Update app.py

app.py

@@ -11,6 +11,7 @@ from PIL import Image
 import cv2
 import torch
 import random
+from transformers import pipeline
 
 os.system("pip install -e ./controlnet_aux")
 
@@ -25,6 +26,14 @@ login(token=hf_token)
 
 MAX_SEED = np.iinfo(np.int32).max
 
+# 번역기 설정
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
+
+def translate_to_english(text):
+    if any('\uAC00' <= char <= '\uD7A3' for char in text):
+        return translator(text, max_length=512)[0]['translation_text']
+    return text
+
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
@@ -57,8 +66,8 @@ controlnet = FluxMultiControlNetModel([controlnet])
 pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
 pipe.to("cuda")
 
-mode_mapping = {"canny":0, "tile":1, "depth":2, "blur":3, "openpose":4, "gray":5, "low quality": 6}
-strength_mapping = {"canny":0.65, "tile":0.45, "depth":0.55, "blur":0.45, "openpose":0.55, "gray":0.45, "low quality": 0.4}
+mode_mapping = {"캐니":0, "타일":1, "깊이":2, "블러":3, "오픈포즈":4, "그레이스케일":5, "저품질": 6}
+strength_mapping = {"캐니":0.65, "타일":0.45, "깊이":0.55, "블러":0.45, "오픈포즈":0.55, "그레이스케일":0.45, "저품질": 0.4}
 
 canny = CannyDetector()
 open_pose = OpenposeDetector.from_pretrained("lllyasviel/Annotators")
@@ -147,23 +156,24 @@ def resize_img(input_image, max_side=768, min_side=512, size=None,
 def infer(cond_in, image_in, prompt, inference_steps, guidance_scale, control_mode, control_strength, seed, progress=gr.Progress(track_tqdm=True)):
         
     control_mode_num = mode_mapping[control_mode]
+    prompt = translate_to_english(prompt)
     
     if cond_in is None:
         if image_in is not None:
             image_in = resize_img(load_image(image_in))
-            if control_mode == "canny":
+            if control_mode == "캐니":
                 control_image = extract_canny(image_in)
-            elif control_mode == "depth":
+            elif control_mode == "깊이":
                 control_image = extract_depth(image_in)
-            elif control_mode == "openpose":
+            elif control_mode == "오픈포즈":
                 control_image = extract_openpose(image_in)
-            elif control_mode == "blur":
+            elif control_mode == "블러":
                 control_image = apply_gaussian_blur(image_in)
-            elif control_mode == "low quality":
+            elif control_mode == "저품질":
                 control_image = add_gaussian_noise(image_in)
-            elif control_mode == "gray":
+            elif control_mode == "그레이스케일":
                 control_image = convert_to_grayscale(image_in)
-            elif control_mode == "tile":
+            elif control_mode == "타일":
                 control_image = tile(image_in)
     else:
         control_image = resize_img(load_image(cond_in))
@@ -202,19 +212,19 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
                 with gr.Column():
                     
                     with gr.Row(equal_height=True):
-                        cond_in = gr.Image(label="Upload a processed control image", sources=["upload"], type="filepath")
-                        image_in = gr.Image(label="Extract condition from a reference image (Optional)", sources=["upload"], type="filepath")
+                        cond_in = gr.Image(label="처리된 컨트롤 이미지 업로드", sources=["upload"], type="filepath")
+                        image_in = gr.Image(label="참조 이미지에서 조건 추출 (선택사항)", sources=["upload"], type="filepath")
                     
-                    prompt = gr.Textbox(label="Prompt", value="best quality")
+                    prompt = gr.Textbox(label="프롬프트", value="최고 품질")
                     
-                    with gr.Accordion("Controlnet"):
+                    with gr.Accordion("컨트롤넷"):
                         control_mode = gr.Radio(
-                            ["canny", "depth", "openpose", "gray", "blur", "tile", "low quality"], label="Mode", value="gray",
-                            info="select the control mode, one for all"
+                            ["캐니", "깊이", "오픈포즈", "그레이스케일", "블러", "타일", "저품질"], label="모드", value="그레이스케일",
+                            info="컨트롤 모드 선택, 모든 이미지에 적용됩니다"
                         )
                         
                         control_strength = gr.Slider(
-                            label="control strength",
+                            label="컨트롤 강도",
                             minimum=0,
                             maximum=1.0,
                             step=0.05,
@@ -222,25 +232,25 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
                         )
                     
                     seed = gr.Slider(
-                        label="Seed",
+                        label="시드",
                         minimum=0,
                         maximum=MAX_SEED,
                         step=1,
                         value=42,
                     )
-                    randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                    randomize_seed = gr.Checkbox(label="시드 무작위화", value=True)
                     
-                    with gr.Accordion("Advanced settings", open=False):
+                    with gr.Accordion("고급 설정", open=False):
                         with gr.Column():
                             with gr.Row():
-                                inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=24)
-                                guidance_scale = gr.Slider(label="Guidance scale", minimum=1.0, maximum=10.0, step=0.1, value=3.5)
+                                inference_steps = gr.Slider(label="추론 단계", minimum=1, maximum=50, step=1, value=24)
+                                guidance_scale = gr.Slider(label="가이던스 스케일", minimum=1.0, maximum=10.0, step=0.1, value=3.5)
                     
-                    submit_btn = gr.Button("Submit")
+                    submit_btn = gr.Button("제출")
                     
                 with gr.Column():
-                    result = gr.Image(label="Result")
-                    processed_cond = gr.Image(label="Preprocessed Cond")
+                    result = gr.Image(label="결과")
+                    processed_cond = gr.Image(label="전처리된 조건")
 
     submit_btn.click(
         fn=randomize_seed_fn,