Update app.py

app.py

@@ -14,19 +14,23 @@ from transformers import pipeline
 import gradio as gr
 import os
 from huggingface_hub import login
+import random
+
+# 상수 정의
+MAX_SEED = 2**32 - 1
 
-# HF_TOKEN 설정 직후에 추가
+# Hugging Face 토큰 설정 및 로그인
 HF_TOKEN = os.getenv("HF_TOKEN")
 if HF_TOKEN is None:
     raise ValueError("Please set the HF_TOKEN environment variable")
 login(token=HF_TOKEN)
 
-# 모델 설정
+# 모델 설정 (한 번만 선언)
 base_model = "black-forest-labs/FLUX.1-dev"
 model_lora_repo = "Motas/Flux_Fashion_Photography_Style"
 clothes_lora_repo = "prithivMLmods/Canopus-Clothing-Flux-LoRA"
 
-# FLUX 모델 초기화 (한 번만)
+# FLUX 모델 초기화 (한 번만 초기화)
 fashion_pipe = DiffusionPipeline.from_pretrained(
     base_model,
     torch_dtype=torch.bfloat16,
@@ -34,16 +38,13 @@ fashion_pipe = DiffusionPipeline.from_pretrained(
 )
 fashion_pipe.to("cuda")
 
-# 번역기 초기화
+# 번역기 초기화 (한 번만)
 translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
 
-# 상수 정의 추가
-import random
-MAX_SEED = 2**32 - 1
-
-# Download checkpoints
+# Leffa 체크포인트 다운로드
 snapshot_download(repo_id="franciszzj/Leffa", local_dir="./ckpts")
 
+# Leffa 관련 모델 초기화
 mask_predictor = AutoMasker(
     densepose_path="./ckpts/densepose",
     schp_path="./ckpts/schp",
@@ -66,16 +67,6 @@ pt_model = LeffaModel(
 )
 pt_inference = LeffaInference(model=pt_model)
 
-
-    
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
-base_model = "black-forest-labs/FLUX.1-dev"
-model_lora_repo = "Motas/Flux_Fashion_Photography_Style"
-clothes_lora_repo = "prithivMLmods/Canopus-Clothing-Flux-LoRA"
-
-fashion_pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
-fashion_pipe.to("cuda")
-
 def contains_korean(text):
     return any(ord('가') <= ord(char) <= ord('힣') for char in text)