Update app.py

app.py

@@ -6,6 +6,7 @@ import gradio as gr
 import torch
 from einops import rearrange
 from PIL import Image
+from transformers import pipeline
 
 from flux.cli import SamplingOptions
 from flux.sampling import denoise, get_noise, get_schedule, prepare, unpack
@@ -13,6 +14,8 @@ from flux.util import load_ae, load_clip, load_flow_model, load_t5
 from pulid.pipeline_flux import PuLIDPipeline
 from pulid.utils import resize_numpy_image_long
 
+# 한영 번역 모델 로드
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
 
 def get_models(name: str, device: torch.device, offload: bool):
     t5 = load_t5(device, max_length=128)
@@ -57,6 +60,11 @@ def generate_image(
         timestep_to_start_cfg=1,
         max_sequence_length=128,
 ):
+    # 한글 프롬프트를 영어로 번역
+    if any('\u3131' <= c <= '\u318E' or '\uAC00' <= c <= '\uD7A3' for c in prompt):
+        translated = translator(prompt)[0]['translation_text']
+        prompt = translated
+
     flux_generator.t5.max_length = max_sequence_length
 
     seed = int(seed)
@@ -157,31 +165,33 @@ def create_demo(args, model_name: str, device: str = "cuda" if torch.cuda.is_ava
                 offload: bool = False):
     
     with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
+        gr.Markdown("# 제목")
+        gr.Markdown("## 설명")
         
         with gr.Row():
             with gr.Column():
-                prompt = gr.Textbox(label="Prompt", value="portrait, color, cinematic")
-                id_image = gr.Image(label="ID Image")
-                generate_btn = gr.Button("Generate")
+                prompt = gr.Textbox(label="프롬프트", value="초상화, 색감, 영화적")
+                id_image = gr.Image(label="ID 이미지", source="webcam", type="numpy")
+                generate_btn = gr.Button("생성")
                 
             with gr.Column():
-                output_image = gr.Image(label="Generated Image")
+                output_image = gr.Image(label="생성된 이미지")
 
         with gr.Row():
             with gr.Column():
-                gr.Markdown("## Examples")
+                gr.Markdown("## 예시")
                 
                 all_examples = [
-                    ['a woman holding sign with glowing green text \"PuLID for FLUX\"', 'example_inputs/liuyifei.png'],
-                    ['portrait, side view', 'example_inputs/liuyifei.png'],
-                    ['white-haired woman with vr technology atmosphere', 'example_inputs/liuyifei.png'],
-                    ['a young child is eating Icecream', 'example_inputs/liuyifei.png'],
-                    ['a man is holding a sign with text \"PuLID for FLUX\", winter, snowing', 'example_inputs/pengwei.jpg'],
-                    ['portrait, candle light', 'example_inputs/pengwei.jpg'],
-                    ['profile shot dark photo of a 25-year-old male with smoke', 'example_inputs/pengwei.jpg'],
-                    ['American Comics, 1boy', 'example_inputs/pengwei.jpg'],
-                    ['portrait, pixar', 'example_inputs/pengwei.jpg'],
-                    ['portrait, made of ice sculpture', 'example_inputs/lecun.jpg'],
+                    ['여자가 \"PuLID for FLUX\"라고 쓰인 빛나는 녹색 표지판을 들고 있다', 'example_inputs/liuyifei.png'],
+                    ['옆모습 초상화', 'example_inputs/liuyifei.png'],
+                    ['VR 기술 분위기의 흰 머리 여성', 'example_inputs/liuyifei.png'],
+                    ['어린 아이가 아이스크림을 먹고 있다', 'example_inputs/liuyifei.png'],
+                    ['남자가 \"PuLID for FLUX\"라고 쓰인 표지판을 들고 있다, 겨울, 눈 내림, 산 정상', 'example_inputs/pengwei.jpg'],
+                    ['초상화, 촛불 조명', 'example_inputs/pengwei.jpg'],
+                    ['25세 남성의 어두운 프로필 사진, 입에서 연기가 나오고 있음', 'example_inputs/pengwei.jpg'],
+                    ['미국 만화 스타일, 소년 1명', 'example_inputs/pengwei.jpg'],
+                    ['초상화, 픽사 스타일', 'example_inputs/pengwei.jpg'],
+                    ['초상화, 얼음 조각상', 'example_inputs/lecun.jpg'],
                 ]
 
                 example_images = [example[1] for example in all_examples]
@@ -189,7 +199,7 @@ def create_demo(args, model_name: str, device: str = "cuda" if torch.cuda.is_ava
 
                 gallery = gr.Gallery(
                     value=list(zip(example_images, example_captions)),
-                    label="Example Gallery",
+                    label="예시 갤러리",
                     show_label=False,
                     elem_id="gallery",
                     columns=5,
@@ -219,7 +229,7 @@ def create_demo(args, model_name: str, device: str = "cuda" if torch.cuda.is_ava
                 prompt, 
                 id_image, 
                 gr.Slider(0.0, 3.0, 1, step=0.05, visible=False),  # id_weight
-                gr.Textbox("bad quality, worst quality, text, signature, watermark, extra limbs", visible=False),  # neg_prompt
+                gr.Textbox("저품질, 최악의 품질, 텍스트, 서명, 워터마크, 여분의 팔다리", visible=False),  # neg_prompt
                 gr.Slider(1.0, 10.0, 1, step=0.1, visible=False),  # true_cfg
                 gr.Slider(0, 20, 1, step=1, visible=False),  # timestep_to_start_cfg
                 gr.Slider(128, 512, 128, step=128, visible=False),  # max_sequence_length
@@ -234,13 +244,13 @@ if __name__ == "__main__":
 
     parser = argparse.ArgumentParser(description="PuLID for FLUX.1-dev")
     parser.add_argument("--name", type=str, default="flux-dev", choices=list('flux-dev'),
-                        help="currently only support flux-dev")
+                        help="현재는 flux-dev만 지원합니다")
     parser.add_argument("--device", type=str, default="cuda" if torch.cuda.is_available() else "cpu",
-                        help="Device to use")
-    parser.add_argument("--offload", action="store_true", help="Offload model to CPU when not in use")
-    parser.add_argument("--port", type=int, default=8080, help="Port to use")
-    parser.add_argument("--dev", action='store_true', help="Development mode")
-    parser.add_argument("--pretrained_model", type=str, help='for development')
+                        help="사용할 디바이스")
+    parser.add_argument("--offload", action="store_true", help="사용하지 않을 때 모델을 CPU로 옮깁니다")
+    parser.add_argument("--port", type=int, default=8080, help="사용할 포트")
+    parser.add_argument("--dev", action='store_true', help="개발 모드")
+    parser.add_argument("--pretrained_model", type=str, help='개발용')
     args = parser.parse_args()
 
     import huggingface_hub