revert

comfy_extras/nodes_hunyuan3d.py

@@ -444,9 +444,7 @@ class VoxelToMeshBasic(IO.ComfyNode):
             vertices.append(v)
             faces.append(f)
 
-        if vertices and all(v.shape == vertices[0].shape for v in vertices) and all(f.shape == faces[0].shape for f in faces):
+        return IO.NodeOutput(Types.MESH(torch.stack(vertices), torch.stack(faces)))
-            return IO.NodeOutput(Types.MESH(torch.stack(vertices), torch.stack(faces)))
-        return IO.NodeOutput(pack_variable_mesh_batch(vertices, faces))
 
     decode = execute  # TODO: remove
 
@@ -483,9 +481,7 @@ class VoxelToMesh(IO.ComfyNode):
             vertices.append(v)
             faces.append(f)
 
-        if vertices and all(v.shape == vertices[0].shape for v in vertices) and all(f.shape == faces[0].shape for f in faces):
+        return IO.NodeOutput(Types.MESH(torch.stack(vertices), torch.stack(faces)))
-            return IO.NodeOutput(Types.MESH(torch.stack(vertices), torch.stack(faces)))
-        return IO.NodeOutput(pack_variable_mesh_batch(vertices, faces))
 
     decode = execute  # TODO: remove
 
@@ -633,57 +629,6 @@ def save_glb(vertices, faces, filepath, metadata=None, colors=None):
 
     return filepath
 
-
-def pack_variable_mesh_batch(vertices, faces, colors=None):
-    batch_size = len(vertices)
-    max_vertices = max(v.shape[0] for v in vertices)
-    max_faces = max(f.shape[0] for f in faces)
-
-    packed_vertices = vertices[0].new_zeros((batch_size, max_vertices, vertices[0].shape[1]))
-    packed_faces = faces[0].new_zeros((batch_size, max_faces, faces[0].shape[1]))
-    vertex_counts = torch.tensor([v.shape[0] for v in vertices], device=vertices[0].device, dtype=torch.int64)
-    face_counts = torch.tensor([f.shape[0] for f in faces], device=faces[0].device, dtype=torch.int64)
-
-    for i, (v, f) in enumerate(zip(vertices, faces)):
-        packed_vertices[i, :v.shape[0]] = v
-        packed_faces[i, :f.shape[0]] = f
-
-    mesh = Types.MESH(packed_vertices, packed_faces)
-    mesh.vertex_counts = vertex_counts
-    mesh.face_counts = face_counts
-
-    if colors is not None:
-        max_colors = max(c.shape[0] for c in colors)
-        packed_colors = colors[0].new_zeros((batch_size, max_colors, colors[0].shape[1]))
-        color_counts = torch.tensor([c.shape[0] for c in colors], device=colors[0].device, dtype=torch.int64)
-        for i, c in enumerate(colors):
-            packed_colors[i, :c.shape[0]] = c
-        mesh.colors = packed_colors
-        mesh.color_counts = color_counts
-
-    return mesh
-
-
-def get_mesh_batch_item(mesh, index):
-    if hasattr(mesh, "vertex_counts"):
-        vertex_count = int(mesh.vertex_counts[index].item())
-        face_count = int(mesh.face_counts[index].item())
-        vertices = mesh.vertices[index, :vertex_count]
-        faces = mesh.faces[index, :face_count]
-        colors = None
-        if hasattr(mesh, "colors") and mesh.colors is not None:
-            if hasattr(mesh, "color_counts"):
-                color_count = int(mesh.color_counts[index].item())
-                colors = mesh.colors[index, :color_count]
-            else:
-                colors = mesh.colors[index, :vertex_count]
-        return vertices, faces, colors
-
-    colors = None
-    if hasattr(mesh, "colors") and mesh.colors is not None:
-        colors = mesh.colors[index]
-    return mesh.vertices[index], mesh.faces[index], colors
-
 class SaveGLB(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -741,8 +686,8 @@ class SaveGLB(IO.ComfyNode):
             bsz = mesh.vertices.shape[0]
             for i in range(bsz):
                 f = f"{filename}_{counter:05}_.glb"
-                vertices, faces, v_colors = get_mesh_batch_item(mesh, i)
+                v_colors = mesh.colors[i] if hasattr(mesh, "colors") and mesh.colors is not None else None
-                save_glb(vertices, faces, os.path.join(full_output_folder, f), metadata, v_colors)
+                save_glb(mesh.vertices[i], mesh.faces[i], os.path.join(full_output_folder, f), metadata, v_colors)
                 results.append({
                     "filename": f,
                     "subfolder": subfolder,