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Traceback (most recent call last):
File "tools/train.py", line 104, in
main()
File "tools/train.py", line 100, in main
runner.train()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1728, in train
self._train_loop = self.build_train_loop(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1520, in build_train_loop
loop = LOOPS.build(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\loops.py", line 220, in init
super().init(runner, dataloader)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\base_loop.py", line 26, in init
self.dataloader = runner.build_dataloader(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1370, in build_dataloader
dataset = DATASETS.build(dataset_cfg)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmsegmentation-1.2.2-py3.8.egg\mmseg\datasets\pidray.py", line 45, in init
super().init(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmsegmentation-1.2.2-py3.8.egg\mmseg\datasets\basesegdataset.py", line 142, in init
self.full_init()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\dataset\base_dataset.py", line 307, in full_init
self.data_bytes, self.data_address = self._serialize_data()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\dataset\base_dataset.py", line 768, in _serialize_data
data_bytes = np.concatenate(data_list)
File "<array_function internals>", line 200, in concatenate
ValueError: need at least one array to concatenate
在训练自己数据集时报出这个错误,我的数据集按格式分好了训练和验证的图片png格式,并注册了mydatasets。不知道怎么解决这个错误
The text was updated successfully, but these errors were encountered:
Traceback (most recent call last):
File "tools/train.py", line 104, in
main()
File "tools/train.py", line 100, in main
runner.train()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1728, in train
self._train_loop = self.build_train_loop(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1520, in build_train_loop
loop = LOOPS.build(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\loops.py", line 220, in init
super().init(runner, dataloader)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\base_loop.py", line 26, in init
self.dataloader = runner.build_dataloader(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\runner\runner.py", line 1370, in build_dataloader
dataset = DATASETS.build(dataset_cfg)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\registry.py", line 570, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\registry\build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args) # type: ignore
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmsegmentation-1.2.2-py3.8.egg\mmseg\datasets\pidray.py", line 45, in init
super().init(
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmsegmentation-1.2.2-py3.8.egg\mmseg\datasets\basesegdataset.py", line 142, in init
self.full_init()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\dataset\base_dataset.py", line 307, in full_init
self.data_bytes, self.data_address = self._serialize_data()
File "D:\anaconda3\envs\mmpretrain\lib\site-packages\mmengine\dataset\base_dataset.py", line 768, in _serialize_data
data_bytes = np.concatenate(data_list)
File "<array_function internals>", line 200, in concatenate
ValueError: need at least one array to concatenate
在训练自己数据集时报出这个错误,我的数据集按格式分好了训练和验证的图片png格式,并注册了mydatasets。不知道怎么解决这个错误
The text was updated successfully, but these errors were encountered: