add yolo v10 and modify pipeline

tracking/trackers/bot_sort.py

@@ -116,11 +116,13 @@ class BOTSORT(BYTETracker):
         self.proximity_thresh = args.proximity_thresh
         self.appearance_thresh = args.appearance_thresh
 
-        if args.with_reid:
-            # Haven't supported BoT-SORT(reid) yet
-            # self.encoder = ReIDInterface(config)
+        # if args.with_reid:
+        #     # Haven't supported BoT-SORT(reid) yet
+        #     # self.encoder = ReIDInterface(config)
             
-            self.encoder = FeatsInterface(conf)
+        #     self.encoder = FeatsInterface(conf)
+            
+        #     print('load model {} in BOTSORT'.format(conf.testbackbone))
         
         # self.gmc = GMC(method=args.gmc_method)     # commented by WQG
 

tracking/tracking_pipeline.py

@@ -0,0 +1,180 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Mar 27 16:09:07 2025
+
+@author: ym
+"""
+import os
+import sys
+import cv2
+import pickle
+import numpy as np
+from pathlib import Path
+from scipy.spatial.distance import cdist
+
+from .dotrack.dotracks_back import doBackTracks
+from .dotrack.dotracks_front import doFrontTracks 
+from .utils.drawtracks import plot_frameID_y2, draw_all_trajectories
+from .utils.read_data import read_similar
+
+
+
+
+class CameraEvent_:
+    def __init__(self):
+        self.cameraType = '',   # "front", "back"
+        self.videoPath = '',
+        self.imagePaths = [],
+        self.yoloResnetTracker =[],
+        self.tracking = None,
+
+class ShoppingEvent_:
+    def __init__(self):
+        self.eventPath = ''
+        self.eventName = ''
+        self.barcode = ''
+        self.eventType = '',   # "input", "output", "other"
+        self.frontCamera = None
+        self.backCamera = None
+        self.one2n = []
+    
+    
+
+
+
+def main():
+    '''
+    将一个对象读取，修改其中一个属性
+    
+    '''
+    
+    
+    evt_pkfile = 'path.pickle'
+    with open(evt_pkfile, 'rb') as f:
+        ShoppingDict = pickle.load(f)
+        
+    savepath = ""
+    
+    back_camera = ShoppingDict["backCamera"]["cameraType"]        
+    back_yrt = ShoppingDict["backCamera"]["yoloResnetTracker"]
+    front_camera = ShoppingDict["frontCamera"]["cameraType"] 
+    front_yrt = ShoppingDict["frontCamera"]["yoloResnetTracker"]
+    yrts = [(back_camera, back_yrt), (front_camera, front_yrt)]
+      
+    
+    shopping_event = ShoppingEvent_()    
+    shopping_event.eventPath = ShoppingDict["eventPath"]
+    shopping_event.eventName = ShoppingDict["eventName"]
+    shopping_event.barcode = ShoppingDict["barcode"]
+    
+    yrtDict = {}
+    event_tracks = []
+    for camera_type, yrtOut in yrts:
+        '''
+        inputs: 
+            yrtOut
+            camera_type
+        outputs:
+            CameraEvent
+        '''
+        
+        camera_event = CameraEvent_()
+        
+
+        
+        '''================= 4. tracking ================='''
+        '''(1) 生成用于 tracking 模块的 boxes、feats'''  
+        bboxes = np.empty((0, 6), dtype=np.float64)
+        trackerboxes = np.empty((0, 9), dtype=np.float64)
+        trackefeats = {}
+        for frameDict in yrtOut:            
+            tboxes = frameDict["tboxes"]
+            ffeats = frameDict["feats"]
+            
+            boxes = frameDict["bboxes"]
+            bboxes = np.concatenate((bboxes, np.array(boxes)), axis=0)
+            trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)), axis=0)
+            for i in range(len(tboxes)):
+                fid, bid = int(tboxes[i, 7]), int(tboxes[i, 8])
+                trackefeats.update({f"{fid}_{bid}": ffeats[f"{fid}_{bid}"]})
+        
+
+        '''(2) tracking, 后摄'''
+        if CameraEvent["cameraType"] == "back":
+            vts = doBackTracks(trackerboxes, trackefeats)
+            vts.classify()
+            event_tracks.append(("back", vts))
+            
+            
+            
+            camera_event.camera_type = camera_type
+            camera_event.yoloResnetTracker = yrtOut
+            camera_event.tracking = vts
+            camera_event.videoPath = ShoppingDict["backCamera"]["videoPath"]  
+            camera_event.imagePaths =  ShoppingDict["backCamera"]["imagePaths"] 
+            shopping_event.backCamera = camera_event
+            
+            yrtDict["backyrt"] = yrtOut
+        
+        '''(2) tracking, 前摄'''    
+        if  CameraEvent["cameraType"] == "front":
+            vts = doFrontTracks(trackerboxes, trackefeats)
+            vts.classify()
+            event_tracks.append(("front", vts))
+            
+            camera_event.camera_type = camera_type
+            camera_event.yoloResnetTracker = yrtOut
+            camera_event.tracking = vts
+            camera_event.videoPath = ShoppingDict["frontCamera"]["videoPath"]  
+            camera_event.imagePaths =  ShoppingDict["frontCamera"]["imagePaths"] 
+            shopping_event.backCamera = camera_event
+            
+            yrtDict["frontyrt"] = yrtOut
+    
+    
+    name = Path(evt_pkfile).stem
+    pf_path = os.path.join(savepath, name+"_new.pickle")
+    with open(str(pf_path), 'wb') as f:
+        pickle.dump(shopping_event, f)
+        
+        
+        
+    illus = [None, None]
+    for CamerType, vts in event_tracks:
+        if len(vts.tracks)==0: continue
+        
+        if CamerType == 'front':
+            edgeline = cv2.imread("./tracking/shopcart/cart_tempt/board_ftmp_line.png")
+            
+            h, w = edgeline.shape[:2]
+            # nh, nw = h//2, w//2
+            # edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
+            
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
+            illus[0] = img_tracking
+
+            plt = plot_frameID_y2(vts)
+            plt.savefig(os.path.join(savepath_pipeline, "front_y2.png"))
+            
+        if CamerType == 'back':
+            edgeline = cv2.imread("./tracking/shopcart/cart_tempt/edgeline.png")
+            
+            h, w = edgeline.shape[:2]
+            # nh, nw = h//2, w//2
+            # edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
+            
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
+            illus[1] = img_tracking
+        
+
+
+
+
+
+
+
+
+
+
+if __name__ == "__main__": 
+    main()