nodes/chflame163-ComfyUI_LayerStyle
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fix bugs of QWenImage2Prompt node

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chflame163
2024-07-18 12:08:38 +08:00
parent 8bf41601df
commit f58f5b8961
2 changed files with 18 additions and 13 deletions
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py/Qwen_image2prompt.py
+17 -12
View File
@@ -7,10 +7,6 @@ from torchvision.transforms import ToPILImage
from huggingface_hub import snapshot_download
import folder_paths
# Define the directory for saving files related to uform-gen2-qwen
# files_for_uform_gen2_qwen = Path(folder_paths.folder_names_and_paths["LLavacheckpoints"][0][0]) / "files_for_uform_gen2_qwen"
files_for_uform_gen2_qwen = Path(os.path.join(folder_paths.models_dir, "LLavacheckpoints", "files_for_uform_gen2_qwen"))
files_for_uform_gen2_qwen.mkdir(parents=True, exist_ok=True) # Ensure the directory exists
class StopOnTokens(StoppingCriteria):
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool:
@@ -22,11 +18,12 @@ class StopOnTokens(StoppingCriteria):
class UformGen2QwenChat:
def __init__(self):
self.model_path = snapshot_download("unum-cloud/uform-gen2-qwen-500m",
local_dir=files_for_uform_gen2_qwen,
force_download=False, # Set to True if you always want to download, regardless of local copy
local_files_only=False, # Set to False to allow downloading if not available locally
local_dir_use_symlinks="auto") # or set to True/False based on your symlink preference
# self.model_path = snapshot_download("unum-cloud/uform-gen2-qwen-500m",
# local_dir=files_for_uform_gen2_qwen,
# force_download=False, # Set to True if you always want to download, regardless of local copy
# local_files_only=True, # Set to False to allow downloading if not available locally
# local_dir_use_symlinks="auto") # or set to True/False based on your symlink preference
self.model_path = Path(os.path.join(folder_paths.models_dir, "LLavacheckpoints", "files_for_uform_gen2_qwen"))
self.device = "cuda:0" if torch.cuda.is_available() else "cpu"
self.model = AutoModel.from_pretrained(self.model_path, trust_remote_code=True).to(self.device)
self.processor = AutoProcessor.from_pretrained(self.model_path, trust_remote_code=True)
@@ -79,8 +76,6 @@ class UformGen2QwenChat:
# Example of integrating UformGen2QwenChat into a node-like structure
class QWenImage2Prompt:
def __init__(self):
self.chat_model = UformGen2QwenChat()
@classmethod
def INPUT_TYPES(cls):
@@ -97,12 +92,22 @@ class QWenImage2Prompt:
CATEGORY = '😺dzNodes/LayerUtility/Prompt'
def uform_gen2_qwen_chat(self, image, question):
chat_model = UformGen2QwenChat()
history = [] # Example empty history
pil_image = ToPILImage()(image[0].permute(2, 0, 1))
temp_path = files_for_uform_gen2_qwen / "temp.png"
pil_image.save(temp_path)
response = self.chat_model.chat_response(question, history, temp_path)
response = chat_model.chat_response(question, history, temp_path)
# Cleanup
del chat_model
import gc
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
return (response.split("assistant\n", 1)[1], )
NODE_CLASS_MAPPINGS = {
pyproject.toml
+1 -1
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@@ -1,7 +1,7 @@
[project]
name = "comfyui_layerstyle"
description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
version = "1.0.13"
version = "1.0.14"
license = "MIT"
dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "opencv-contrib-python", "pymatting", "segment_anything", "timm", "addict", "yapf", "colour-science", "wget", "mediapipe", "loguru", "typer_config", "fastapi", "rich", "google-generativeai", "diffusers", "omegaconf", "tqdm", "transformers", "kornia", "image-reward", "ultralytics", "blend_modes", "blind-watermark", "qrcode", "pyzbar", "psd-tools"]