Update app.py

app.py

@@ -1,13 +1,11 @@
 import gradio as gr
 import numpy as np
 import random
-
-# import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+model_repo_id = "stabilityai/sdxl-turbo"  # 사용하려는 모델 이름
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
@@ -20,8 +18,6 @@ pipe = pipe.to(device)
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
     prompt,
     negative_prompt,
@@ -66,71 +62,71 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
+        gr.Markdown(" # 텍스트-이미지 생성 Gradio 템플릿")
 
         with gr.Row():
             prompt = gr.Text(
-                label="Prompt",
+                label="프롬프트",
                 show_label=False,
                 max_lines=1,
-                placeholder="Enter your prompt",
+                placeholder="생성하고 싶은 이미지를 입력하세요",
                 container=False,
             )
 
-            run_button = gr.Button("Run", scale=0, variant="primary")
+            run_button = gr.Button("실행", scale=0, variant="primary")
 
-        result = gr.Image(label="Result", show_label=False)
+        result = gr.Image(label="결과", show_label=False)
 
-        with gr.Accordion("Advanced Settings", open=False):
+        with gr.Accordion("고급 설정", open=False):
             negative_prompt = gr.Text(
-                label="Negative prompt",
+                label="네거티브 프롬프트",
                 max_lines=1,
-                placeholder="Enter a negative prompt",
+                placeholder="포함하지 않을 내용을 입력하세요",
                 visible=False,
             )
 
             seed = gr.Slider(
-                label="Seed",
+                label="시드 값",
                 minimum=0,
                 maximum=MAX_SEED,
                 step=1,
                 value=0,
             )
 
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+            randomize_seed = gr.Checkbox(label="시드 랜덤화", value=True)
 
             with gr.Row():
                 width = gr.Slider(
-                    label="Width",
+                    label="너비 (픽셀)",
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,  # 모델에 적합한 기본값으로 설정
                 )
 
                 height = gr.Slider(
-                    label="Height",
+                    label="높이 (픽셀)",
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,  # 모델에 적합한 기본값으로 설정
                 )
 
             with gr.Row():
                 guidance_scale = gr.Slider(
-                    label="Guidance scale",
+                    label="가이던스 스케일",
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                    value=0.0,  # 모델에 적합한 기본값으로 설정
                 )
 
                 num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
+                    label="추론 단계 수",
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=2,  # 모델에 적합한 기본값으로 설정
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])