diff --git a/sdxl_train.py b/sdxl_train.py
index 66b3c76d..35934c38 100644
--- a/sdxl_train.py
+++ b/sdxl_train.py
@@ -41,6 +41,7 @@ def train(args):
     ), "cache_text_encoder_outputs is not supported when training text encoder / text encoderを学習するときはcache_text_encoder_outputsはサポートされていません"
 
     cache_latents = args.cache_latents
+    use_dreambooth_method = args.in_json is None
 
     if args.seed is not None:
         set_seed(args.seed)  # 乱数系列を初期化する
@@ -61,18 +62,31 @@ def train(args):
                     )
                 )
         else:
-            user_config = {
-                "datasets": [
-                    {
-                        "subsets": [
-                            {
-                                "image_dir": args.train_data_dir,
-                                "metadata_file": args.in_json,
-                            }
-                        ]
-                    }
-                ]
-            }
+            if use_dreambooth_method:
+                print("Using DreamBooth method.")
+                user_config = {
+                    "datasets": [
+                        {
+                            "subsets": config_util.generate_dreambooth_subsets_config_by_subdirs(
+                                args.train_data_dir, args.reg_data_dir
+                            )
+                        }
+                    ]
+                }
+            else:
+                print("Training with captions.")
+                user_config = {
+                    "datasets": [
+                        {
+                            "subsets": [
+                                {
+                                    "image_dir": args.train_data_dir,
+                                    "metadata_file": args.in_json,
+                                }
+                            ]
+                        }
+                    ]
+                }
 
         blueprint = blueprint_generator.generate(user_config, args, tokenizer=[tokenizer1, tokenizer2])
         train_dataset_group = config_util.generate_dataset_group_by_blueprint(blueprint.dataset_group)