Update app.py

app.py

@@ -9,7 +9,7 @@ from diffusers import DiffusionPipeline
 from custom_pipeline import FLUXPipelineWithIntermediateOutputs
 from transformers import pipeline
 
-# 번역 모델 로드
+# Translation model loading
 translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
 
 # Constants
@@ -26,18 +26,18 @@ pipe = FLUXPipelineWithIntermediateOutputs.from_pretrained(
 ).to("cuda")
 torch.cuda.empty_cache()
 
-# 한글 메뉴 이름 dictionary
-korean_labels = {
-    "Generated Image": "생성된 이미지",
-    "Prompt": "프롬프트",
-    "Enhance Image": "이미지 향상",
-    "Advanced Options": "고급 옵션",
-    "Seed": "시드",
-    "Randomize Seed": "시드 무작위화",
-    "Width": "너비",
-    "Height": "높이",
-    "Inference Steps": "추론 단계",
-    "Inspiration Gallery": "영감 갤러리"
+# Menu labels dictionary
+english_labels = {
+    "Generated Image": "Generated Image",
+    "Prompt": "Prompt",
+    "Enhance Image": "Enhance Image",
+    "Advanced Options": "Advanced Options",
+    "Seed": "Seed",
+    "Randomize Seed": "Randomize Seed",
+    "Width": "Width",
+    "Height": "Height",
+    "Inference Steps": "Inference Steps",
+    "Inspiration Gallery": "Inspiration Gallery"
 }
 
 def translate_if_korean(text):
@@ -66,17 +66,17 @@ def generate_image(prompt, seed=42, width=DEFAULT_WIDTH, height=DEFAULT_HEIGHT,
             height=height,
             generator=generator
         ): 
-        latency = f"처리 시간: {(time.time()-start_time):.2f} 초"    
+        latency = f"Processing Time: {(time.time()-start_time):.2f} seconds"    
         yield img, seed, latency
 
-# Example prompts
+# Example prompts (keeping one Korean example)
 examples = [
-    "달에서 알에서 부화하는 작은 우주 비행사",
-    "안녕하세요 세상이라고 쓰인 표지판을 들고 있는 고양이",
-    "비너 슈니첼의 애니메이션 일러스트레이션",
-    "하늘을 나는 자동차와 네온 불빛이 있는 미래적인 도시 풍경",
-    "긴 갈색 웨이브 머리를 올려 묶고 안경을 쓴 젊은 여성의 사진. 그녀는 흰 피부에 눈과 입술을 강조한 은은한 화장을 했습니다. 그녀는 검은색 상의를 입었습니다. 배경은 도시 건물 외관으로 보이며, 햇빛이 그녀의 얼굴에 따뜻한 빛을 비추고 있습니다.",
-    "스티브 잡스를 스타워즈 영화 캐릭터로 상상해보세요"
+    "비너 슈니첼의 애니메이션 일러스트레이션",  # Keeping this Korean example
+    "A steampunk owl wearing Victorian-era clothing and reading a mechanical book",
+    "A floating island made of books with waterfalls of knowledge cascading down",
+    "A bioluminescent forest where mushrooms glow like neon signs in a cyberpunk city",
+    "An ancient temple being reclaimed by nature, with robots performing archaeology",
+    "A cosmic coffee shop where baristas are constellations serving drinks made of stardust"
 ]
 
 css = """
@@ -91,30 +91,30 @@ with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css) as demo:
 
         with gr.Row():
             with gr.Column(scale=3):
-                result = gr.Image(label=korean_labels["Generated Image"], show_label=False, interactive=False)
+                result = gr.Image(label=english_labels["Generated Image"], show_label=False, interactive=False)
             with gr.Column(scale=1):
                 prompt = gr.Text(
-                    label=korean_labels["Prompt"],
-                    placeholder="생성하고 싶은 이미지를 설명하세요...",
+                    label=english_labels["Prompt"],
+                    placeholder="Describe the image you want to generate...",
                     lines=3,
                     show_label=False,
                     container=False,
                 )
-                enhanceBtn = gr.Button(f"🚀 {korean_labels['Enhance Image']}")
+                enhanceBtn = gr.Button(f"🚀 {english_labels['Enhance Image']}")
 
-                with gr.Column(korean_labels["Advanced Options"]):
+                with gr.Column(english_labels["Advanced Options"]):
                     with gr.Row():
                         latency = gr.Text(show_label=False)
                     with gr.Row():
-                        seed = gr.Number(label=korean_labels["Seed"], value=42, precision=0)
-                        randomize_seed = gr.Checkbox(label=korean_labels["Randomize Seed"], value=False)
+                        seed = gr.Number(label=english_labels["Seed"], value=42, precision=0)
+                        randomize_seed = gr.Checkbox(label=english_labels["Randomize Seed"], value=False)
                     with gr.Row():
-                        width = gr.Slider(label=korean_labels["Width"], minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_WIDTH)
-                        height = gr.Slider(label=korean_labels["Height"], minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_HEIGHT)
-                        num_inference_steps = gr.Slider(label=korean_labels["Inference Steps"], minimum=1, maximum=4, step=1, value=DEFAULT_INFERENCE_STEPS)
+                        width = gr.Slider(label=english_labels["Width"], minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_WIDTH)
+                        height = gr.Slider(label=english_labels["Height"], minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_HEIGHT)
+                        num_inference_steps = gr.Slider(label=english_labels["Inference Steps"], minimum=1, maximum=4, step=1, value=DEFAULT_INFERENCE_STEPS)
 
         with gr.Row():
-            gr.Markdown(f"### 🌟 {korean_labels['Inspiration Gallery']}")
+            gr.Markdown(f"### 🌟 {english_labels['Inspiration Gallery']}")
         with gr.Row():
             gr.Examples(
                 examples=examples,