modify byte.trackerupdate, add list first_finded

tracking/dotrack/dotracks.py

@@ -216,7 +216,7 @@ class Track:
                         trajdist_min,  trajdist_max,
                         trajlen_rate, trajdist_rate]
         
-    def compute_static_fids(self, det_y, STATIC_THRESH = 8):
+    def pt_state_fids(self, det_y, STATIC_THRESH = 8):
         '''
         前摄时，y一般选择为 box 的 y1 坐标，且需限定商品在购物车内。
         inputs：
@@ -324,12 +324,15 @@ class doTracks:
         for t_id in self.trackID: 
             # print(f"The ID is: {t_id}")
             idx = np.where(track_ids == t_id)[0]
-            box = self.bboxes[idx, :]     
+            box = self.bboxes[idx, :]  
+            
+            assert len(set(box[:, 7])) == len(box), "Please check!!!"
 
             lboxes.append(box)
         
         return lboxes
     
+    '''
     def classify(self):
         
         tracks = self.tracks
@@ -354,10 +357,11 @@ class doTracks:
         self.Static.extend(static_tracks)
         
         
-        '''剔除静止目标后的 tracks'''
+        # 剔除静止目标后的 tracks
         tracks = self.sub_tracks(tracks, static_tracks)
         
         return tracks
+    '''
         
     
         

tracking/dotrack/dotracks_back.py

@@ -51,41 +51,29 @@ class doBackTracks(doTracks):
 #         return lboxes
 # =============================================================================
 
-            
-    
     def classify(self):
-        '''
-        功能：对 tracks 中元素分类
-        
-        '''
-        tracks = super().classify()
-        
-        # tracks = self.tracks
-        # shopcart = self.shopcart
+        '''功能：对 tracks 中元素分类 '''
 
-        # # 提取手的frame_id，并和动目标的frame_id 进行关联
-        # hand_tracks = [t for t in tracks if t.cls==0]
-        # self.Hands.extend(hand_tracks)
-        # tracks = self.sub_tracks(tracks, hand_tracks)
+        tracks = self.tracks
+        # 提取手的frame_id，并和动目标的frame_id 进行关联
+        hand_tracks = [t for t in tracks if t.cls==0]
+        self.Hands.extend(hand_tracks)
         
-        
-        
-        # # 提取小孩的track，并计算状态：left, right, incart
-        # kid_tracks = [t for t in tracks if t.cls==9]
-        # kid_states = [self.kid_state(t) for t in kid_tracks]
-        # self.Kids = [x for x in zip(kid_tracks, kid_states)]
-        
-        # tracks = self.sub_tracks(tracks, kid_tracks)
+        tracks = self.sub_tracks(tracks, hand_tracks)
 
+        # 提取小孩的track，并计算状态：left, right, incart
+        kid_tracks = [t for t in tracks if t.cls==9]
+        kid_states = [self.kid_state(t) for t in kid_tracks]
+        self.Kids = [x for x in zip(kid_tracks, kid_states)]
+        
+        tracks = self.sub_tracks(tracks, kid_tracks)
 
-        # static_tracks = [t for t in tracks if t.frnum>1 and t.is_static()] 
-        # self.Static.extend(static_tracks)
-        
-        
-        # '''剔除静止目标后的 tracks'''
-        # tracks = self.sub_tracks(tracks, static_tracks)
-        
+        static_tracks = [t for t in tracks if t.frnum>1 and t.is_static()] 
+        self.Static.extend(static_tracks)
         
+        '''剔除静止目标后的 tracks'''
+        tracks = self.sub_tracks(tracks, static_tracks)
+
         
         '''购物框边界外具有运动状态的干扰目标'''
         out_trcak = [t for t in tracks if t.is_OutTrack()]

tracking/dotrack/track_back.py

@@ -31,7 +31,7 @@ class backTrack(Track):
         '''运动点帧索引(运动帧两端的静止帧索引)'''
         self.moving_index = self.compute_dynamic_fids()
         
-        self.static_dynamic_fids = self.compute_static_dynamic_fids()
+        # self.static_index, self.moving_index = self.compute_static_dynamic_fids()
         
         '''该函数依赖项: self.cornpoints，定义 4 个商品位置变量：
             self.Cent_isIncart, self.LB_isIncart, self.RB_isIncart
@@ -250,13 +250,35 @@ class backTrack(Track):
         return moving_index     
     
     def compute_static_dynamic_fids(self):
-        static_dynamic_fids = []
-        for traj in self.trajectory:
-            static, dynamic = self.compute_static_fids(traj)
+        
+        idx2 = self.trajlens.index(min(self.trajlens))            
+        trajmin = self.trajectory[idx2]
+        
+        static, dynamic = self.pt_state_fids(trajmin) 
+        
+        static = np.array(static)
+        dynamic = np.array(dynamic)
+        
+        if static.size:
+            indx = np.argsort(static[:, 0])
+            static = static[indx]
+        if dynamic.size:
+            indx = np.argsort(dynamic[:, 0])
+            dynamic = dynamic[indx]
             
-            static_dynamic_fids.append((static, dynamic))
-            
-        return static_dynamic_fids
+        return static, dynamic
+        
+        
+        
+        
+# =============================================================================
+#         static_dynamic_fids = []
+#         for traj in self.trajectory:
+#             static, dynamic = self.pt_state_fids(traj)            
+#             static_dynamic_fids.append((static, dynamic))
+#                
+#         return static_dynamic_fids
+# =============================================================================
     
     
     
@@ -270,6 +292,10 @@ class backTrack(Track):
                       trajlen_rate, trajdist_rate]
         '''
         
+        # print(f"TrackID: {self.tid}")
+        boxes = self.boxes
+        
+        
         condt1 = self.feature[5] < 0.2 or self.feature[3] < 120
         
         '''静态情况 2: 目标初始状态为静止，适当放宽关键点最小相对运动轨迹 < 0.5'''

tracking/dotrack/track_front.py

@@ -31,8 +31,8 @@ class frontTrack(Track):
         '''y1、y2静止状态区间，值是 boxes 中对 axis=0 的索引，不是帧索引'''
         det_y1 = np.diff(boxes[:, 1], axis=0)
         det_y2 = np.diff(boxes[:, 3], axis=0)
-        self.static_y1, self.dynamic_y1 = self.compute_static_fids(det_y1)
-        self.static_y2, self.dynamic_y2 = self.compute_static_fids(det_y2)
+        self.static_y1, self.dynamic_y1 = self.pt_state_fids(det_y1)
+        self.static_y2, self.dynamic_y2 = self.pt_state_fids(det_y2)
         
         self.isCornpoint = self.is_left_or_right_cornpoint()
         self.isBotmpoint = self.is_bottom_cornpoint()

tracking/test_tracking.py

@@ -90,7 +90,7 @@ def have_tracked():
     k = 0
     gt = Profile()
     for filename in os.listdir(trackdict):
-        filename = 'test_20240402-173935_6920152400975_front_174037379.pkl'
+        filename = 'test_20240402-173935_6920152400975_back_174037372.pkl'
         file, ext = os.path.splitext(filename)
         filepath = os.path.join(trackdict, filename)
         TracksDict = np.load(filepath, allow_pickle=True)
@@ -121,9 +121,9 @@ def have_tracked():
         
         
         
-        # k += 1
-        # if k==1:
-        #     break
+        k += 1
+        if k==1:
+            break
     
     if len(alltracks):
         drawFeatures(alltracks, save_dir)

tracking/trackers/byte_tracker.py

@@ -214,6 +214,8 @@ class BYTETracker:
         refind_stracks = []
         lost_stracks = []
         removed_stracks = []
+        
+        first_finded = []
 
         scores = results.conf
         cls = results.cls
@@ -328,6 +330,9 @@ class BYTETracker:
                 continue
             track.activate(self.kalman_filter, self.frame_id)
             activated_stracks.append(track)
+            
+            first_finded.append(track)
+            
         # Step 5: Update state
         for track in self.lost_stracks:
             if self.frame_id - track.end_frame > self.max_time_lost:
@@ -359,7 +364,7 @@ class BYTETracker:
                               for x in self.tracked_stracks if x.is_activated]
         
         output2 = [x.tlwh_to_tlbr(x._tlwh).tolist() + [x.track_id, x.score, x.cls, x.frame_id, x.idx] 
-                              for x in activated_stracks if x.first_find]
+                              for x in first_finded if x.first_find]
         
         output = np.asarray(output1+output2, dtype=np.float32)
 

tracking/utils/drawtracks.py

@@ -11,6 +11,7 @@ import matplotlib.pyplot as plt
 from sklearn.decomposition import PCA
 from utils.annotator import TrackAnnotator
 from utils.plotting import colors
+from pathlib import Path
 
 
 def plot_frameID_y2(vts):
@@ -88,14 +89,18 @@ def draw_all_trajectories(vts, edgeline, save_dir, filename):
     
 # =============================================================================
 #     '''1. tracks 5点轨迹'''
+#     trackpth = save_dir.parent /Path("trajectory")/ Path(f"{file}")
+#     if not trackpth.exists():
+#         trackpth.mkdir(parents=True, exist_ok=True)
 #     for track in vts.tracks:
-#         if track.cls != 0:
-#             img = edgeline.copy()
-#             img = draw5points(track, img)
-#             pth = save_dir.joinpath(f"{file}_{track.tid}.png")
-#             cv2.imwrite(pth, img)
+#         # if track.cls != 0:
+#         img = edgeline.copy()
+#         img = draw5points(track, img)
+# 
+#         pth = trackpth.joinpath(f"{track.tid}.png")        
+#         cv2.imwrite(str(pth), img)
+#     
 # =============================================================================
-    
     '''2. all tracks 中心轨迹'''
     img1, img2 = edgeline.copy(), edgeline.copy()