Update app.py

app.py

@@ -423,44 +423,43 @@ def create_gradio_interface():
         )
     
     with gr.Blocks(css="""
-        .contain {margin-left: auto; margin-right: auto; max-height: 800px}
-        .plot-container {height: 600px !important; width: 100% !important;}
+        .contain {margin-left: auto; margin-right: auto}
+        .output-plot {min-height: 600px !important; width: 100% !important;}
     """) as interface:
-        with gr.Column():
-            gr.Markdown("# Renewable Energy Potential Predictor")
-            
-            # 입력 섹션 - 하나의 Row에 모든 입력 배치
-            with gr.Row(equal_height=True):
-                # 이미지/파일 입력
-                rgb_input = gr.Image(label="RGB Satellite Image", type="numpy", height=150, scale=1)
-                ndvi_input = gr.Image(label="NDVI Image", type="numpy", height=150, scale=1)
-                terrain_input = gr.Image(label="Terrain Map", type="numpy", height=150, scale=1)
-                elevation_input = gr.File(label="Elevation Data (NPY)", scale=1)
-                
-                # 날씨 파라미터 입력
-                with gr.Column(scale=1):
-                    wind_speed = gr.Number(label="Wind Speed (m/s)", value=5.0)
-                    wind_direction = gr.Number(label="Wind Direction (°)", value=180.0)
-                    temperature = gr.Number(label="Temperature (°C)", value=25.0)
-                    humidity = gr.Number(label="Humidity (%)", value=60.0)
-                    predict_btn = gr.Button("Generate Predictions", variant="primary", size="lg")
-            
-            # 출력 섹션 - 전체 너비 사용
-            with gr.Box(elem_classes="plot-container"):
-                output_plot = gr.Plot(label="Prediction Results", container=True)
+        gr.Markdown("# Renewable Energy Potential Predictor")
+        
+        # 입력 섹션 - 하나의 Row에 모든 입력 배치
+        with gr.Row(equal_height=True):
+            # 이미지/파일 입력
+            rgb_input = gr.Image(label="RGB Satellite Image", type="numpy", height=150, scale=1)
+            ndvi_input = gr.Image(label="NDVI Image", type="numpy", height=150, scale=1)
+            terrain_input = gr.Image(label="Terrain Map", type="numpy", height=150, scale=1)
+            elevation_input = gr.File(label="Elevation Data (NPY)", scale=1)
             
-            # 예제 섹션
-            examples = load_examples_from_directory("filtered_climate_data")
-            gr.Examples(
-                examples=examples,
-                inputs=[rgb_input, ndvi_input, terrain_input, elevation_input,
-                       wind_speed, wind_direction, temperature, humidity],
-                outputs=output_plot,
-                fn=predict_with_processing,
-                cache_examples=True,
-                label="Click any example to run",
-                examples_per_page=5
-            )
+            # 날씨 파라미터 입력
+            with gr.Column(scale=1):
+                wind_speed = gr.Number(label="Wind Speed (m/s)", value=5.0)
+                wind_direction = gr.Number(label="Wind Direction (°)", value=180.0)
+                temperature = gr.Number(label="Temperature (°C)", value=25.0)
+                humidity = gr.Number(label="Humidity (%)", value=60.0)
+                predict_btn = gr.Button("Generate Predictions", variant="primary", size="lg")
+        
+        # 출력 섹션 - 전체 너비 사용
+        with gr.Column(elem_classes="output-plot"):
+            output_plot = gr.Plot(label="Prediction Results", container=True)
+        
+        # 예제 섹션
+        examples = load_examples_from_directory("filtered_climate_data")
+        gr.Examples(
+            examples=examples,
+            inputs=[rgb_input, ndvi_input, terrain_input, elevation_input,
+                   wind_speed, wind_direction, temperature, humidity],
+            outputs=output_plot,
+            fn=predict_with_processing,
+            cache_examples=True,
+            label="Click any example to run",
+            examples_per_page=5
+        )
         
         predict_btn.click(
             fn=predict_with_processing,