YOLOX训练报错：FileNotFoundError: [Errno 2] No such file or directory: ‘yumi102.xml‘&the best AP is 0.00

本文链接：https://blog.youkuaiyun.com/ELSA001/article/details/120919823

问题已解决，请查看以下文章：
https://blog.youkuaiyun.com/ELSA001/article/details/120918082?spm=1001.2014.3001.5501

刚刚在训练yolox_s模型的时候，遇到了如下错误：

2021-10-23 10:19:46 | ERROR    | yolox.core.launch:98 - An error has been caught in function 'launch', process 'MainProcess' (44024), thread 'MainThread' (540):
FileNotFoundError: [Errno 2] No such file or directory: 'yumi102.xml'

提示没有找到这个文件：
在这里插入图片描述

但问题是我的文件里面有的呀：

并且还报了：

2021-10-23 10:19:46 | INFO     | yolox.core.trainer:183 - Training of experiment is done and the best AP is 0.00

the best AP is 0.00

AP = 0
这个是不是一个很大的问题呢？
完整报错信息如下：

2021-10-23 10:19:46 | INFO     | yolox.core.trainer:183 - Training of experiment is done and the best AP is 0.00
2021-10-23 10:19:46 | ERROR    | yolox.core.launch:98 - An error has been caught in function 'launch', process 'MainProcess' (44024), thread 'MainThread' (540):
Traceback (most recent call last):

  File "tools\train.py", line 125, in <module>
    launch(
    └ <function launch at 0x0000026C80EE7550>

> File "e:\yolox\yolox\core\launch.py", line 98, in launch
    main_func(*args)
    │          └ (╒══════════════════╤════════════════════════════════════════════════════════════════════════════════════════════════════════...
    └ <function main at 0x0000026C82F6F3A0>

  File "tools\train.py", line 110, in main
    trainer.train()
    │       └ <function Trainer.train at 0x0000026C822CFC10>
    └ <yolox.core.trainer.Trainer object at 0x0000026C83007A30>

  File "e:\yolox\yolox\core\trainer.py", line 72, in train
    self.train_in_epoch()
    │    └ <function Trainer.train_in_epoch at 0x0000026C82F3D550>
    └ <yolox.core.trainer.Trainer object at 0x0000026C83007A30>

  File "e:\yolox\yolox\core\trainer.py", line 82, in train_in_epoch
    self.after_epoch()
    │    └ <function Trainer.after_epoch at 0x0000026C82F4BB80>
    └ <yolox.core.trainer.Trainer object at 0x0000026C83007A30>

  File "e:\yolox\yolox\core\trainer.py", line 207, in after_epoch
    self.evaluate_and_save_model()
    │    └ <function Trainer.evaluate_and_save_model at 0x0000026C82F4BE50>
    └ <yolox.core.trainer.Trainer object at 0x0000026C83007A30>

  File "e:\yolox\yolox\core\trainer.py", line 302, in evaluate_and_save_model
    ap50_95, ap50, summary = self.exp.eval(
                             │    │   └ <function Exp.eval at 0x0000026C82F6F9D0>
                             │    └ ╒══════════════════╤═════════════════════════════════════════════════════════════════════════════════════════════════════════...
                             └ <yolox.core.trainer.Trainer object at 0x0000026C83007A30>

  File "e:\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 0x0000026C82F3DC10>
           └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000026C8E4A9A00>

  File "e:\yolox\yolox\evaluators\voc_evaluator.py", line 128, in evaluate
    eval_results = self.evaluate_prediction(data_list, statistics)
                   │    │                   │          └ tensor([ 0.6692,  1.2153, 30.0000], device='cuda:0')
                   │    │                   └ {0: (tensor([[ 65.5363, 148.8881, 314.1370, 348.9427],
                   │    │                             [102.8350, -30.9026, 548.5400, 365.2217],
                   │    │                             [ 46.0711, -...
                   │    └ <function VOCEvaluator.evaluate_prediction at 0x0000026C82F3DD30>
                   └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000026C8E4A9A00>

  File "e:\yolox\yolox\evaluators\voc_evaluator.py", line 205, in evaluate_prediction
    mAP50, mAP70 = self.dataloader.dataset.evaluate_detections(
                   │    │          │       └ <function VOCDetection.evaluate_detections at 0x0000026C82F4B670>
                   │    │          └ <yolox.data.datasets.voc.VOCDetection object at 0x0000026C8E4A9B20>
                   │    └ <torch.utils.data.dataloader.DataLoader object at 0x0000026C8E4A99D0>
                   └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x0000026C8E4A9A00>

  File "e:\yolox\yolox\data\datasets\voc.py", line 271, in evaluate_detections
    mAP = self._do_python_eval(output_dir, iou)
          │    │               │           └ 0.5
          │    │               └ 'C:\\Users\\ASUS\\AppData\\Local\\Temp\\tmp3b5fh8xp'
          │    └ <function VOCDetection._do_python_eval at 0x0000026C82F4B820>
          └ <yolox.data.datasets.voc.VOCDetection object at 0x0000026C8E4A9B20>

  File "e:\yolox\yolox\data\datasets\voc.py", line 335, in _do_python_eval
    rec, prec, ap = voc_eval(
                    └ <function voc_eval at 0x0000026C82F3DE50>

  File "e:\yolox\yolox\evaluators\voc_eval.py", line 93, in voc_eval
    recs[imagename] = parse_rec(annopath.format(imagename))
    │    │            │         │        │      └ 'yumi102'
    │    │            │         │        └ <method 'format' of 'str' objects>
    │    │            │         └ '{:s}.xml'
    │    │            └ <function parse_rec at 0x0000026C82F3D700>
    │    └ 'yumi102'
    └ {}

  File "e:\yolox\yolox\evaluators\voc_eval.py", line 17, in parse_rec
    tree = ET.parse(filename)
           │  │     └ 'yumi102.xml'
           │  └ <function parse at 0x0000026C80DE3C10>
           └ <module 'xml.etree.ElementTree' from 'E:\\Anaconda3\\envs\\torch_G\\lib\\xml\\etree\\ElementTree.py'>

  File "E:\Anaconda3\envs\torch_G\lib\xml\etree\ElementTree.py", line 1202, in parse
    tree.parse(source, parser)
    │    │     │       └ None
    │    │     └ 'yumi102.xml'
    │    └ <function ElementTree.parse at 0x0000026C80DDACA0>
    └ <xml.etree.ElementTree.ElementTree object at 0x0000026C8CE359A0>

  File "E:\Anaconda3\envs\torch_G\lib\xml\etree\ElementTree.py", line 584, in parse
    source = open(source, "rb")
                  └ 'yumi102.xml'

FileNotFoundError: [Errno 2] No such file or directory: 'yumi102.xml'