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[V3] hunyuan3d: make Voxel and Mesh types strict #9061

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[V3] hunyuan3d: make Voxel and Mesh types strict #9061

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14 changes: 12 additions & 2 deletions comfy_api/latest/_io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -619,13 +619,23 @@ class LossMapDict(TypedDict):
loss: list[torch.Tensor]
Type = LossMapDict


@comfytype(io_type="VOXEL")
class Voxel(ComfyTypeIO):
Type = Any # TODO: VOXEL class is defined in comfy_extras/nodes_hunyuan3d.py; should be moved to somewhere else before referenced directly in v3
class VoxelDict(TypedDict):
data: torch.Tensor

Type = VoxelDict


@comfytype(io_type="MESH")
class Mesh(ComfyTypeIO):
Type = Any # TODO: MESH class is defined in comfy_extras/nodes_hunyuan3d.py; should be moved to somewhere else before referenced directly in v3
class MeshDict(TypedDict):
vertices: list[torch.Tensor]
faces: list[torch.Tensor]

Type = MeshDict


@comfytype(io_type="HOOKS")
class Hooks(ComfyTypeIO):
Expand Down
50 changes: 21 additions & 29 deletions comfy_extras/v3/nodes_hunyuan3d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,17 +16,6 @@
from comfy_api.latest import io


class VOXEL:
def __init__(self, data):
self.data = data


class MESH:
def __init__(self, vertices, faces):
self.vertices = vertices
self.faces = faces


def voxel_to_mesh(voxels, threshold=0.5, device=None):
if device is None:
device = torch.device("cpu")
Expand Down Expand Up @@ -485,11 +474,11 @@ def define_schema(cls):
node_id="Hunyuan3Dv2Conditioning_V3",
category="conditioning/video_models",
inputs=[
io.ClipVisionOutput.Input("clip_vision_output")
io.ClipVisionOutput.Input("clip_vision_output"),
],
outputs=[
io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(display_name="negative")
io.Conditioning.Output(display_name="negative"),
]
)

Expand All @@ -511,11 +500,11 @@ def define_schema(cls):
io.ClipVisionOutput.Input("front", optional=True),
io.ClipVisionOutput.Input("left", optional=True),
io.ClipVisionOutput.Input("back", optional=True),
io.ClipVisionOutput.Input("right", optional=True)
io.ClipVisionOutput.Input("right", optional=True),
],
outputs=[
io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(display_name="negative")
io.Conditioning.Output(display_name="negative"),
]
)

Expand Down Expand Up @@ -552,7 +541,7 @@ def define_schema(cls):
)

@classmethod
def execute(cls, mesh, filename_prefix):
def execute(cls, mesh: io.Mesh.MeshDict, filename_prefix):
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, folder_paths.get_output_directory())
results = []

Expand All @@ -564,9 +553,9 @@ def execute(cls, mesh, filename_prefix):
for x in cls.hidden.extra_pnginfo:
metadata[x] = json.dumps(cls.hidden.extra_pnginfo[x])

for i in range(mesh.vertices.shape[0]):
for i in range(mesh["vertices"].shape[0]):
f = f"{filename}_{counter:05}_.glb"
save_glb(mesh.vertices[i], mesh.faces[i], os.path.join(full_output_folder, f), metadata)
save_glb(mesh["vertices"][i], mesh["faces"][i], os.path.join(full_output_folder, f), metadata)
results.append({
"filename": f,
"subfolder": subfolder,
Expand All @@ -590,14 +579,17 @@ def define_schema(cls):
io.Int.Input("octree_resolution", default=256, min=16, max=512)
],
outputs=[
io.Voxel.Output()
io.Voxel.Output(),
]
)

@classmethod
def execute(cls, vae, samples, num_chunks, octree_resolution):
voxels = VOXEL(vae.decode(samples["samples"], vae_options={"num_chunks": num_chunks, "octree_resolution": octree_resolution}))
return io.NodeOutput(voxels)
return io.NodeOutput(
io.Voxel.VoxelDict(
data=vae.decode(samples["samples"], vae_options={"num_chunks": num_chunks, "octree_resolution": octree_resolution})
)
)


class VoxelToMesh(io.ComfyNode):
Expand All @@ -612,12 +604,12 @@ def define_schema(cls):
io.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01)
],
outputs=[
io.Mesh.Output()
io.Mesh.Output(),
]
)

@classmethod
def execute(cls, voxel, algorithm, threshold):
def execute(cls, voxel: io.Voxel.VoxelDict, algorithm, threshold):
vertices = []
faces = []

Expand All @@ -626,12 +618,12 @@ def execute(cls, voxel, algorithm, threshold):
elif algorithm == "surface net":
mesh_function = voxel_to_mesh_surfnet

for x in voxel.data:
for x in voxel["data"]:
v, f = mesh_function(x, threshold=threshold, device=None)
vertices.append(v)
faces.append(f)

return io.NodeOutput(MESH(torch.stack(vertices), torch.stack(faces)))
return io.NodeOutput(io.Mesh.MeshDict(vertices=torch.stack(vertices), faces=torch.stack(faces)))


class VoxelToMeshBasic(io.ComfyNode):
Expand All @@ -645,20 +637,20 @@ def define_schema(cls):
io.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01)
],
outputs=[
io.Mesh.Output()
io.Mesh.Output(),
]
)

@classmethod
def execute(cls, voxel, threshold):
def execute(cls, voxel: io.Voxel.VoxelDict, threshold):
vertices = []
faces = []
for x in voxel.data:
for x in voxel["data"]:
v, f = voxel_to_mesh(x, threshold=threshold, device=None)
vertices.append(v)
faces.append(f)

return io.NodeOutput(MESH(torch.stack(vertices), torch.stack(faces)))
return io.NodeOutput(io.Mesh.MeshDict(vertices=torch.stack(vertices), faces=torch.stack(faces)))


NODES_LIST: list[type[io.ComfyNode]] = [
Expand Down