(yolov8) D:\wenxvn\vsc_path>yolo task=detect mode=train model=./yolov8n.pt data=yolo-bvn.yaml epochs=30 workers=1 batch=16
Ultralytics 8.3.197 Python-3.9.23 torch-2.8.0+cu129 CUDA:0 (NVIDIA GeForce RTX 4060 Laptop GPU, 8188MiB)
engine\trainer: agnostic_nms=False, amp=True, augment=False, auto_augment=randaugment, batch=16, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=yolo-bvn.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=30, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=./yolov8n.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=train5, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=D:\wenxvn\vsc_path\runs\detect\train5, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=1, workspace=None
Traceback (most recent call last):
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\engine\trainer.py", line 631, in get_dataset
data = check_det_dataset(self.args.data)
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\data\utils.py", line 427, in check_det_dataset
raise SyntaxError(emojis(f"{dataset} key missing ❌.\n either 'names' or 'nc' are required in all data YAMLs."))
SyntaxError: yolo-bvn.yaml key missing .
either 'names' or 'nc' are required in all data YAMLs.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\mini\envs\yolov8\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\mini\envs\yolov8\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\mini\envs\yolov8\Scripts\yolo.exe\__main__.py", line 6, in <module>
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\cfg\__init__.py", line 991, in entrypoint
getattr(model, mode)(**overrides) # default args from model
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\engine\model.py", line 795, in train
self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks)
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\models\yolo\detect\train.py", line 66, in __init__
super().__init__(cfg, overrides, _callbacks)
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\engine\trainer.py", line 157, in __init__
self.data = self.get_dataset()
File "C:\Users\10556\Desktop\ultralytics-8.3.197\ultralytics\engine\trainer.py", line 635, in get_dataset
raise RuntimeError(emojis(f"Dataset '{clean_url(self.args.data)}' error ❌ {e}")) from e
RuntimeError: Dataset 'yolo-bvn.yaml' error yolo-bvn.yaml key missing .
either 'names' or 'nc' are required in all data YAMLs.
本文介绍了解决Visual C++ 2012中出现的“Required file tracker.exe is missing”错误的方法。通过修改项目文件xxxx.vcxproj中的配置，设置TrackFileAccess为false，成功解决了该问题。
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