YOLOX
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Megvii-BaseDetection
How to solve this?yolox.core.launch:98 - An error has been caught in function 'launch', process 'MainProcess' (10152), thread 'MainThread' (19384):
2023-08-10 08:54:40 | INFO | yolox.core.trainer:203 - ---> start train epoch1 - epoch: 1/300, iter: 10/12, mem: 2956Mb, iter_time: 0.771s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 1.1, lr: 4.340e-04, size: 640, ETA: 0:46:06 2023-08-10 08:54:49 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:54:49 | INFO | yolox.core.trainer:203 - ---> start train epoch2 2023-08-10 08:54:53 | INFO | yolox.core.trainer:253 - epoch: 2/300, iter: 10/12, mem: 2956Mb, iter_time: 0.383s, data_time: 0.001s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 6.250e-04, size: 576, ETA: 0:34:23 2023-08-10 08:54:53 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:54:53 | INFO | yolox.core.trainer:203 - ---> start train epoch3 2023-08-10 08:54:58 | INFO | yolox.core.trainer:253 - epoch: 3/300, iter: 10/12, mem: 3329Mb, iter_time: 0.470s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 6.249e-04, size: 768, ETA: 0:30:50 2023-08-10 08:54:59 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:54:59 | INFO | yolox.core.trainer:203 - ---> start train epoch4 2023-08-10 08:55:03 | INFO | yolox.core.trainer:253 - epoch: 4/300, iter: 10/12, mem: 3329Mb, iter_time: 0.448s, data_time: 0.003s, total_loss: 4.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.6, lr: 6.249e-04, size: 608, ETA: 0:28:58 2023-08-10 08:55:03 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:04 | INFO | yolox.core.trainer:203 - ---> start train epoch5 2023-08-10 08:55:05 | INFO | yolox.core.trainer:253 - epoch: 5/300, iter: 10/12, mem: 3329Mb, iter_time: 0.194s, data_time: 0.006s, total_loss: 4.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.6, lr: 6.247e-04, size: 768, ETA: 0:25:10 2023-08-10 08:55:06 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:06 | INFO | yolox.core.trainer:203 - ---> start train epoch6 2023-08-10 08:55:08 | INFO | yolox.core.trainer:253 - epoch: 6/300, iter: 10/12, mem: 3329Mb, iter_time: 0.156s, data_time: 0.001s, total_loss: 4.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.3, cls_loss: 0.6, lr: 6.246e-04, size: 640, ETA: 0:22:27 2023-08-10 08:55:08 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:08 | INFO | yolox.core.trainer:203 - ---> start train epoch7 2023-08-10 08:55:10 | INFO | yolox.core.trainer:253 - epoch: 7/300, iter: 10/12, mem: 3329Mb, iter_time: 0.194s, data_time: 0.001s, total_loss: 3.6, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 1.1, cls_loss: 0.5, lr: 6.244e-04, size: 768, ETA: 0:20:46 2023-08-10 08:55:11 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:11 | INFO | yolox.core.trainer:203 - ---> start train epoch8 2023-08-10 08:55:15 | INFO | yolox.core.trainer:253 - epoch: 8/300, iter: 10/12, mem: 3329Mb, iter_time: 0.429s, data_time: 0.001s, total_loss: 5.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.6, lr: 6.242e-04, size: 544, ETA: 0:20:59 2023-08-10 08:55:15 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:15 | INFO | yolox.core.trainer:203 - ---> start train epoch9 2023-08-10 08:55:20 | INFO | yolox.core.trainer:253 - epoch: 9/300, iter: 10/12, mem: 3329Mb, iter_time: 0.433s, data_time: 0.001s, total_loss: 4.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.4, cls_loss: 0.6, lr: 6.239e-04, size: 672, ETA: 0:21:04 2023-08-10 08:55:20 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 2023-08-10 08:55:20 | INFO | yolox.core.trainer:203 - ---> start train epoch10 2023-08-10 08:55:22 | INFO | yolox.core.trainer:253 - epoch: 10/300, iter: 10/12, mem: 3329Mb, iter_time: 0.181s, data_time: 0.003s, total_loss: 3.4, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 0.8, cls_loss: 0.6, lr: 6.236e-04, size: 672, ETA: 0:19:55 2023-08-10 08:55:22 | INFO | yolox.core.trainer:352 - Save weights to ./YOLOX_outputs\yolox_voc_s 100%|############################################################################################################################################################################| 3/3 [00:03<00:00, 1.32s/it] 2023-08-10 08:55:26 | INFO | yolox.evaluators.voc_evaluator:160 - Evaluate in main process... Writing defect VOC results file 2023-08-10 08:55:26 | INFO | yolox.core.trainer:195 - Training of experiment is done and the best AP is 0.00 2023-08-10 08:55:26 | ERROR | yolox.core.launch:98 - An error has been caught in function 'launch', process 'MainProcess' (10152), thread 'MainThread' (19384): Traceback (most recent call last):
File "C:\YOLOX-0.3.0\tools\train.py", line 134, in
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\core\launch.py", line 98, in launch main_func(*args) │ └ (╒═══════════════════╤═══════════════════════════════════════════════════════════════════════════════════════════════════════... └ <function main at 0x000001F792D5B1F0>
File "C:\YOLOX-0.3.0\tools\train.py", line 118, in main trainer.train() │ └ <function Trainer.train at 0x000001F7931A0EE0> └ <yolox.core.trainer.Trainer object at 0x000001F792D36760>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\core\trainer.py", line 76, in train self.train_in_epoch() │ └ <function Trainer.train_in_epoch at 0x000001F7931A75E0> └ <yolox.core.trainer.Trainer object at 0x000001F792D36760>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\core\trainer.py", line 86, in train_in_epoch self.after_epoch() │ └ <function Trainer.after_epoch at 0x000001F7931A7940> └ <yolox.core.trainer.Trainer object at 0x000001F792D36760>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\core\trainer.py", line 222, in after_epoch self.evaluate_and_save_model() │ └ <function Trainer.evaluate_and_save_model at 0x000001F7931A7C10> └ <yolox.core.trainer.Trainer object at 0x000001F792D36760>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\core\trainer.py", line 325, in evaluate_and_save_model ap50_95, ap50, summary = self.exp.eval( │ │ └ <function Exp.eval at 0x000001F7931A7550> │ └ ╒═══════════════════╤════════════════════════════════════════════════════════════════════════════════════════════════════════... └ <yolox.core.trainer.Trainer object at 0x000001F792D36760>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\exp\yolox_base.py", line 322, 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 0x000001F793198940> └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x000001F796DBDEE0>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\evaluators\voc_evaluator.py", line 128, in evaluate eval_results = self.evaluate_prediction(data_list, statistics) │ │ │ └ tensor([1.2701, 0.0080, 2.0000], device='cuda:0') │ │ └ {0: (tensor([[ 629.6754, 368.1148, 858.0634, 579.1842], │ │ [1442.0361, 432.8301, 1494.7188, 451.6152], │ │ [108... │ └ <function VOCEvaluator.evaluate_prediction at 0x000001F793198A60> └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x000001F796DBDEE0>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\evaluators\voc_evaluator.py", line 205, in evaluate_prediction mAP50, mAP70 = self.dataloader.dataset.evaluate_detections( │ │ │ └ <function VOCDetection.evaluate_detections at 0x000001F7931A03A0> │ │ └ <yolox.data.datasets.voc.VOCDetection object at 0x000001F796DA0280> │ └ <torch.utils.data.dataloader.DataLoader object at 0x000001F7965AEC40> └ <yolox.evaluators.voc_evaluator.VOCEvaluator object at 0x000001F796DBDEE0>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\data\datasets\voc.py", line 265, in evaluate_detections self._write_voc_results_file(all_boxes) │ │ └ [[array([[6.29675354e+02, 3.68114777e+02, 8.58063354e+02, 5.79184204e+02, │ │ 9.08658028e-01], │ │ [1.44203613e+03, 4.... │ └ <function VOCDetection._write_voc_results_file at 0x000001F7931A04C0> └ <yolox.data.datasets.voc.VOCDetection object at 0x000001F796DA0280>
File "C:\Anaconda\envs\env1\lib\site-packages\yolox-0.3.0-py3.9.egg\yolox\data\datasets\voc.py", line 299, in _write_voc_results_file if dets == []: └ array([[6.29675354e+02, 3.68114777e+02, 8.58063354e+02, 5.79184204e+02, 9.08658028e-01], [1.44203613e+03, 4.32...
ValueError: operands could not be broadcast together with shapes (24,5) (0,)
