trimesh(vertices=vertices, faces=faces, process=False) | |
| # print('get_occ_gt', type(mesh.vertices), mesh.vertices.shape, mesh.faces.shape) | |
| # points_size = 100000 | |
| points_padding = 0.1 | |
| # points_sigma = 0.01 | |
| points_uniform_ratio = 0.5 | |
| n_points_uniform = int(pts_num * points_uniform_ratio) | |
| n_points_surface = pts_num - n_points_uniform | |
| if points is None: | |
| points_scale = 2.0 | |
| boxsize = points_scale + points_padding | |
| points_uniform = np.random.rand(n_points_uniform, 3) | |
| points_uniform = boxsize * (points_uniform - 0.5) | |
| points_surface, index_surface = mesh.sample(n_points_surface, return_index=True) | |
| points_surface += points_sigma * np.random.randn(n_points_surface, 3) | |
| points = np.concatenate([points_uniform, points_surface], axis=0) | |
| if extra_points is not None: | |
| extra_points += points_sigma * np.random.randn(len(extra_points), 3) | |
| points = np.concatenate([points, extra_points], axis=0) | |
| occupancies = check_mesh_contains(mesh, points) | |
| index_surface = None | |
| # points = points.astype(dtype) | |
| # print('occupancies', occupancies.dtype, np.sum(occupancies), occupancies.shape) | |
| # occupancies = np.packbits(occupancies) | |
| # print('occupancies bit', occupancies.dtype, np.sum(occupancies), occupancies.shape) | |
| # print('occupancies', points.shape, occupancies.shape, occupancies.dtype, np.sum(occupancies), index_surface.shape) | |
| return_dict = {} | |
| return_dict['points'] = points | |
| return_dict['points.occ'] = occupancies | |
| return_dict['sf_sidx'] = index_surface | |
| # export_pointcloud(mesh, modelname, loc, scale, args) | |
| # export_points(mesh, modelname, loc, scale, args) | |
| return return_dict | |