Update app.py

app.py

@@ -194,8 +194,8 @@ def plot_confusion_matrix_from_csv(csv_file_path, title, save_path, light_mode=F
     plt.title(f"{title}\nF1 Score: {f1:.3f}", color=text_color, fontsize=18)
 
     # Customize tick labels for light/dark mode
-    plt.xticks([0.5, 1.5], labels=['Class 0', 'Class 1'], color=text_color, fontsize=12)
-    plt.yticks([0.5, 1.5], labels=['Class 0', 'Class 1'], color=text_color, fontsize=12)
+    plt.xticks([0.5, 1.5], labels=['NLoS', 'LoS'], color=text_color, fontsize=12)
+    plt.yticks([0.5, 1.5], labels=['NLoS', 'LoS'], color=text_color, fontsize=12)
 
     plt.ylabel('True label', color=text_color, fontsize=14)
     plt.xlabel('Predicted label', color=text_color, fontsize=14)
@@ -365,8 +365,8 @@ def plot_confusion_matrix(y_true, y_pred, title, light_mode=False):
     plt.title(f"{title}\nF1 Score: {f1:.3f}", color=text_color, fontsize=18)
     
     # Customize tick labels for dark mode
-    plt.xticks([0.5, 1.5], labels=['Class 0', 'Class 1'], color=text_color, fontsize=12)
-    plt.yticks([0.5, 1.5], labels=['Class 0', 'Class 1'], color=text_color, fontsize=12)
+    plt.xticks([0.5, 1.5], labels=['NLoS', 'LoS'], color=text_color, fontsize=12)
+    plt.yticks([0.5, 1.5], labels=['NLoS', 'LoS'], color=text_color, fontsize=12)
     
     plt.ylabel('True label', color=text_color, fontsize=14)
     plt.xlabel('Predicted label', color=text_color, fontsize=14)