How to determine the input bounding box size?

[nepfaff]

I want to do some testing on my data, but I'm struggling to find a working input bounding box size. Does someone have hints on how to find the right size?

Whenever I use a bounding box instead of an initial mesh, I get the following error:

Traceback (most recent call last):
  File "reconstruct.py", line 84, in <module>
    mesh_initial = generate_mesh(args.initial_mesh, views, AABB.load(args.input_bbox), device=device)
  File "/home/nep/robot_locomotion/neural-deferred-shading/nds/utils/geometry.py", line 355, in generate_mesh
    v, f = mesh_generators[generator_name]()
  File "/home/nep/robot_locomotion/neural-deferred-shading/nds/utils/geometry.py", line 350, in <lambda>
    'vh32': (lambda: compute_visual_hull(views, aabb, grid_size=32, device=device)),
  File "/home/nep/robot_locomotion/neural-deferred-shading/nds/utils/geometry.py", line 249, in compute_visual_hull
    return marching_cubes(voxels, voxels_occupancy, gradient_direction='ascent')
  File "/home/nep/robot_locomotion/neural-deferred-shading/nds/utils/geometry.py", line 203, in marching_cubes
    vertices, faces, normals, values = measure.marching_cubes_lewiner(voxel_occupancy.cpu().numpy(), level=0.5, spacing=spacing, **kwargs)
  File "/home/nep/.local/lib/python3.8/site-packages/skimage/measure/_marching_cubes_lewiner.py", line 276, in marching_cubes_lewiner
    return _marching_cubes_lewiner(volume, level, spacing, gradient_direction,
  File "/home/nep/.local/lib/python3.8/site-packages/skimage/measure/_marching_cubes_lewiner.py", line 302, in _marching_cubes_lewiner
    raise ValueError("Surface level must be within volume data range.")

A OneDrive download link to one of my datasets: https://1drv.ms/u/s!AjFJcUGSEjrpgcdYVbeeM28llLLshg?e=R1auVR Preview: