def batch_load_gt_data(j, meshes, gt_corners, sem_cls_label, batch_id, voxel_size):
mesh_data = meshes[j]
obj_points = mesh_data.vertices
obj_points = fit_shapenet_obj_to_votenet_box(obj_points, gt_corners[batch_id, j])
mesh_data.vertices = obj_points
dimension = int(max((obj_points.max(0) - obj_points.min(0))) / voxel_size)
dimension = max(dimension, 2)
# internal voxels
voxel_data_internal = voxelize_mesh(mesh_data, dimension=dimension, wireframe=True, dilated_carving=True)
# surface voxels
voxel_data_surface = voxelize_mesh(mesh_data, exact=True, dimension=dimension)
return (sem_cls_label[batch_id, j], gt_corners[batch_id, j], (voxel_data_internal, voxel_data_surface))
def batch_load_pred_data_wo_cls(j, proposal_ids, meshes, pred_corners, batch_id, pred_sem_cls, obj_prob, voxel_size):
mesh_data = meshes[list(proposal_ids[batch_id, :, 0]).index(j)]
obj_points = mesh_data.vertices
obj_points = fit_shapenet_obj_to_votenet_box(obj_points, pred_corners[batch_id, j])
mesh_data.vertices = obj_points
dimension = int(max((obj_points.max(0) - obj_points.min(0))) / voxel_size)
dimension = max(dimension, 2)
# internal voxels
voxel_data_internal = voxelize_mesh(mesh_data, dimension=dimension, wireframe=True, dilated_carving=True)
# surface voxels
voxel_data_surface = voxelize_mesh(mesh_data, exact=True, dimension=dimension)
return (pred_sem_cls[batch_id, j], pred_corners[batch_id, j], obj_prob[batch_id, j],
(voxel_data_internal, voxel_data_surface))
def voxelize_binvox(mesh,
pitch=None,
dimension=None,
bounds=None,
**binvoxer_kwargs):
"""
Voxelize via binvox tool.
Parameters
--------------
mesh : trimesh.Trimesh
Mesh to voxelize
pitch : float
Side length of each voxel. Ignored if dimension is provided
dimension: int
Number of voxels along each dimension. If not provided, this is
calculated based on pitch and bounds/mesh extents
bounds: (2, 3) float
min/max values of the returned `VoxelGrid` in each instance. Uses
`mesh.bounds` if not provided.
**binvoxer_kwargs:
Passed to `trimesh.exchange.binvox.Binvoxer`.
Should not contain `bounding_box` if bounds is not None.
Returns
--------------
`VoxelGrid` instance
Raises
--------------
`ValueError` if `bounds is not None and 'bounding_box' in binvoxer_kwargs`.
"""
from trimesh.exchange import binvox
if dimension is None:
# pitch must be provided
if bounds is None:
extents = mesh.extents
else:
mins, maxs = bounds
extents = maxs - mins
dimension = int(np.ceil(np.max(extents) / pitch))
if bounds is not None:
if 'bounding_box' in binvoxer_kwargs:
raise ValueError('Cannot provide both bounds and bounding_box')
binvoxer_kwargs['bounding_box'] = np.asanyarray(bounds).flatten()
binvoxer = binvox.Binvoxer(dimension=dimension, **binvoxer_kwargs)
return binvox.voxelize_mesh(mesh, binvoxer)
chair_mesh = trimesh.load(os.path.join(dir_models, '%s.obj' % base_name))
if isinstance(chair_mesh, trimesh.scene.Scene):
chair_mesh = trimesh.util.concatenate([
trimesh.Trimesh(mesh.vertices, mesh.faces)
for mesh in chair_mesh.geometry.values()
])
binvox_path = os.path.join(dir_models, '%s.binvox' % base_name)
chair_voxels = trimesh.load(binvox_path)
chair_voxels = v.VoxelGrid(chair_voxels.encoding.dense,
chair_voxels.transform)
print('white: voxelized chair (binvox, exact)')
show(chair_mesh,
voxelize_mesh(chair_mesh, exact=True),
colors=(1, 1, 1, 0.3))
print('red: binvox-loaded chair')
show(chair_mesh, chair_voxels, colors=(1, 0, 0, 0.3))
voxelized_chair_mesh = chair_mesh.voxelized(
np.max(chair_mesh.extents) / 32)
print('green: voxelized chair (default).')
show(chair_mesh, voxelized_chair_mesh, colors=(0, 1, 0, 0.3))
shape = (50, 17, 63)
revox = chair_voxels.revoxelized(shape)
print('cyan: revoxelized.')
show(chair_mesh, revox, colors=(0, 1, 1, 0.3))