Update stable_makeup_nodes.py

This commit is contained in:
smthemex
2025-04-05 17:55:24 +08:00
committed by GitHub
parent aa6423bc2e
commit c9fded0fd6
+7 -7
View File
@@ -4,9 +4,7 @@
import folder_paths
import os
import torch
import diffusers
dif_version = str(diffusers.__version__)
dif_version_int = int(dif_version.split(".")[1])
from diffusers import (DDIMScheduler, ControlNetModel,
KDPM2AncestralDiscreteScheduler, LMSDiscreteScheduler, DPMSolverMultistepScheduler,
@@ -116,7 +114,7 @@ class StableMakeup_LoadModel:
return {
"required": {
"ckpt_name": (folder_paths.get_filename_list("checkpoints"),),
"clip":("STRING", {"default": "openai/clip-vit-large-patch14"}),
"clip":(folder_paths.get_filename_list("clip"),),
"lora":(["none"]+folder_paths.get_filename_list("loras"),),
"lora_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.1, "round": 0.01}),
"lora_trigger_words":("STRING", {"default": "best"}),
@@ -130,6 +128,7 @@ class StableMakeup_LoadModel:
CATEGORY = "Stable_Makeup"
def main_loader(self,ckpt_name,clip,lora,lora_scale,lora_trigger_words,scheduler):
clip=folder_paths.get_full_path("clip", clip)
ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
scheduler_used = get_sheduler(scheduler)
makeup_encoder_path = os.path.join(weigths_current_path,"pytorch_model.bin")
@@ -137,10 +136,10 @@ class StableMakeup_LoadModel:
pose_encoder_path = os.path.join(weigths_current_path,"pytorch_model_2.bin")
original_config_file=os.path.join(folder_paths.models_dir,"configs","v1-inference.yaml")
sd15_config=os.path.join(makeup_current_path,"sd15_config")
if dif_version_int >= 28:
try:
pipe = StableDiffusionPipeline.from_single_file(
ckpt_path,config=sd15_config, original_config=original_config_file)
else:
except:
pipe = StableDiffusionPipeline.from_single_file(
ckpt_path, config=sd15_config,original_config_file=original_config_file)
pipe.to("cuda")
@@ -149,7 +148,8 @@ class StableMakeup_LoadModel:
text_encoder = pipe.text_encoder
id_encoder = ControlNetModel.from_unet(Unet)
pose_encoder = ControlNetModel.from_unet(Unet)
makeup_encoder = detail_encoder(Unet, clip, "cuda", dtype=torch.float32)
repo=os.path.join(makeup_current_path,"clip")
makeup_encoder = detail_encoder(Unet, clip,repo, "cuda", dtype=torch.float32)
makeup_state_dict = torch.load(makeup_encoder_path)
id_state_dict = torch.load(id_encoder_path)