python跑yolov5报错，好像是标签和图片的问题，这标签是直接从labelme弄标的好像没错吧
```python
D:\ad\envs\pytorch\python.exe D:/pythonProject2/yolov5-5.0/train.py
github: skipping check (not a git repository)
YOLOv5 2021-4-12 torch 1.11.0+cu113 CUDA:0 (NVIDIA GeForce RTX 2060, 6143.6875MB)
Namespace(weights='weights/yolov5s.pt', cfg='models/yolov5_hat.yaml', data='data/person.yaml', hyp='data/hyp.scratch.yaml', epochs=300, batch_size=16, img_size=[640, 640], rect=False, resume=False, nosave=False, notest=False, noautoanchor=False, evolve=False, bucket='', cache_images=False, image_weights=False, device='', multi_scale=False, single_cls=False, adam=False, sync_bn=False, local_rank=-1, workers=0, project='runs/train', entity=None, name='exp', exist_ok=False, quad=False, linear_lr=False, labels_smoothing=0.0, upload_dataset=False, bbox_interval=-1, save_period=-1, artifact_alias='latest', world_size=1, global_rank=-1, save_dir='runs\\train\\exp18', total_batch_size=16)
tensorboard: Start with 'tensorboard --logdir runs/train', view at http://localhost:6006/
hyperparameters: lr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0
wandb: Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)
from n params module arguments
0 -1 1 3520 models.common.Focus [3, 32, 3]
1 -1 1 18560 models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 models.common.C3 [64, 64, 1]
3 -1 1 73984 models.common.Conv [64, 128, 3, 2]
4 -1 1 156928 models.common.C3 [128, 128, 3]
5 -1 1 295424 models.common.Conv [128, 256, 3, 2]
6 -1 1 625152 models.common.C3 [256, 256, 3]
7 -1 1 1180672 models.common.Conv [256, 512, 3, 2]
8 -1 1 656896 models.common.SPP [512, 512, [5, 9, 13]]
9 -1 1 1182720 models.common.C3 [512, 512, 1, False]
10 -1 1 131584 models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 models.common.Concat [1]
13 -1 1 361984 models.common.C3 [512, 256, 1, False]
14 -1 1 33024 models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 models.common.Concat [1]
17 -1 1 90880 models.common.C3 [256, 128, 1, False]
18 -1 1 147712 models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 models.common.Concat [1]
20 -1 1 296448 models.common.C3 [256, 256, 1, False]
21 -1 1 590336 models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 models.common.Concat [1]
23 -1 1 1182720 models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 21576 models.yolo.Detect [3, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
D:\ad\envs\pytorch\lib\site-packages\torch\functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:2228.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
Model Summary: 283 layers, 7068936 parameters, 7068936 gradients, 16.5 GFLOPS
Transferred 308/362 items from weights/yolov5s.pt
Scaled weight_decay = 0.0005
Optimizer groups: 62 .bias, 62 conv.weight, 59 other
train: Scanning 'D:\pythonProject2\yolov5-5.0\VOCdevkit\imges\train.cache' images and labels... 0 found, 10 missing, 0 empty, 0 corrupted: 100%|██████████| 10/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "D:\pythonProject2\yolov5-5.0\train.py", line 543, in <module>
train(hyp, opt, device, tb_writer)
File "D:\pythonProject2\yolov5-5.0\train.py", line 189, in train
dataloader, dataset = create_dataloader(train_path, imgsz, batch_size, gs, opt,
File "D:\pythonProject2\yolov5-5.0\utils\datasets.py", line 63, in create_dataloader
dataset = LoadImagesAndLabels(path, imgsz, batch_size,
File "D:\pythonProject2\yolov5-5.0\utils\datasets.py", line 396, in __init__
assert nf > 0 or not augment, f'{prefix}No labels in {cache_path}. Can not train without labels. See {help_url}'
AssertionError: train: No labels in D:\pythonProject2\yolov5-5.0\VOCdevkit\imges\train.cache. Can not train without labels. See https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data
进程已结束，退出代码为 1
路径也没问题呀
train: D:/pythonProject2/yolov5-5.0/VOCdevkit/imges/train # 16551 images
val: D:/pythonProject2/yolov5-5.0/VOCdevkit/imges/val # 4952 images
