modify the event pickle file
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@ -76,7 +76,7 @@ def attempt_load(weights, device=None, inplace=True, fuse=True):
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model = Ensemble()
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for w in weights if isinstance(weights, list) else [weights]:
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ckpt = torch.load(attempt_download(w), map_location=device) # load
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ckpt = torch.load(attempt_download(w), map_location=device, weights_only=False) # load
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ckpt = (ckpt.get('ema') or ckpt['model']).to(device).float() # FP32 model
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# Model compatibility updates
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pipeline.py
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pipeline.py
@ -114,6 +114,7 @@ def pipeline(
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"backCamera": {},
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"one2n": [] #
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}
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yrtDict = {}
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procpath = Path(eventpath).joinpath('process.data')
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@ -158,11 +159,23 @@ def pipeline(
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'''================= 3. Yolo + Resnet + Tracker ================='''
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optdict["source"] = vpath
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optdict["save_dir"] = savepath_pipeline_imgs
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optdict["save_dir"] = savepath_pipeline_imgs
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optdict["is_save_img"] = False
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optdict["is_save_video"] = True
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yrtOut = yolo_resnet_tracker(**optdict)
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CameraEvent["yoloResnetTracker"] = yrtOut
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yrtOut_save = []
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for frdict in yrtOut:
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fr_dict = {}
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for k, v in frdict.items():
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if k != "imgs":
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fr_dict[k]=v
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yrtOut_save.append(fr_dict)
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CameraEvent["yoloResnetTracker"] = yrtOut_save
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# CameraEvent["yoloResnetTracker"] = yrtOut
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'''================= 4. tracking ================='''
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'''(1) 生成用于 tracking 模块的 boxes、feats'''
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@ -189,6 +202,8 @@ def pipeline(
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CameraEvent["tracking"] = vts
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ShoppingDict["backCamera"] = CameraEvent
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yrtDict["backyrt"] = yrtOut
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'''(2) tracking, 前摄'''
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if CameraEvent["cameraType"] == "front":
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@ -198,6 +213,8 @@ def pipeline(
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CameraEvent["tracking"] = vts
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ShoppingDict["frontCamera"] = CameraEvent
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yrtDict["frontyrt"] = yrtOut
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'''========================== 保存模块 ================================='''
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'''(1) 保存 ShoppingDict 事件'''
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@ -208,10 +225,14 @@ def pipeline(
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for CamerType, vts in event_tracks:
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if len(vts.tracks)==0: continue
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if CamerType == 'front':
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yolos = ShoppingDict["frontCamera"]["yoloResnetTracker"]
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# yolos = ShoppingDict["frontCamera"]["yoloResnetTracker"]
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yolos = yrtDict["frontyrt"]
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ctype = 1
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if CamerType == 'back':
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yolos = ShoppingDict["backCamera"]["yoloResnetTracker"]
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# yolos = ShoppingDict["backCamera"]["yoloResnetTracker"]
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yolos = yrtDict["backyrt"]
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ctype = 0
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imgdict, featdict, simidict = {}, {}, {}
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@ -269,10 +290,10 @@ def main():
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函数:pipeline(),遍历事件文件夹,选择类型 image 或 video,
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'''
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parmDict = {}
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evtdir = r"D:\works\后台回传数据"
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evtdir = r"../dataset/backend_20250310"
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parmDict["SourceType"] = "video" # video, image
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parmDict["savepath"] = r"D:\works\results"
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parmDict["weights"] = r'D:\DetectTracking\ckpts\best_cls10_0906.pt'
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parmDict["savepath"] = r"../dataset/run"
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parmDict["weights"] = r'./ckpts/best_cls10_0906.pt'
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evtdir = Path(evtdir)
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k, errEvents = 0, []
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@ -280,14 +301,14 @@ def main():
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if item.is_dir():
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# item = evtdir/Path("20250303-103058-074_6914973604223_6914973604223")
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parmDict["eventpath"] = item
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# pipeline(**parmDict)
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try:
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pipeline(**parmDict)
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except Exception as e:
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errEvents.append(str(item))
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# k+=1
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# if k==1:
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# break
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pipeline(**parmDict)
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# try:
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# pipeline(**parmDict)
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# except Exception as e:
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# errEvents.append(str(item))
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k+=1
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if k==1:
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break
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errfile = os.path.join(parmDict["savepath"], f'error_events.txt')
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with open(errfile, 'w', encoding='utf-8') as f:
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@ -311,6 +311,9 @@ def yolo_resnet_tracker(
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h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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else: # stream
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fps, w, h = 25, im0.shape[1], im0.shape[0]
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## for image rotating in dataloader.LoadImages.__next__()
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w, h = im0.shape[1], im0.shape[0]
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vdieo_path = str(Path(vdieo_path).with_suffix('.mp4')) # force *.mp4 suffix on results videos
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vid_writer[i] = cv2.VideoWriter(vdieo_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
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vid_writer[i].write(im0)
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@ -594,6 +597,9 @@ def run(
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h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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else: # stream
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fps, w, h = 30, im0.shape[1], im0.shape[0]
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## for image rotating in dataloader.LoadImages.__next__()
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w, h = im0.shape[1], im0.shape[0]
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save_path = str(Path(save_path).with_suffix('.mp4')) # force *.mp4 suffix on results videos
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vid_writer[i] = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
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vid_writer[i].write(im0)
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@ -132,11 +132,11 @@ class backTrack(Track):
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num_outcart = cv2.countNonZero(isoutcart)
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num_cartboarder = cv2.countNonZero(iscartboarder)
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incart_iou = num_incart/num_temp
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outcart_iou = num_outcart/num_temp
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cartboarder_iou = num_cartboarder/num_temp
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maxbox_iou = maxarea/num_temp
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minbox_iou = minarea/num_temp
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incart_iou = num_incart/(num_temp+1e-6)
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outcart_iou = num_outcart/(num_temp+1e-6)
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cartboarder_iou = num_cartboarder/(num_temp+1e-6)
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maxbox_iou = maxarea/(num_temp+1e-6)
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minbox_iou = minarea/(num_temp+1e-6)
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self.feature_ious = (incart_iou, outcart_iou, cartboarder_iou, maxbox_iou, minbox_iou)
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self.incartrates = incartrates
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