update for bakeup

tracking/utils/read_data.py

@@ -30,6 +30,8 @@ def find_samebox_in_array(arr, target):
             return i
     return -1
 
+import warnings
+
 
 def extract_data(datapath):
     bboxes, ffeats = [], []
@@ -47,6 +49,17 @@ def extract_data(datapath):
             if line.find("CameraId")>=0:
                 if len(boxes): bboxes.append(np.array(boxes))
                 if len(feats): ffeats.append(np.array(feats))
+                
+                # with warnings.catch_warnings(record=True) as w:
+                #     if len(boxes): bboxes.append(np.array(boxes))
+                #     if len(feats): ffeats.append(np.array(feats))
+                # if w:
+                #     print(f"捕获到 {len(w)} 个警告:")
+                #     for warning in w:
+                #         print(f"警告类型: {warning.category}")
+                #         print(f"警告消息: {warning.message}")
+                #         print(f"警告发生的地方: {warning.filename}:{warning.lineno}")
+                
                 if len(tboxes):  
                     trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)))
                 if len(tfeats):
@@ -56,16 +69,20 @@ def extract_data(datapath):
             
             if line.find("box:") >= 0 and line.find("output_box:") < 0:
                 box = line[line.find("box:") + 4:].strip()
+                # if len(box)==6:
                 boxes.append(str_to_float_arr(box))
                 
             if line.find("feat:") >= 0:
                 feat = line[line.find("feat:") + 5:].strip()
+                # if len(feat)==256:
                 feats.append(str_to_float_arr(feat))
                     
             if line.find("output_box:") >= 0:
                 box = str_to_float_arr(line[line.find("output_box:") + 11:].strip())
                 tboxes.append(box)  # 去掉'output_box:'并去除可能的空白字符  
                 index = find_samebox_in_array(boxes, box)
+                
+                assert(len(boxes)==len(feats)), f"{datapath}, {datapath}, len(boxes)!=len(feats)"
                 if index >= 0:
                     # feat_f = str_to_float_arr(input_feats[index])
                     feat_f = feats[index]
@@ -120,7 +137,7 @@ def extract_data(datapath):
                     tracking_feat_dict[f"track_{tid}"]= {"feats": {}}
                 tracking_feat_dict[f"track_{tid}"]["feats"].update({f"{fid}_{bid}": tracker_feat_dict[f"frame_{fid}"]["feats"][bid]})
     except Exception as e:
-        print(f'Path: {datapath}, Error: {e}') 
+        print(f'Path: {datapath}, tracking_feat_dict can not be structured correcttly, Error: {e}') 
 
     return bboxes, ffeats, trackerboxes, tracker_feat_dict, trackingboxes, tracking_feat_dict
 
@@ -142,6 +159,8 @@ def read_tracking_output(filepath):
                 boxes.append(data)
             if data.size == 256:
                 feats.append(data)
+        
+        assert(len(feats)==len(boxes)), f"{filepath}, len(feats)!=len(boxes)"
     
     return np.array(boxes), np.array(feats) 
     
@@ -166,16 +185,9 @@ def read_deletedBarcode_file(filePth):
                 dict, barcode_list, similarity_list =  {}, [], []
                 continue
             
-            # print(line)
-            try:
-                label = line.split(':')[0]
-                value = line.split(':')[1]
-            except Exception as e:
-                print(f'Error: {e}')    
-            
-            
-            
-            
+            if line.find(':')<0: continue
+            label = line.split(':')[0]
+            value = line.split(':')[1]
             
             if label == 'SeqDir':
                 dict['SeqDir'] = value