def __call__(self, x):
import kaolin.conversions as cvt
x = super().__call__(x)
t = []
for i in range(x.shape[0]):
t.append(
cvt.voxelgrid_to_pointcloud(x[i], self.res, normalize=True))
return torch.stack(t)
def __call__(self, voxel: Type[VoxelGrid]):
"""
Args:
voxel (torch.Tensor): Voxel grid.
Returns:
(torch.Tensor): Converted point cloud.
"""
return cvt.voxelgrid_to_pointcloud(voxel, self.num_points, self.thresh, self.mode, self.normalize)