diff --git a/simple_reid.py b/simple_reid.py
index 7a84db2..893651f 100644
--- a/simple_reid.py
+++ b/simple_reid.py
@@ -1,19 +1,17 @@
 import shutil
-
+import matplotlib.pyplot as plt
 import torch
 from torchvision import transforms
 import numpy as np
 import cv2
 import os
-
 import param
 from deep_sort.deep.feature_extractor import FastReIDExtractor
-
 from fastreid.demo import FeatureExtractionDemo
 from fastreid.config import get_cfg
 
 
-def extractidfeature(id_path:str,extractor:FeatureExtractionDemo):
+def extractidfeature(id_path: str, extractor: FeatureExtractionDemo):
     img_id = cv2.imread(id_path)
     tensor_id = extractor.run_on_image(img_id)
     return tensor_id.detach().cpu().numpy()
@@ -21,46 +19,60 @@ def extractidfeature(id_path:str,extractor:FeatureExtractionDemo):
 # example        
 if __name__ == '__main__':
     dislist = {}
-    
     extractor_model_path = "./deep_sort/deep/checkpoint/market_bot_R50-ibn.pth"
     cfg_path   = "./fastreid/cfgs/Market1501/bagtricks_R50-ibn.yml"
-    query_path = "./query/cam1"
-    galla_path = "./gallary"
-    
+    query_path = "D:\\study\\python\\1zhouxue\\UESTC_ReID_Dataset_V3\\query\\cam3"
+    galla_path = "D:\\study\\python\\1zhouxue\\UESTC_ReID_Dataset_V3\\gallery"
+    C=3
     gallary_list = os.listdir(galla_path)
-    
     count = 0
     cfg = get_cfg()
     cfg.MODEL.DEVICE = 'cpu'
+    cfg.MODEL.WEIGHTS = extractor_model_path
     cfg.merge_from_file(cfg_path)
     cfg.freeze()
     
     my_option = param.Parameters() # load model in head
     extractor = FeatureExtractionDemo(cfg)
     with torch.no_grad():
-        for i in range(3,26):
+        for i in range(1,6):
             count = 0
             dislist.clear()
-            id_try = extractidfeature(query_path+f"/1_{i}.jpg",extractor)
+            id_try = extractidfeature(query_path+f"/{C}_{i}.jpg",extractor)
             for gal in gallary_list:
                 count += 1
-                if(count%10 == 0):
+                if count % 25 == 0:
                     id_tar = extractidfeature(galla_path+'/'+gal,extractor)
-                    dist   = np.sum(np.abs(id_try-id_tar))
+                    dist = np.sum(np.abs(id_try-id_tar))
                     dislist[gal] = float(dist)
-                if count>5000:
+                if count > 8000:
                     break
-            matched = sorted(dislist.items(),key=lambda x:x[1])
+            matched = sorted(dislist.items(), key=lambda x : x[1])
             print(matched)
             try:
-                os.mkdir("match/"+ f"1_{i}")
+                os.mkdir("match/" + f"{C}_{i}")
             except:
                 pass
+            x = 1
             for path in matched[0:10]:
                 s_path = galla_path+'/'+path[0]
-                t_path = "match/"+ f"1_{i}" +"/"+path[0]
-                print(s_path,t_path)
-                shutil.copy(s_path,t_path)
-            
+                t_path = "match/" + f"{C}_{i}" + "/" + path[0]
+                print(s_path, t_path)
+                shutil.copy(s_path, t_path)
+
+                ID = path[0].split('_')
+                # print(ID)
+                ID = int(ID[0])
+                img = plt.imread(s_path)
+                plt.subplot(1, 10, x)
+                if id == i:
+                    plt.title(x)
+                else:
+                    plt.title(f"{x}_F")
+                plt.imshow(img)
+                plt.xticks([])
+                plt.yticks([])
+                x += 1
+            plt.show()
             
             
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