.

trellis/representations/mesh/cube2mesh.py

@@ -2,8 +2,7 @@ import torch
 from ...modules.sparse import SparseTensor
 from easydict import EasyDict as edict
 from .utils_cube import *
-from .flexicubes.flexicubes import FlexiCubes
-
+from .flexicube import FlexiCubes
 
 class MeshExtractResult:
     def __init__(self,

trellis/representations/mesh/flexicube.py

@@ -48,6 +48,7 @@ class FlexiCubes:
 
     def __call__(self, voxelgrid_vertices, scalar_field, cube_idx, resolution, qef_reg_scale=1e-3,
                  weight_scale=0.99, beta=None, alpha=None, gamma_f=None, voxelgrid_colors=None, training=False):
+
         surf_cubes, occ_fx8 = self._identify_surf_cubes(scalar_field, cube_idx)
         if surf_cubes.sum() == 0:
             return (
@@ -356,4 +357,4 @@ class FlexiCubes:
             vd = torch.cat([vd, vd_center])
             faces = quad_vd_idx[:, self.quad_split_train].reshape(-1, 4, 2)
             faces = torch.cat([faces, vd_center_idx.reshape(-1, 1, 1).repeat(1, 4, 1)], -1).reshape(-1, 3)
-        return vd, faces, s_edges, edge_indices, vd_color
+        return vd, faces, s_edges, edge_indices, vd_color

trellis/representations/mesh/flexicubes/flexicubes.py

@@ -8,7 +8,6 @@
 
 import torch
 from .tables import *
-from kaolin.utils.testing import check_tensor
 
 __all__ = [
     'FlexiCubes'
@@ -49,29 +48,6 @@ class FlexiCubes:
 
     def __call__(self, voxelgrid_vertices, scalar_field, cube_idx, resolution, qef_reg_scale=1e-3,
                  weight_scale=0.99, beta=None, alpha=None, gamma_f=None, voxelgrid_colors=None, training=False):
-        assert torch.is_tensor(voxelgrid_vertices) and \
-            check_tensor(voxelgrid_vertices, (None, 3), throw=False), \
-            "'voxelgrid_vertices' should be a tensor of shape (num_vertices, 3)"
-        num_vertices = voxelgrid_vertices.shape[0]
-        assert torch.is_tensor(scalar_field) and \
-            check_tensor(scalar_field, (num_vertices,), throw=False), \
-            "'scalar_field' should be a tensor of shape (num_vertices,)"
-        assert torch.is_tensor(cube_idx) and \
-            check_tensor(cube_idx, (None, 8), throw=False), \
-            "'cube_idx' should be a tensor of shape (num_cubes, 8)"
-        num_cubes = cube_idx.shape[0]
-        assert beta is None or (
-            torch.is_tensor(beta) and
-            check_tensor(beta, (num_cubes, 12), throw=False)
-        ), "'beta' should be a tensor of shape (num_cubes, 12)"
-        assert alpha is None or (
-            torch.is_tensor(alpha) and
-            check_tensor(alpha, (num_cubes, 8), throw=False)
-        ), "'alpha' should be a tensor of shape (num_cubes, 8)"
-        assert gamma_f is None or (
-            torch.is_tensor(gamma_f) and
-            check_tensor(gamma_f, (num_cubes,), throw=False)
-        ), "'gamma_f' should be a tensor of shape (num_cubes,)"
 
         surf_cubes, occ_fx8 = self._identify_surf_cubes(scalar_field, cube_idx)
         if surf_cubes.sum() == 0: