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Update Hidiffusion_node.py

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fix bug and add new model
This commit is contained in:
smthemex
2024-05-28 16:04:24 +08:00
committed by GitHub
parent 89740ec832
commit a9c72115a6
1 changed files with 11 additions and 16 deletions
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Hidiffusion_node.py
+11 -16
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@@ -17,7 +17,7 @@ from diffusers import (StableDiffusionXLPipeline, DiffusionPipeline, DDIMSchedul
from .hidiffusion.hidiffusion import apply_hidiffusion
import folder_paths
from safetensors.torch import load_file
import yaml
dir_path = os.path.dirname(os.path.abspath(__file__))
path_dir = os.path.dirname(dir_path)
@@ -66,18 +66,13 @@ scheduler_list = [
"TCD"
]
sdxl_lightning_list = [
"sdxl_lightning_1step_unet_x0.safetensors",
"sdxl_lightning_2step_unet.safetensors",
"sdxl_lightning_4step_unet.safetensors",
"sdxl_lightning_8step_unet.safetensors"
"Hyper-SDXL-1step-Unet.safetensors",
"lcm-sdxl-base-1.0.safetensors",
]
normal_model_list = ["stable-diffusion-2-1-base", "stable-diffusion-v1-5", "playground-v2.5-1024px-aesthetic",
"Ghibli-Diffusion", "playground-v2-1024px-aesthetic"]
fs = open(os.path.join(dir_path,"model.yaml"),encoding="UTF-8")
datas = yaml.load(fs,Loader=yaml.FullLoader) #添加后就不警告了
normal_model_list = datas["surport_model"]
sdxl_lightning_list =datas["lightning_unet"]
controlnet_suport = datas["surport_controlnet"]
xl_model_support =datas["sdxl_model"]
def get_sheduler(name):
scheduler = False
@@ -194,7 +189,7 @@ class Hi_Text2Img:
"mosaic, artifacts, bad limbs"}),
"repo_id": ("STRING", {"forceInput": True}),
"scheduler": (scheduler_list,),
"unet_model": ([] + folder_paths.get_filename_list("unet"),),
"unet_model": (["none"] + folder_paths.get_filename_list("unet"),),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 50, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 7.5, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01}),
@@ -213,7 +208,7 @@ class Hi_Text2Img:
steps, cfg, eta, height, width):
model_type = repo_id.rsplit("/")[-1]
scheduler_used = get_sheduler(scheduler)
if model_type == "stable-diffusion-xl-base-1.0":
if model_type in xl_model_support:
if unet_model in sdxl_lightning_list:
light_path = os.path.join(file_path, "models", "unet", unet_model)
ckpt = get_instance_path(light_path)
@@ -435,7 +430,7 @@ class Hi_Control2Img:
"deformed, close up, weird colors, watermark"}),
"scheduler": (scheduler_list,),
"unet_model": ([] + folder_paths.get_filename_list("unet"),),
"unet_model": (["none"] + folder_paths.get_filename_list("unet"),),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 12.5, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01}),
@@ -471,7 +466,7 @@ class Hi_Control2Img:
mask_image = tensor_to_image(mask_image)
model_type = repo_id.rsplit("/")[-1]
control_model_type = controlnet_repo_id.rsplit("/")[-1]
controlnet_suport = ["controlnet-canny-sdxl-1.0", "MistoLine"]
if control_model_type == "stable-diffusion-xl-1.0-inpainting-0.1":
output_img = self.inpainting_gener(image, repo_id, controlnet_repo_id, prompt, negative_prompt, scheduler,