在加载完模型后报错

[jinghongying]

你好，请问我在训练加载完模型后，遇到了下面的错误，是哪一步出现了问题呢 Scaled weight_decay = 0.0005 optimizer: SGD with parameter groups 63 weight, 73 weight (no decay), 72 bias train: Scanning 'datasets\datasets_track\train' images and labels...4557 found, 0 missing, 0 empty, 4557 corrupted: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████| 4557/4557 [00:05<00:00, 769.07it/s] train: WARNING: datasets\datasets_track\images\train\000001.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000002.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000003.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000004.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000005.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000006.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000007.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000009.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000010.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000011.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000012.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000013.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000014.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000015.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000017.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000018.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000019.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: WARNING: datasets\datasets_track\images\train\000020.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>) train: train: New cache created: datasets\datasets_track\train.cache Traceback (most recent call last): File "D:\Yolov8_obb_Prune_Track-latest\train.py", line 672, in main(opt) File "D:\Yolov8_obb_Prune_Track-latest\train.py", line 569, in main train(opt.hyp, opt, device, callbacks) File "D:\Yolov8_obb_Prune_Track-latest\train.py", line 222, in train train_loader, dataset = create_dataloader(train_path, imgsz, batch_size // WORLD_SIZE, gs, names, single_cls, File "D:\Yolov8_obb_Prune_Track-latest\utils\datasets.py", line 101, in create_dataloader dataset = LoadImagesAndLabels(path, names, imgsz, batch_size, File "D:\Yolov8_obb_Prune_Track-latest\utils\datasets.py", line 451, in init labels, shapes, self.segments = zip(*cache.values()) ValueError: not enough values to unpack (expected 3, got 0) 这是我的数据集分布和标签文件，