报错：ValueError: invalid literal for int() with base 10: 'Unspecified'

问题
跑YOLOX的时候训练完第一遍评估过程中报出了ValueError: invalid literal for int() with base 10: 'Unspecified'，在Google逛了半天，也没有找到很好的解决方案，希望各位大神能帮帮我
报错内容

Traceback (most recent call last):

  File "D:/Python_project/YOLOX/tools\train.py", line 132, in <module>
    args=(exp, args),
          │    └ Namespace(batch_size=2, cache=True, ckpt='D:\\Python_project\\YOLOX\\weights\\yolox_s.pth', devices=0, dist_backend='nccl', d...
          └ ╒══════════════════╤═════════════════════════════════════════════════════════════════════════════════════════════════════════...

> File "d:\python_project\yolox\yolox\core\launch.py", line 98, in launch
    main_func(*args)
    │          └ (╒══════════════════╤════════════════════════════════════════════════════════════════════════════════════════════════════════...
    └ <function main at 0x0000022A291D9AE8>

  File "D:/Python_project/YOLOX/tools\train.py", line 110, in main
    trainer.train()
    │       └ <function Trainer.train at 0x0000022A29190048>
    └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>

  File "d:\python_project\yolox\yolox\core\trainer.py", line 72, in train
    self.train_in_epoch()
    │    └ <function Trainer.train_in_epoch at 0x0000022A2919FAE8>
    └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>

  File "d:\python_project\yolox\yolox\core\trainer.py", line 82, in train_in_epoch
    self.after_epoch()
    │    └ <function Trainer.after_epoch at 0x0000022A291B8730>
    └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>

  File "d:\python_project\yolox\yolox\core\trainer.py", line 207, in after_epoch
    self.evaluate_and_save_model()
    │    └ <function Trainer.evaluate_and_save_model at 0x0000022A291B89D8>
    └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>

  File "d:\python_project\yolox\yolox\core\trainer.py", line 303, in evaluate_and_save_model
    evalmodel, self.evaluator, self.is_distributed
    │          │    │          │    └ False
    │          │    │          └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>
    │          │    └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000022A2B48B7F0>
    │          └ <yolox.core.trainer.Trainer object at 0x0000022A291DAD30>
    └ YOLOX(
        (backbone): YOLOPAFPN(
          (backbone): CSPDarknet(
            (stem): Focus(
              (conv): BaseConv(
                (conv): ...

  File "d:\python_project\yolox\yolox\exp\yolox_base.py", line 284, in eval
    return evaluator.evaluate(model, is_distributed, half)
           │         │        │      │               └ False
           │         │        │      └ False
           │         │        └ YOLOX(
           │         │            (backbone): YOLOPAFPN(
           │         │              (backbone): CSPDarknet(
           │         │                (stem): Focus(
           │         │                  (conv): BaseConv(
           │         │                    (conv): ...
           │         └ <function VOCEvaluator.evaluate at 0x0000022A291A8840>
           └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000022A2B48B7F0>

  File "d:\python_project\yolox\yolox\evaluators\voc_evaluator.py", line 128, in evaluate
    eval_results = self.evaluate_prediction(data_list, statistics)
                   │    │                   │          └ tensor([27.5073,  0.3150, 60.0000], device='cuda:0')
                   │    │                   └ {0: (tensor([[ 6.0443e+02,  2.8392e+02,  7.4877e+02,  6.5690e+02],
                   │    │                             [ 7.8033e+02,  2.6140e+02,  9.5504e+02,  6.5532e+0...
                   │    └ <function VOCEvaluator.evaluate_prediction at 0x0000022A291A8950>
                   └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000022A2B48B7F0>

  File "d:\python_project\yolox\yolox\evaluators\voc_evaluator.py", line 206, in evaluate_prediction
    all_boxes, tempdir
    │          └ 'C:\\Users\\WINDOW~1\\AppData\\Local\\Temp\\tmpvmnqyb48'
    └ [[array([[ 6.04426941e+02,  2.83921021e+02,  7.48771362e+02,
               6.56901184e+02,  9.64037299e-01],
             [ 7.80328064e+...

  File "d:\python_project\yolox\yolox\data\datasets\voc.py", line 266, in evaluate_detections
    mAP = self._do_python_eval(output_dir, iou)
          │    │               │           └ 0.5
          │    │               └ 'C:\\Users\\WINDOW~1\\AppData\\Local\\Temp\\tmpvmnqyb48'
          │    └ <function VOCDetection._do_python_eval at 0x0000022A291B8400>
          └ <yolox.data.datasets.voc.VOCDetection object at 0x0000022A010D7DA0>

  File "d:\python_project\yolox\yolox\data\datasets\voc.py", line 338, in _do_python_eval
    use_07_metric=use_07_metric,
                  └ True

  File "d:\python_project\yolox\yolox\evaluators\voc_eval.py", line 93, in voc_eval
    recs[imagename] = parse_rec(annopath.format(imagename))
    │    │            │         │        │      └ '102'
    │    │            │         │        └ <method 'format' of 'str' objects>
    │    │            │         └ 'd:\\python_project\\yolox\\datasets\\VOCdeckit\\VOC2007\\Annotations/{:s}.xml'
    │    │            └ <function parse_rec at 0x0000022A291A82F0>
    │    └ '102'
    └ {}

  File "d:\python_project\yolox\yolox\evaluators\voc_eval.py", line 23, in parse_rec
    obj_struct["truncated"] = int(obj.find("truncated").text)
    │                             │   └ <method 'find' of 'xml.etree.ElementTree.Element' objects>
    │                             └ <Element 'object' at 0x0000022A2B4CED68>
    └ {'name': 'person', 'pose': 'Unspecified'}

ValueError: invalid literal for int() with base 10: 'Unspecified'

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