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updates for naming

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This commit is contained in:
Yousef Rafat 2026-05-14 15:37:02 +03:00
parent f78a20271a
commit e94cad71ca
1 changed files with 10 additions and 6 deletions
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16
comfy_extras/nodes_trellis2.py
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@ -403,8 +403,10 @@ class Trellis2UpsampleCascade(IO.ComfyNode):
return IO.Schema( return IO.Schema(
node_id="Trellis2UpsampleCascade", node_id="Trellis2UpsampleCascade",
category="latent/3d", category="latent/3d",
display_name="Trellis2 Upsample Cascade",
description="Upsamples low-resolution Trellis2 shape latents into higher resolution coordinates while respecting the maximum token budget.",
inputs=[ inputs=[
IO.Latent.Input("shape_latent_512"), IO.Latent.Input("shape_latent"),
IO.Vae.Input("vae"), IO.Vae.Input("vae"),
IO.Combo.Input("target_resolution", options=["1024", "1536"], default="1024"), IO.Combo.Input("target_resolution", options=["1024", "1536"], default="1024"),
IO.Int.Input("max_tokens", default=49152, min=1024, max=100000) IO.Int.Input("max_tokens", default=49152, min=1024, max=100000)
@ -415,7 +417,8 @@ class Trellis2UpsampleCascade(IO.ComfyNode):
) )
@classmethod @classmethod
def execute(cls, shape_latent_512, vae, target_resolution, max_tokens): def execute(cls, shape_latent, vae, target_resolution, max_tokens):
shape_latent_512 = shape_latent
device = comfy.model_management.get_torch_device() device = comfy.model_management.get_torch_device()
prepare_trellis_vae_for_decode(vae, shape_latent_512["samples"].shape) prepare_trellis_vae_for_decode(vae, shape_latent_512["samples"].shape)
@ -1329,7 +1332,8 @@ class PostProcessMesh(IO.ComfyNode):
category="latent/3d", category="latent/3d",
inputs=[ inputs=[
IO.Mesh.Input("mesh"), IO.Mesh.Input("mesh"),
IO.Int.Input("simplify", default=1_000_000, min=0, max=50_000_000), IO.Int.Input("target_face_count", default=1_000_000, min=0, max=50_000_000,
tooltip="Target maximum number of faces after mesh simplification. Set to 0 to disable simplification."),
IO.Float.Input("fill_holes_perimeter", default=0.03, min=0.0, step=0.0001) IO.Float.Input("fill_holes_perimeter", default=0.03, min=0.0, step=0.0001)
], ],
outputs=[ outputs=[
@ -1338,7 +1342,7 @@ class PostProcessMesh(IO.ComfyNode):
) )
@classmethod @classmethod
def execute(cls, mesh, simplify, fill_holes_perimeter): def execute(cls, mesh, target_face_count, fill_holes_perimeter):
# input should be comfy.NestedTensor # input should be comfy.NestedTensor
mesh = copy.deepcopy(mesh) mesh = copy.deepcopy(mesh)
@ -1346,8 +1350,8 @@ class PostProcessMesh(IO.ComfyNode):
if fill_holes_perimeter > 0: if fill_holes_perimeter > 0:
v, f = fill_holes_fn(v, f, max_perimeter=fill_holes_perimeter) v, f = fill_holes_fn(v, f, max_perimeter=fill_holes_perimeter)
if simplify > 0 and f.shape[0] > simplify: if target_face_count > 0 and f.shape[0] > target_face_count:
v, f, c = simplify_fn(v, f, colors=c, target=simplify) v, f, c = simplify_fn(v, f, colors=c, target=target_face_count)
v, f = make_double_sided(v, f) v, f = make_double_sided(v, f)
return v, f, c return v, f, c