Update app.py

app.py

@@ -113,20 +113,20 @@ def predict_and_plot(velocity, temperature, precipitation, humidity):
         cleaning_times = calculate_cleaning_time(time_intervals, simulated_contamination_levels)
 
         # Lidar names
-        lidar_names = ['F/L', 'F/R', 'Left', 'Right', 'Roof', 'Rear']
+        lidar_names = ['앞/왼쪽', '앞/오른쪽', '왼쪽', '오른쪽', '지붕', '뒤']
 
         # Plot the graph
         fig, ax = plt.subplots(figsize=(12, 8))
 
         for i in range(simulated_contamination_levels.shape[1]):
             ax.plot(time_intervals, simulated_contamination_levels[:, i], label=f'{lidar_names[i]}')
-            ax.axhline(y=0.4, color='r', linestyle='--', label='Contamination Threshold' if i == 0 else "")
+            ax.axhline(y=0.4, color='r', linestyle='--', label='오염 임계값' if i == 0 else "")
             if i < len(cleaning_times):
                 ax.scatter(cleaning_times[i], 0.4, color='k')  # Mark the cleaning time point
 
-        ax.set_title('Contamination Levels Over Time for Each Lidar')
-        ax.set_xlabel('Time (seconds)')
-        ax.set_ylabel('Contamination Level')
+        ax.set_title('각 LiDAR에 대한 시간 경과에 따른 오염 수준')
+        ax.set_xlabel('시간 (초)')
+        ax.set_ylabel('오염 수준')
         ax.legend()
         ax.grid(True)