hoàn thành chức năng tính ndvi analysys 2 màn hình

new_import_ODC.py

@@ -224,12 +224,46 @@ def train_with_rf(X_train, X_val, y_train, y_val):
     return grid_search
 
 
-def save_model(name_file, grid_search):
+def save_model(name_file, model, metadata=None, label_encoder=None):
+    """
+    Save model với metadata để tương thích với ModelManager
+    
+    Args:
+        name_file: Tên file model
+        model: Model object
+        metadata: Dict chứa thông tin về model (optional)
+        label_encoder: Label encoder (optional)
+    """
+    from model_manager import get_model_manager
+    
     dir_save_model = "model_train"
     if not os.path.exists(dir_save_model):
         os.mkdir(dir_save_model)
-    joblib.dump(grid_search, os.path.join(dir_save_model, name_file))
-    print("Done!")
+    
+    # Nếu có metadata, sử dụng ModelManager
+    if metadata is not None:
+        model_manager = get_model_manager()
+        model_manager.save_model(
+            model=model,
+            metadata=metadata,
+            model_filename=name_file,
+            label_encoder=label_encoder
+        )
+    else:
+        # Legacy mode: save trực tiếp (backward compatibility)
+        model_data = {
+            'model': model,
+            'label_encoder': label_encoder
+        } if label_encoder is not None else model
+        
+        joblib.dump(model_data, os.path.join(dir_save_model, name_file))
+    
+    print(f"✅ Model saved: {name_file}")
+    if metadata:
+        print(f"   - Type: {metadata.get('model_type', 'N/A')}")
+        print(f"   - Features: {metadata.get('n_features', 'N/A')}")
+        print(f"   - Accuracy: {metadata.get('test_accuracy', 'N/A')}")
+
     
     
 def predict(model, data_crs, ndvi, vh, vv):