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Add custom nodes, Civitai loras (LFS), and vast.ai setup script
Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-09 00:56:42 +00:00

32 lines
1.1 KiB
Python

from PIL import Image
from usdu_utils import tensor_to_pil, pil_to_tensor
from comfy_extras.nodes_upscale_model import ImageUpscaleWithModel
from modules import shared
if (not hasattr(Image, 'Resampling')): # For older versions of Pillow
Image.Resampling = Image
class Upscaler:
def upscale(self, img: Image, scale, selected_model: str = None):
if scale == 1.0:
return img
if (shared.actual_upscaler is None):
return img.resize((img.width * scale, img.height * scale), Image.Resampling.LANCZOS)
if "execute" in dir(ImageUpscaleWithModel):
# V3 schema: https://github.com/comfyanonymous/ComfyUI/pull/10149
(upscaled,) = ImageUpscaleWithModel.execute(shared.actual_upscaler, shared.batch_as_tensor)
else:
(upscaled,) = ImageUpscaleWithModel().upscale(shared.actual_upscaler, shared.batch_as_tensor)
shared.batch = [tensor_to_pil(upscaled, i) for i in range(len(upscaled))]
return shared.batch[0]
class UpscalerData:
name = ""
data_path = ""
def __init__(self):
self.scaler = Upscaler()