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some fixes

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This commit is contained in:
Yousef Rafat 2025-07-10 21:32:35 +03:00
parent f49e4b5411
commit b184a61046
2 changed files with 16 additions and 28 deletions
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28
comfy/ldm/hunyuan3dv2_1/vae.py
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@ -5,7 +5,6 @@
import torch
from torch import Tensor
import math
import trimesh
import numpy as np
from skimage import measure
from dataclasses import dataclass
@ -607,8 +606,8 @@ class PointCrossAttention(nn.Module):
@dataclass
class Latent2MeshOutput():
# mesh for vertices and faces
mesh_v: None
mesh_f: None
vertices: None
faces: None
class SufraceExtractor():
def compute_box_stat(self, bounds, octree_resolution: int):
@ -644,7 +643,7 @@ class SufraceExtractor():
vertices, faces = self.run(grid_logits[i], **kwds)
vertices = vertices.astype(np.float32)
faces = np.ascontiguousarray(faces)
outputs.append(Latent2MeshOutput(mesh_v = vertices, mesh_f = faces))
outputs.append(Latent2MeshOutput(vertices = vertices, faces = faces))
except Exception:
import traceback
@ -687,24 +686,6 @@ class VanillaVolumeDecoder():
return grid_logits
def export_to_trimesh(mesh_output):
import trimesh
if isinstance(mesh_output, list):
outputs = []
for mesh in mesh_output:
if mesh is None:
outputs.append(None)
else:
mesh.mesh_f = mesh.mesh_f[:, ::-1]
mesh_output = trimesh.Trimesh(mesh.mesh_v, mesh.mesh_f)
outputs.append(mesh_output)
return outputs
else:
mesh_output.mesh_f = mesh_output.mesh_f[:, ::-1]
mesh_output = trimesh.Trimesh(mesh_output.mesh_v, mesh_output.mesh_f)
return mesh_output
def normalize_mesh(mesh, scale = 0.9999):
"""Normalize mesh to fit in [-scale, scale]. Translate mesh so its center is [0,0,0]"""
@ -767,6 +748,8 @@ def sharp_sample_pointcloud(mesh, num = 16384):
def load_surface_sharpedge(mesh, num_points=4096, num_sharp_points=4096, sharpedge_flag = True, device = "cuda"):
"""Load a surface with optional sharp-edge annotations from a trimesh mesh."""
import trimesh
try:
mesh_full = trimesh.util.concatenate(mesh.dump())
except Exception:
@ -837,6 +820,7 @@ class SharpEdgeSurfaceLoader:
@staticmethod
def _load_mesh(mesh_input):
import trimesh
if isinstance(mesh_input, str):
mesh = trimesh.load(mesh_input, force="mesh", merge_primitives = True)

16
comfy_extras/nodes_hunyuan3d.py
View File

@ -110,17 +110,15 @@ class VAEDecodeHunyuan3D:
}),
"num_chunks": ("INT", {
"default": 8000, "min": 1000, "max": 500000,
"visible_if": {"version": "2.0"}
}),
"octree_resolution": ("INT", {
"default": 256, "min": 16, "max": 512,
"visible_if": {"version": "2.0"}
}),
}
}
RETURN_TYPES = ("VOXEL", "SDF_FUNCTION")
RETURN_NAMES = ("voxel", "sdf")
RETURN_TYPES = ("VOXEL", "MESH")
RETURN_NAMES = ("voxel", "mesh")
FUNCTION = "decode"
CATEGORY = "latent/3d"
@ -137,6 +135,12 @@ class VAEDecodeHunyuan3D:
mesh = vae.decode(samples["samples"], to_mesh = True,
num_chunks = num_chunks,
octree_resolution = octree_resolution)
# ensure batch dim
if mesh.verticies.ndim == 2:
mesh.verticies = mesh.verticies[np.newaxis, ...]
mesh.faces = mesh.faces[np.newaxis, ...]
return (None, mesh)
def voxel_to_mesh(voxels, threshold=0.5, device=None):
@ -495,7 +499,7 @@ class VoxelToMesh:
return (MESH(torch.stack(vertices), torch.stack(faces)), )
def save_glb(vertices, faces, filepath, metadata=None, numpy_ready = False):
def save_glb(vertices, faces, filepath, metadata=None):
"""
Save PyTorch tensor vertices and faces as a GLB file without external dependencies.
@ -506,7 +510,7 @@ def save_glb(vertices, faces, filepath, metadata=None, numpy_ready = False):
"""
# Convert tensors to numpy arrays
if not numpy_ready:
if isinstance(vertices, torch.tensor) and isinstance(faces, torch.tensor):
vertices_np = vertices.cpu().numpy().astype(np.float32)
faces_np = faces.cpu().numpy().astype(np.uint32)
else: