Closed kands-code closed 2 years ago
在训练过程中出现了如下报错:
2021-12-02 08:42:15 | INFO | yolox.evaluators.coco_evaluator:171 - Evaluate in main process... 2021-12-02 08:42:15 | INFO | yolox.evaluators.coco_evaluator:204 - Loading and preparing results... 2021-12-02 08:42:15 | INFO | yolox.evaluators.coco_evaluator:204 - DONE (t=0.01s) 2021-12-02 08:42:15 | INFO | pycocotools.coco:362 - creating index... 2021-12-02 08:42:15 | INFO | pycocotools.coco:362 - index created! 2021-12-02 08:42:15 | INFO | yolox.core.trainer:184 - Training of experiment is done and the best AP is 0.00 2021-12-02 08:42:15 | ERROR | yolox.core.launch:98 - An error has been caught in function 'launch', process 'MainProcess' (8900), thread 'MainThread' (9032): Traceback (most recent call last): File "yolox_tools\train.py", line 132, in <module> args=(exp, args), │ └ Namespace(batch_size=4, cache=False, ckpt='weights/yolox_tiny.pth', devices=1, dist_backend='nccl', dist_url=None, exp_file='... └ ╒══════════════════╤═════════════════════════════════════════════════════════════════════════════════════════════════════════... > File "c:\users\lenovo\genshin_auto_fish\yolox\core\launch.py", line 98, in launch main_func(*args) │ └ (╒══════════════════╤════════════════════════════════════════════════════════════════════════════════════════════════════════... └ <function main at 0x000001780A103DC8> File "yolox_tools\train.py", line 110, in main trainer.train() │ └ <function Trainer.train at 0x0000017810F38CA8> └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> File "c:\users\lenovo\genshin_auto_fish\yolox\core\trainer.py", line 72, in train self.train_in_epoch() │ └ <function Trainer.train_in_epoch at 0x0000017811AFA9D8> └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> File "c:\users\lenovo\genshin_auto_fish\yolox\core\trainer.py", line 82, in train_in_epoch self.after_epoch() │ └ <function Trainer.after_epoch at 0x0000017813870798> └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> File "c:\users\lenovo\genshin_auto_fish\yolox\core\trainer.py", line 207, in after_epoch self.evaluate_and_save_model() │ └ <function Trainer.evaluate_and_save_model at 0x0000017813870A68> └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> File "c:\users\lenovo\genshin_auto_fish\yolox\core\trainer.py", line 303, in evaluate_and_save_model evalmodel, self.evaluator, self.is_distributed │ │ │ │ └ False │ │ │ └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> │ │ └ <yolox.evaluators.coco_evaluator.COCOEvaluator object at 0x000001781B337108> │ └ <yolox.core.trainer.Trainer object at 0x00000178124D8848> └ YOLOX( (backbone): YOLOPAFPN( (backbone): CSPDarknet( (stem): Focus( (conv): BaseConv( (conv): ... File "c:\users\lenovo\genshin_auto_fish\yolox\exp\yolox_base.py", line 288, in eval return evaluator.evaluate(model, is_distributed, half) │ │ │ │ └ False │ │ │ └ False │ │ └ YOLOX( │ │ (backbone): YOLOPAFPN( │ │ (backbone): CSPDarknet( │ │ (stem): Focus( │ │ (conv): BaseConv( │ │ (conv): ... │ └ <function COCOEvaluator.evaluate at 0x0000017813862B88> └ <yolox.evaluators.coco_evaluator.COCOEvaluator object at 0x000001781B337108> File "c:\users\lenovo\genshin_auto_fish\yolox\evaluators\coco_evaluator.py", line 131, in evaluate eval_results = self.evaluate_prediction(data_list, statistics) │ │ │ └ tensor([10.2540, 0.1897, 32.0000], device='cuda:0') │ │ └ [{'image_id': 0, 'category_id': 3, 'bbox': [404.795654296875, 327.560302734375, 276.18157958984375, 106.73675537109375], 'sco... │ └ <function COCOEvaluator.evaluate_prediction at 0x0000017813862CA8> └ <yolox.evaluators.coco_evaluator.COCOEvaluator object at 0x000001781B337108> File "c:\users\lenovo\genshin_auto_fish\yolox\evaluators\coco_evaluator.py", line 212, in evaluate_prediction cocoEval = COCOeval(cocoGt, cocoDt, annType[1]) │ │ │ └ ['segm', 'bbox', 'keypoints'] │ │ └ <pycocotools.coco.COCO object at 0x0000017801300448> │ └ <pycocotools.coco.COCO object at 0x00000178137761C8> └ <class 'yolox.layers.fast_coco_eval_api.COCOeval_opt'> File "D:\anaconda\lib\site-packages\pycocotools\cocoeval.py", line 76, in __init__ self.params = Params(iouType=iouType) # parameters │ │ │ └ 'bbox' │ │ └ <class 'pycocotools.cocoeval.Params'> │ └ {} └ <yolox.layers.fast_coco_eval_api.COCOeval_opt object at 0x00000178017DD6C8> File "D:\anaconda\lib\site-packages\pycocotools\cocoeval.py", line 527, in __init__ self.setDetParams() │ └ <function Params.setDetParams at 0x0000017804179DC8> └ <pycocotools.cocoeval.Params object at 0x0000017812660FC8> File "D:\anaconda\lib\site-packages\pycocotools\cocoeval.py", line 507, in setDetParams self.iouThrs = np.linspace(.5, 0.95, np.round((0.95 - .5) / .05) + 1, endpoint=True) │ │ │ │ └ <function round_ at 0x000001780E00C1F8> │ │ │ └ <module 'numpy' from 'D:\\anaconda\\lib\\site-packages\\numpy\\__init__.py'> │ │ └ <function linspace at 0x000001780E686828> │ └ <module 'numpy' from 'D:\\anaconda\\lib\\site-packages\\numpy\\__init__.py'> └ <pycocotools.cocoeval.Params object at 0x0000017812660FC8> File "<__array_function__ internals>", line 6, in linspace File "D:\anaconda\lib\site-packages\numpy\core\function_base.py", line 120, in linspace num = operator.index(num) │ │ └ 10.0 │ └ <built-in function index> └ <module 'operator' from 'D:\\anaconda\\lib\\operator.py'> TypeError: 'numpy.float64' object cannot be interpreted as an integer
可能是numpy版本的问题，换个版本试试
IrisRainbowNeko
commented
2 years ago IrisRainbowNeko
commented
2 years ago
在训练过程中出现了如下报错: