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The pytorch implementation of CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
有训练好的模型吗
2022-02-02 16:31:18,549 [INFO ] dataset_root: root\is\here
dataset: \
sub-directory: /. num samples: 3736
num total samples of total dataset is 3736
2022-02-02 16:31:18,559 [INFO ] num total samples of \: 3736 x 1.0 (total_data_usage_ratio) = 3736
num samples of \ per batch: 32 x 1.0 (batch_ratio) = 32
Traceback (most recent call last):
File "train.py", line 71, in <module>
main()
File "train.py", line 48, in main
train_loader = build_data_loader(flags, mode='train')
File "root\is\here\CdistNet2\program.py", line 84, in build_data_loader
dataloader = create_module(dataloader_infor)(flags)
File "root\is\here\CdistNet2\dataset.py", line 114, in __init__
self.dataloader_iter_list.append(iter(_data_loader))
File "I:\Anaconda\envs\CDistNet2\lib\site-packages\torch\utils\data\dataloader.py", line 279, in __iter__
return _MultiProcessingDataLoaderIter(self)
File "I:\Anaconda\envs\CDistNet2\lib\site-packages\torch\utils\data\dataloader.py", line 719, in __init__
w.start()
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
reduction.dump(process_obj, to_child)
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <class 'flags.FLAGS'>: attribute lookup FLAGS on flags failed
(CDistNet2) I:\Google_Drive\Hyundai\Learnin\CdistNet2>Traceback (most recent call last):
File "<string>", line 1, in <module>
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "I:\Anaconda\envs\CDistNet2\lib\multiprocessing\spawn.py", line 115, in _main
self = reduction.pickle.load(from_parent)
EOFError: Ran out of input
I don't know what is problem exactly but Looks like problem of namedtuple I guess??
Is there any way to get around this problem?
Thank you for your work.
Training accuracy is good but when I tried to predict not predicting any text all are empty. could you please let me know what is the problem?
I think masking array needs to be upper triangular, i made that change and now i am getting correct test and valdation accuracy..
I have a relatively small dataset of a different format (license plates) and it often gets license plate format wrong.
I was wondering if there was a way to train the model on just a bunch of text string data without feeding any images at all in order to enforce the format.
Please let me know if it is possible to train the language/semantic model independently, by just feeding string text data of words, without corresponding images.
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