wangbo/ComfyUI
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More cleanup

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This commit is contained in:
kijai 2026-07-02 15:28:51 +03:00
parent be67e2366d
commit 419e726061
2 changed files with 8 additions and 10 deletions
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4
comfy_extras/nodes_mesh_postprocess.py
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@ -2278,8 +2278,8 @@ class RemeshMesh(IO.ComfyNode):
# mode-specific sub-widgets (absent → defaults)
qef = bool(sign_mode.get("qef", True))
manifold = bool(sign_mode.get("manifold", False))
drop_inverted_components = bool(sign_mode.get("drop_inverted_components", True))
drop_enclosed_components = bool(sign_mode.get("drop_enclosed_components", True))
drop_inverted_components = bool(sign_mode.get("drop_inverted_components", False))
drop_enclosed_components = bool(sign_mode.get("drop_enclosed_components", False))
# ComfyUI passes meshes on CPU (remesh far faster on GPU); compute on device, return on original.
compute_device = comfy.model_management.get_torch_device()

14
comfy_extras/nodes_trellis2.py
View File

@ -434,21 +434,19 @@ def _dinov3_encode(model, image_bchw, image_size, want_patches=False):
return {"tokens": tokens[:, :1 + n_reg], "patches_2d": _dinov3_patches_to_2d(tokens, image_size)}
def run_conditioning(model, cropped_pil_img, include_1024=True):
def run_conditioning(model, cropped_pil_img):
device = comfy.model_management.intermediate_device()
img_np = np.array(cropped_pil_img).astype(np.float32) / 255.0
image_bchw = torch.from_numpy(img_np).permute(2, 0, 1).unsqueeze(0).contiguous()
cond_512 = _dinov3_encode(model, image_bchw, 512)
conditioning = {
cond_1024 = _dinov3_encode(model, image_bchw, 1024)
return {
"cond_512": cond_512.to(device),
"neg_cond": torch.zeros_like(cond_512).to(device),
"cond_1024": cond_1024.to(device),
}
if include_1024:
cond_1024 = _dinov3_encode(model, image_bchw, 1024)
conditioning["cond_1024"] = cond_1024.to(device)
return conditioning
class Trellis2Conditioning(IO.ComfyNode):
@classmethod
@ -581,7 +579,7 @@ class Trellis2Conditioning(IO.ComfyNode):
cropped_pil = Image.fromarray(rgba_composite, mode="RGBA")
# Convert to RGB to ensure the CLIP/DINO model receives a 3-channel image
item_conditioning = run_conditioning(clip_vision_model, cropped_pil.convert("RGB"), include_1024=True)
item_conditioning = run_conditioning(clip_vision_model, cropped_pil.convert("RGB"))
cond_512_list.append(item_conditioning["cond_512"])
cond_1024_list.append(item_conditioning["cond_1024"])
@ -868,7 +866,7 @@ class Pixal3DConditioning(IO.ComfyNode):
@classmethod
def execute(cls, clip_vision_model, image, mask, camera_angle_x) -> IO.NodeOutput:
naf_model = getattr(clip_vision_model, "naf", None)
naf_model = clip_vision_model.naf
if image.ndim == 3:
image = image.unsqueeze(0)
if mask.ndim == 2: