I keep getting this error, but there is no problem with the numpy version and it is also compatible with pytorch
root@autodl-container-e3534eb58d-3a694e74:~# yolo detect train data = /tmp/pycharm_project_720/datasets.yaml model = /tmp/pycharm_project_720/yolo11n.pt epochs = 10 imgsz = 640 device = 0
Ultralytics 8.3.32 🚀 Python-3.8.10 torch-2.0.0+cu118 CUDA:0 (NVIDIA GeForce RTX 4090, 24210MiB)
engine/trainer: task=detect, mode=train, model=/tmp/pycharm_project_720/yolo11n.pt, data=/tmp/pycharm_project_720/datasets.yaml, epochs=10, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=0, workers=8, project=None, name=train3, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, 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, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train3
Overriding model.yaml nc=80 with nc=2
from n params module arguments
0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2]
1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2]
2 -1 1 6640 ultralytics.nn.modules.block.C3k2 [32, 64, 1, False, 0.25]
3 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2]
4 -1 1 26080 ultralytics.nn.modules.block.C3k2 [64, 128, 1, False, 0.25]
5 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
6 -1 1 87040 ultralytics.nn.modules.block.C3k2 [128, 128, 1, True]
7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2]
8 -1 1 346112 ultralytics.nn.modules.block.C3k2 [256, 256, 1, True]
9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5]
10 -1 1 249728 ultralytics.nn.modules.block.C2PSA [256, 256, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1]
13 -1 1 111296 ultralytics.nn.modules.block.C3k2 [384, 128, 1, False]
14 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
15 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1]
16 -1 1 32096 ultralytics.nn.modules.block.C3k2 [256, 64, 1, False]
17 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2]
18 [-1, 13] 1 0 ultralytics.nn.modules.conv.Concat [1]
19 -1 1 86720 ultralytics.nn.modules.block.C3k2 [192, 128, 1, False]
20 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
21 [-1, 10] 1 0 ultralytics.nn.modules.conv.Concat [1]
22 -1 1 378880 ultralytics.nn.modules.block.C3k2 [384, 256, 1, True]
23 [16, 19, 22] 1 431062 ultralytics.nn.modules.head.Detect [2, [64, 128, 256]]
YOLO11n summary: 319 layers, 2,590,230 parameters, 2,590,214 gradients, 6.4 GFLOPs
Transferred 448/499 items from pretrained weights
TensorBoard: Start with 'tensorboard --logdir runs/detect/train3', view at http://localhost:6006/
Freezing layer 'model.23.dfl.conv.weight'
AMP: running Automatic Mixed Precision (AMP) checks...
Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n.pt to 'yolo11n.pt'...
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.35M/5.35M [06:12<00:00, 15.1kB/s]
AMP: checks passed ✅
Traceback (most recent call last):
File "/root/miniconda3/bin/yolo", line 8, in <module>
sys.exit(entrypoint())
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/cfg/__init__.py", line 969, in entrypoint
getattr(model, mode)(**overrides) # default args from model
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/engine/model.py", line 802, in train
self.trainer.train()
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/engine/trainer.py", line 207, in train
self._do_train(world_size)
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/engine/trainer.py", line 322, in _do_train
self._setup_train(world_size)
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/engine/trainer.py", line 286, in _setup_train
self.train_loader = self.get_dataloader(self.trainset, batch_size=batch_size, rank=LOCAL_RANK, mode="train")
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/models/yolo/detect/train.py", line 49, in get_dataloader
dataset = self.build_dataset(dataset_path, mode, batch_size)
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/models/yolo/detect/train.py", line 43, in build_dataset
return build_yolo_dataset(self.args, img_path, batch, self.data, mode=mode, rect=mode == "val", stride=gs)
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/data/build.py", line 87, in build_yolo_dataset
return dataset(
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/data/dataset.py", line 64, in __init__
super().__init__(*args, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/data/base.py", line 74, in __init__
self.labels = self.get_labels()
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/data/dataset.py", line 138, in get_labels
cache, exists = load_dataset_cache_file(cache_path), True # attempt to load a *.cache file
File "/root/miniconda3/lib/python3.8/site-packages/ultralytics/data/utils.py", line 659, in load_dataset_cache_file
cache = np.load(str(path), allow_pickle=True).item() # load dict
File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/npyio.py", line 432, in load
return format.read_array(fid, allow_pickle=allow_pickle,
File "/root/miniconda3/lib/python3.8/site-packages/numpy/lib/format.py", line 792, in read_array
array = pickle.load(fp, **pickle_kwargs)
ModuleNotFoundError: No module named 'numpy._core'