diff --git a/best0.pt b/best0.pt
index d19e0c8..e538ab6 100644
Binary files a/best0.pt and b/best0.pt differ
diff --git a/config.json b/config.json
index 650d072..32dd98b 100644
--- a/config.json
+++ b/config.json
@@ -1,18 +1,8 @@
 {
     "groups": [
-        {
-            "name": "电脑2",
-            "serial_port": "COM13",
-            "serial_baudrate": 9600,
-            "camera_index": 1,
-            "camera_width": 1920,
-            "camera_height": 1080,
-            "move_velocity": 400,
-            "active": false
-        },
         {
             "name": "服务器",
-            "serial_port": "COM12",
+            "serial_port": "COM16",
             "serial_baudrate": 9600,
             "camera_index": 0,
             "camera_width": 1920,
diff --git a/main.py b/main.py
index 2a9c50e..460846a 100644
--- a/main.py
+++ b/main.py
@@ -62,6 +62,18 @@ rw = (632, 378)
 v = active_group['move_velocity']
 
 def yolo_shibie(im_PIL, detections, model):
+    detections = {
+        'center': None,
+        'next': None,
+        'npc1': None,
+        'npc2': None,
+        'npc3': None,
+        'npc4': None,
+        'boss': None,
+        'daojv': [],
+        'gw': [],
+        'zhaozi': None
+    }
     results = model(im_PIL)  # 目标检测
     for result in results:
         for i in range(len(result.boxes.xyxy)):
@@ -186,7 +198,7 @@ while True:
         continue
     detections = yolo_shibie(im_opencv[1], detections, model)
     
-    if shizi.tuwai(im_opencv[0]):  # 进图算法
+    if shizi.tuwai(im_opencv[0]) or yolo_shibie(im_opencv[1], model0)['npc1'] is not None or yolo_shibie(im_opencv[1], model0)['npc2'] is not None or yolo_shibie(im_opencv[1], model0)['npc3'] is not None or yolo_shibie(im_opencv[1], model0)['npc4'] is not None:  # 进图算法  # 进图算法
         im_opencv = get_image.get_frame()  # [RGB,PIL]
         if im_opencv is None:
             print("⚠️ 无法获取图像帧，跳过本次循环")
diff --git a/utils/shizi.py b/utils/shizi.py
index ac8f3a4..8eb33f8 100644
--- a/utils/shizi.py
+++ b/utils/shizi.py
@@ -68,7 +68,7 @@ def tuwai(image):
     img_bytes = img_encoded.tobytes()
     result = ocr.classification(img_bytes)
     print(result)
-    if result == "tap" or result=='tqp' or result=='top':
+    if result == "tap" or result=='tqp' or result=='top' or result=='tp':
         return True
     else:
         return False