增加了单帧入侵判断及yoloV10

tracking/dotrack/dotracks_back.py

@@ -7,9 +7,19 @@ Created on Mon Mar  4 18:36:31 2024
 import numpy as np
 import cv2
 import copy
-from tracking.utils.mergetrack import track_equal_track
-from scipy.spatial.distance import cdist
+import sys
 from pathlib import Path
+
+FILE = Path(__file__).resolve()
+ROOT = FILE.parents[2]  # YOLOv5 root directory
+if str(ROOT) not in sys.path:
+    sys.path.append(str(ROOT))
+
+from tracking.utils.mergetrack import track_equal_track
+
+
+from scipy.spatial.distance import cdist
+
 curpath = Path(__file__).resolve().parents[0]
 curpath = Path(curpath)
 parpath = curpath.parent

tracking/tracking_pipeline.py

@@ -11,170 +11,222 @@ import pickle
 import numpy as np
 from pathlib import Path
 from scipy.spatial.distance import cdist
+import copy
 
-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
+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
 
 
+def get_trail(ShoppingDict, ppath):
+    
+    evtname = ShoppingDict["eventName"]
+    
+    back_yrt = ShoppingDict["backCamera"]["yoloResnetTracker"]
+    front_yrt = ShoppingDict["frontCamera"]["yoloResnetTracker"]
+    
+    back_vts = ShoppingDict["frontCamera"]["tracking"]
+    front_vts = ShoppingDict["backCamera"]["tracking"]
+    
+    
+    event_tracks = [("back", back_yrt, back_vts), ("front", front_yrt, front_vts)]
+    
+    
+    savepath = ppath / "alltrail" 
+    if not savepath.exists():
+        savepath.mkdir()
+    
+    savepath = str(savepath)
+    evtime = evtname[:15]
+        
+    illus = [None, None]
+    for camera_type, yrtOut, vts in event_tracks:
+        if len(vts.Residual)==1: continue
+        
+        if camera_type == 'front':
+            edgeline = cv2.imread("./shopcart/cart_tempt/board_ftmp_line.png")
+            
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
+            illus[0] = img_tracking
 
-
-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 = []
+            plt = plot_frameID_y2(vts)
+            plt.savefig(os.path.join(savepath, f"{evtime}_front.png"))
+            
+        if camera_type == 'back':
+            edgeline = cv2.imread("./shopcart/cart_tempt/edgeline.png")
+ 
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
+            illus[1] = img_tracking
+            
+    illus = [im for im in illus if im is not None]
+    if len(illus):
+        img_cat = np.concatenate(illus, axis = 1)
+        if len(illus)==2:
+            H, W = img_cat.shape[:2]
+            cv2.line(img_cat, (int(W/2), 0), (int(W/2), int(H)), (128, 128, 255), 3)
+            
+        trajpath = os.path.join(savepath, f"{evtime}.png")
+        cv2.imwrite(trajpath, img_cat)
+        
+        return evtime
+    
+    return None
+    
+    
     
     
 
 
 
-def main():
+
+
+
+def track_opt(ShoppingDict, ppath):
     '''
     将一个对象读取，修改其中一个属性
     
     '''
+    evtname = ShoppingDict["eventName"]
     
+    shopping = copy.deepcopy(ShoppingDict)
     
-    evt_pkfile = 'path.pickle'
-    with open(evt_pkfile, 'rb') as f:
-        ShoppingDict = pickle.load(f)
-        
-    savepath = ""
-    
+    ## only need to init item: tracking for each Camera
+    shopping["frontCamera"]["tracking"] = []
+    shopping["backCamera"]["tracking"] = []
+
     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 ================='''
+    errtrail = ''
+    for camera_type, yrtOut in yrts:        
+        '''================= 1. tracking ================='''
         '''(1) 生成用于 tracking 模块的 boxes、feats'''  
-        bboxes = np.empty((0, 6), dtype=np.float64)
+        # 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)
+            # 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":
+        if camera_type == "back":
             vts = doBackTracks(trackerboxes, trackefeats)
             vts.classify()
-            event_tracks.append(("back", vts))
+            shopping["backCamera"]["tracking"] = 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":
+            if len(vts.Residual)!=1:
+                errtrail = evtname
+
+        '''(3) tracking, 前摄'''    
+        if camera_type == "front":
             vts = doFrontTracks(trackerboxes, trackefeats)
             vts.classify()
-            event_tracks.append(("front", vts))
+            shopping["frontCamera"]["tracking"] = 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
+            if len(vts.Residual)!=1:
+                errtrail = evtname
+
+        event_tracks.append((camera_type, yrtOut, vts))
+
     
+    pckpath = ppath / "track_optim"
+    if not pckpath.exists():
+        pckpath.mkdir()
+        
+    fpath = pckpath / "{}_new.pickle".format(evtname)
+    with open(str(fpath), 'wb') as f:
+        pickle.dump(shopping, f)
+     
     
-    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)
-        
-        
+    savepath = ppath / "yolos_tracking" / evtname
         
     illus = [None, None]
-    for CamerType, vts in event_tracks:
+    for camera_type, yrtOut, vts in event_tracks:
         if len(vts.tracks)==0: continue
         
-        if CamerType == 'front':
-            edgeline = cv2.imread("./tracking/shopcart/cart_tempt/board_ftmp_line.png")
+        if camera_type == 'front':
+            edgeline = cv2.imread("./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)
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
             illus[0] = img_tracking
 
             plt = plot_frameID_y2(vts)
-            plt.savefig(os.path.join(savepath_pipeline, "front_y2.png"))
+            plt.savefig(os.path.join(savepath, "front_y2_new.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)
+        if camera_type == 'back':
+            edgeline = cv2.imread("./shopcart/cart_tempt/edgeline.png")
+ 
+            img_tracking = draw_all_trajectories(vts, edgeline, savepath, camera_type, draw5p=False)
             illus[1] = img_tracking
+            
+    illus = [im for im in illus if im is not None]
+    if len(illus):
+        img_cat = np.concatenate(illus, axis = 1)
+        if len(illus)==2:
+            H, W = img_cat.shape[:2]
+            cv2.line(img_cat, (int(W/2), 0), (int(W/2), int(H)), (128, 128, 255), 3)
+            
+        trajpath = os.path.join(savepath, "trajectory_new.png")
+        cv2.imwrite(trajpath, img_cat)
+        
+    return errtrail
         
 
-
-
-
-
-
-
-
+def main():
+    # evttypes = ["single_event_V10", "single_event_V5", "performence_V10", "performence_V5"]
+    evttypes = ["single_event_V10"]
+    
+    k = 0
+    error_trail = []
+    for evttype in evttypes:
+        ppath = Path("/home/wqg/dataset/pipeline/yrt/{}".format(evttype))
+    
+        pkpath =  ppath / "shopping_pkl"
+        for fp in pkpath.iterdir():
+            # fp = pkpath / "{}.pickle".format("20250305-152917-635_6970209860221_6970209860221")
+            print(fp)
+            
+            if fp.suffix != '.pickle': continue
+            with open(str(fp), 'rb') as f:
+                ShoppingDict = pickle.load(f)
+                
+            # errtrail = track_opt(ShoppingDict, ppath)
+            # error_trail.append(errtrail)
+            
+            errtrail = get_trail(ShoppingDict, ppath)
+            if errtrail is not None:
+                error_trail.append(errtrail)
+            
+            # k+=1
+            # if k==100:
+            #     break
+            
+    errfile = ppath / 'error_trail.txt'
+    with open(errfile, 'w', encoding='utf-8') as f:
+        for line in error_trail:
+            f.write(line + '\n')
+            
+            
 
 
 if __name__ == "__main__": 
-    main()
+    main()
+    
+    
+    
+    
+    
+    
+