diff --git a/classifier/embedding_food_classifier_app.py b/classifier/embedding_food_classifier_app.py
index d386498..81a8fad 100644
--- a/classifier/embedding_food_classifier_app.py
+++ b/classifier/embedding_food_classifier_app.py
@@ -61,7 +61,7 @@ class EmbeddingFoodClassifierApp:
         """加载训练好的embedding模型和FAISS索引"""
         try:
             # 模型路径
-            model_path = "../model/embedding_20250930_102826/best_embedding_model.pth"
+            model_path = "../model/embedding_20251010_111257/best_embedding_model.pth"
             
             # FAISS索引目录
             index_dir = "../faiss_vector_db/faiss_index"
diff --git a/classifier/embedding_food_classifier_search_app.py b/classifier/embedding_food_classifier_search_app.py
index da4e56c..82c764f 100644
--- a/classifier/embedding_food_classifier_search_app.py
+++ b/classifier/embedding_food_classifier_search_app.py
@@ -62,7 +62,7 @@ class EmbeddingFoodClassifierApp:
         """加载训练好的embedding模型和FAISS索引"""
         try:
             # 模型路径
-            model_path = "../model/embedding_20250930_102826/best_embedding_model.pth"
+            model_path = "../model/embedding_20251010_111257/best_embedding_model.pth"
             
             # FAISS索引目录
             index_dir = "../faiss_vector_db/faiss_index"
@@ -1136,8 +1136,8 @@ class EmbeddingFoodClassifierApp:
             topk_scores, topk_indices = torch.topk(sims, k=min(k, sims.shape[1]), dim=1)
             indices = topk_indices.cpu().numpy()
             scores = topk_scores.cpu().numpy()
-            # print("相似度索引：", indices)
-            # print("相似度分数：", scores)
+            print("相似度索引：", indices)
+            print("相似度分数：", scores)
 
             # 收集相似图片的类别
             similar_classes = []
diff --git a/data_expansion/data_expansion.py b/data_expansion/data_expansion.py
index 052e561..03e879e 100644
--- a/data_expansion/data_expansion.py
+++ b/data_expansion/data_expansion.py
@@ -27,7 +27,7 @@ for class_name in os.listdir(input_root):
     input_dir = os.path.join(input_root, class_name)
     output_dir = os.path.join(output_root, class_name)
     os.makedirs(output_dir, exist_ok=True)
-    if class_name == "肉沫酸豆角":
+    if class_name == "手撕包菜":
         # 读取类别下所有图片路径
         img_files = [f for f in os.listdir(input_dir) if f.lower().endswith(('.jpg', '.png', '.jpeg'))]
         img_paths = [os.path.join(input_dir, f) for f in img_files]
diff --git a/faiss_vector_db/build_faiss_index.py b/faiss_vector_db/build_faiss_index.py
index 5c1abaf..7335be1 100644
--- a/faiss_vector_db/build_faiss_index.py
+++ b/faiss_vector_db/build_faiss_index.py
@@ -477,7 +477,7 @@ class FAISSSearcher:
 def main():
     """主函数"""
     # 配置参数
-    MODEL_PATH = "../model/embedding_20250930_102826/best_embedding_model.pth"
+    MODEL_PATH = "../model/embedding_20251010_111257/best_embedding_model.pth"
     TRAIN_DIR = "../dataset/train"
     OUTPUT_DIR = "faiss_index"
     BATCH_SIZE = 16