initial project version!

tracking/dotrack/dotracks_back.py

@@ -0,0 +1,179 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar  4 18:36:31 2024
+
+@author: ym
+"""
+import numpy as np
+from utils.mergetrack import track_equal_track
+from scipy.spatial.distance import cdist
+from .dotracks import doTracks, ShoppingCart
+from .track_back import backTrack
+
+
+class doBackTracks(doTracks):
+    def __init__(self, bboxes, TracksDict):
+        
+        super().__init__(bboxes, TracksDict)
+        
+        self.tracks = [backTrack(b) for b in self.lboxes]
+        
+        # self.similar_dict = self.similarity()
+        
+        
+        self.shopcart = ShoppingCart(bboxes)
+
+# =============================================================================
+#     def array2list(self):
+#         '''           0, 1,   2,  3,     4,      5,    6,      7,          8
+#             bboxes: [x1, y1, x2, y2, track_id, score, cls, frame_index, box_index]
+#             lboxes：[x1, y1, x2, y2, track_id, score, cls, frame_index, box_index] 
+#         '''
+# 
+#         track_ids = set(self.bboxes[:, 4])
+#         lboxes = []
+#         for t_id in track_ids:
+#             idx = np.where(self.bboxes[:, 4] == t_id)[0]
+#             box = self.bboxes[idx, :]
+#             
+#             x = (box[:, 0] + box[:, 2]) / 2
+#             y = (box[:, 1] + box[:, 3]) / 2
+#             
+#             # box: [x, y, w, h, track_id, score, cls, frame_index]
+#             box[:, 2] = box[:, 2] - box[:, 0]    
+#             box[:, 3] = box[:, 3] - box[:, 1]
+#             box[:, 0] = x
+#             box[:, 1] = y
+#       
+#             lboxes.append(box)
+# 
+#         
+#         return lboxes
+# =============================================================================
+
+            
+    
+    def classify(self):
+        '''
+        功能：对 tracks 中元素分类
+        
+        '''
+        tracks = super().classify()
+        
+        # tracks = self.tracks
+        # shopcart = self.shopcart
+
+        # # 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)
+        
+        
+        
+        # # 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)
+        
+        
+        
+        '''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()]
+
+        tracks = self.sub_tracks(tracks, out_trcak)
+
+        
+        '''轨迹循环归并'''
+        # merged_tracks = self.merge_tracks(tracks)
+        merged_tracks = self.merge_tracks_loop(tracks)
+        tracks = [t for t in merged_tracks if t.frnum > 1]
+
+        self.Residual = tracks
+
+
+        
+    def merge_tracks(self, Residual):
+        """
+        对不同id，但可能是同一商品的目标进行归并
+        """ 
+        mergedTracks = self.base_merge_tracks(Residual)
+        
+        oldtracks, newtracks = [], []
+        for tracklist in mergedTracks:
+            if len(tracklist) > 1:
+                boxes = np.empty((0, 9), dtype=np.float32)
+                for i, track in enumerate(tracklist):
+                    if i==0: ntid, ncls=track.boxes[0, 4], track.boxes[0, 6]
+                    iboxes = track.boxes.copy()
+                    
+                    iboxes[:, 4], iboxes[:, 6] = ntid, ncls
+                    boxes = np.concatenate((boxes, iboxes), axis=0)
+                    
+                    oldtracks.append(track)
+                    
+                fid_indices = np.argsort(boxes[:, 7])
+                boxes_fid = boxes[fid_indices]    
+                    
+                newtracks.append(backTrack(boxes_fid))
+            elif len(tracklist) == 1:
+                oldtracks.append(tracklist[0])
+                newtracks.append(tracklist[0])
+                
+
+        redu = self.sub_tracks(Residual, oldtracks)
+        merged = self.join_tracks(redu, newtracks)
+
+        return merged      
+        
+    def kid_state(self, track):
+        
+        left_dist = track.cornpoints[:, 2]
+        right_dist = 1024 - track.cornpoints[:, 4]
+        
+        if np.sum(left_dist<30)/track.frnum>0.8 and np.sum(right_dist>512)/track.frnum>0.7:
+            kidstate = "left"
+        elif np.sum(left_dist>512)/track.frnum>0.7 and np.sum(right_dist<30)/track.frnum>0.8:
+            kidstate = "right"
+        else:
+            kidstate = "incart"
+        
+        return kidstate
+    
+    
+
+    def is_associate_with_hand(self):
+        """
+        分析商品和手之间的关联性
+        """
+        pass 
+    
+    
+    
+
+      
+       
+
+    def isuptrack(self, track):
+        Flag = False
+        
+        return Flag
+    
+    def isdowntrack(self, track):
+        Flag = False
+        
+        return Flag
+    
+    def isfreetrack(self, track):
+        Flag = False
+        
+        return Flag