Texture Vertex.num_verts_per_mesh deep copy when num_verts_per_mesh is a list

[JudyYe]

Hi,

Nice work! Thank you for this pytorch3d repo which boosted my research efficiency. However, I found a potential unexpected behavior regarding TextureVertex. Here is my guess, proposed fixed, and a toy example.

The TexturesVertex._num_verts_per_mesh is not correctly copied in clone(), detach(), join_batch()when this property is a list. In fact, it is created as a list as in __init__ here or here

As a result, when a list of Mehses is join_batched(), the num_verts_per_mesh in the list will be unexpectedly modified although the merged meshes is in correct shape. A toyish self-contained test is as followed:

verts, faces = create_cube('cpu', 1)
textures = TexturesVertex(torch.ones_like(verts))
mesh_list = []
for i in range(2):
    meshes = Meshes(verts, faces, textures)
    mesh_list.append(meshes)
for i, each in enumerate(mesh_list):
    print(i, each.textures._num_verts_per_mesh)
# output: 
# 0 [8]
# 1 [8]
joined_meshes = join_meshes_as_batch(mesh_list)
print('joined', joined_meshes.textures._num_verts_per_mesh)
# output: 
# joined [8, 8]
for i, each in enumerate(mesh_list):
    print(i, each.textures._num_verts_per_mesh)
# output: 
0 [8, 8] // !!!!
1 [8, 8] // !!!!

Note the output becomes [8, 8] from [8] after join_batch(). After the fixed, the last output is [8] as expected.

create_cube is:

def create_cube(device, N=1, align='center'):
    """
    :return: verts: (1, 8, 3) faces: (1, 12, 3)
    """
    cube_verts = torch.tensor(
        [
            [0, 0, 0],
            [0, 0, 1],
            [0, 1, 0],
            [0, 1, 1],
            [1, 0, 0],
            [1, 0, 1],
            [1, 1, 0],
            [1, 1, 1],
        ],
        dtype=torch.float32,
        device=device,
    )
    if align == 'center':
        cube_verts -= .5

    # faces corresponding to a unit cube: 12x3
    cube_faces = torch.tensor(
        [
            [0, 1, 2],
            [1, 3, 2],  # left face: 0, 1
            [2, 3, 6],
            [3, 7, 6],  # bottom face: 2, 3
            [0, 2, 6],
            [0, 6, 4],  # front face: 4, 5
            [0, 5, 1],
            [0, 4, 5],  # up face: 6, 7
            [6, 7, 5],
            [6, 5, 4],  # right face: 8, 9
            [1, 7, 3],
            [1, 5, 7],  # back face: 10, 11
        ],
        dtype=torch.int64,
        device=device,
    )  # 12, 3

    return cube_verts.unsqueeze(0).expand(N, 8, 3), cube_faces.unsqueeze(0).expand(N, 12, 3)

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@bottler has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

[bottler]

Thanks for letting us know about this. I agree there is a bug here and these fixes are correct. I plan to commit them together with another fix in the same area.

[gkioxari]

@JudyYe
Thank you very much for the kind words! It makes us happy that this library has helped you :)
Just came here to say this :D

[JudyYe]

@gkioxari

Aww. Thank you Georgia! That is so kind of you. Thank you for putting such efforts in maintaining the repo. The whole team is so prompt. And you made my fan-girl moment of the day! :p