1:n modified

tracking/tracking_test.py

@@ -24,6 +24,8 @@ from dotrack.dotracks_back import doBackTracks
 from dotrack.dotracks_front import doFrontTracks 
 from utils.drawtracks import draw5points, drawTrack, drawtracefeat, plot_frameID_y2, drawFeatures, draw_all_trajectories
 
+from utils.read_data import extract_data_realtime, read_tracking_output_realtime
+
 # from datetime import datetime
 # from utils.proBoxes import boxes_add_fid
 # from utils.plotting import boxing_img  #, Annotator, colors,
@@ -80,20 +82,38 @@ def save_subimgs(vts, file, TracksDict):
             cv2.imwrite(str(imgdir) + f"/{tid}_{fid}_{bid}.png", img)
 
 def have_tracked():
-    trackdict = r'./data/trackdicts'
-    alltracks = []
+    # trackdict = r'./data/trackdicts'
+    trackdict = r'D:\全实时\202502\20250228-152846-438_6901668934727_6901668934727'
+    
+    bboxes, alltracks = [], []
     k = 0
     gt = Profile()
     for filename in os.listdir(trackdict):
-        filename = '153112511_0_seek_105.pkl'
-
+        # filename = '153112511_0_seek_105.pkl'
+        
         file, ext = os.path.splitext(filename)
         filepath = os.path.join(trackdict, filename)
-        TracksDict = np.load(filepath, allow_pickle=True)
+        
+        if file.split('_')[0]=='0' or file.find("back") >= 0:
+            CamerType = "back"
+        if file.split('_')[0]=='1' or file.find("front") >= 0:
+            CamerType = "front"
+        
+        ## 1. 加载 tracker 输出的 pickle 文件
+        if ext in ['.pkl', '.pickle']:
+            filepath = os.path.join(trackdict, filename)
+            TracksDict = np.load(filepath, allow_pickle=True)
+            bboxes = TracksDict['TrackBoxes']
+        
+        ## 2. 加载 data 文件    
+        if filename.find('tracker.data')>0:
+            bboxes, TracksDict = extract_data_realtime(filepath)
+            
+        if len(bboxes)==0:
+            continue
 
-        bboxes = TracksDict['TrackBoxes']
         with gt:
-            if filename.find("front") >= 0:
+            if CamerType == "front":
                 vts = doFrontTracks(bboxes, TracksDict)
                 
                 Intrude = vts.isintrude()
@@ -112,7 +132,7 @@ def have_tracked():
                 edgeline = cv2.imread("./shopcart/cart_tempt/board_ftmp_line.png")
                 img_tracking = draw_all_trajectories(vts, edgeline, save_dir, file, draw5p=True)
                 
-            else:
+            if CamerType == "back":
                 vts = doBackTracks(bboxes, TracksDict)
                 
                 Intrude = vts.isintrude()

tracking/utils/read_data.py

@@ -205,10 +205,13 @@ def extract_data_realtime(datapath):
             if line.endswith(','):  
                 line = line[:-1]  
             ftlist = [float(x) for x in line.split()]
-            if len(ftlist) != 265: continue
+            
+            if len(ftlist) != 265:
+                continue
             boxes.append(ftlist[:9])
             feats.append(ftlist[9:])
     
+    
     trackerboxes = np.array(boxes)
     trackerfeats = np.array(feats)
     
@@ -381,14 +384,21 @@ def read_similar(filePath):
             if Flag_1ton:
                 label = line.split(':')[0].strip()
                 value = line.split(':')[1].strip()
-                
-                bcd = label.split('_')[-1] 
-                if len(bcd)<8: continue
-            
+                Dict['barcode'] = ''
+                if label.find("_") > 0:
+                    bcd = label.split('_')[-1]
+                    if len(bcd)>=10 and bcd.isdigit():
+                        Dict['barcode'] = bcd
+                        
+
+
                 Dict['event'] = label
-                Dict['barcode'] = bcd
                 Dict['similar'] = float(value.split(',')[0])
-                Dict['type'] = value.split(',')[1]
+                
+                if value.find("=")>0:
+                    Dict['type'] = value.split('=')[-1]
+                else:
+                    Dict['type'] = value.split(',')[-1]
                 one2n_list.append(Dict)
 
         if len(one2one_list): SimiDict['one2one'] = one2one_list