Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
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🐛 Bug (问题描述)
I encountered an error while trying to reproduce parseq based on PaddleOCR. It seems to be a bug in the code. Please take a look at the specific information below:
Here is the config file:
Here is the what 'data_dir' looks like, each folder includes two file: 'data.mdb' and 'lock.mdb', which are generated by 'python tools/create_lmdb_dataset.py /path/to/img/root /path/to/gt /path/to/save/lmdb':
Based on infos above, I run order "python3 tools/train.py -c configs/rec/rec_vit_parseq_cty_v1.yml" and encountered a bug at 'ppocr/modeling/heads/rec_parseq_head.py' Line 498:
where targets[0]:
targets[1]:
And:
Is there something wrong with the code? How to solve the problem? Thank you a lot!
Regarding the above problem, it should be caused by the incorrect use of index [0] for a scalar. On the one hand, I think that as an official maintainer, you generally won't make such a simple mistake; but on the other hand, it did happen, which is very strange. Please help solve this problem, thank you!
🏃♂️ Environment (运行环境)
(base) /mnt/workspace/workgroup/sukunming/code/parseq/data/val_label_data/synth> uname -a
Linux dsw84519-5b9bbbb4d-mwmw2 5.10.112-005.ali5000.al8.x86_64 #1 SMP Tue Jun 28 10:43:38 CST 2022 x86_64 x86_64 x86_64 GNU/Linux
(base) /mnt/workspace/workgroup/sukunming/code/parseq/data/val_label_data/synth> pip list
Package Version
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🐛 Bug (问题描述)
I encountered an error while trying to reproduce parseq based on PaddleOCR. It seems to be a bug in the code. Please take a look at the specific information below: Here is the config file:
Here is the what 'data_dir' looks like, each folder includes two file: 'data.mdb' and 'lock.mdb', which are generated by 'python tools/create_lmdb_dataset.py /path/to/img/root /path/to/gt /path/to/save/lmdb':
Based on infos above, I run order "python3 tools/train.py -c configs/rec/rec_vit_parseq_cty_v1.yml" and encountered a bug at 'ppocr/modeling/heads/rec_parseq_head.py' Line 498:
where targets[0]:
targets[1]:
And:
Is there something wrong with the code? How to solve the problem? Thank you a lot! Regarding the above problem, it should be caused by the incorrect use of index [0] for a scalar. On the one hand, I think that as an official maintainer, you generally won't make such a simple mistake; but on the other hand, it did happen, which is very strange. Please help solve this problem, thank you!
🏃♂️ Environment (运行环境)
(base) /mnt/workspace/workgroup/sukunming/code/parseq/data/val_label_data/synth> uname -a Linux dsw84519-5b9bbbb4d-mwmw2 5.10.112-005.ali5000.al8.x86_64 #1 SMP Tue Jun 28 10:43:38 CST 2022 x86_64 x86_64 x86_64 GNU/Linux
(base) /mnt/workspace/workgroup/sukunming/code/parseq/data/val_label_data/synth> pip list Package Version
addict 2.4.0 aiohttp 3.9.1 aiosignal 1.3.1 albucore 0.0.13 albumentations 1.4.14 alibabacloud-credentials 0.3.2 alibabacloud-endpoint-util 0.0.3 alibabacloud-gateway-spi 0.0.1 alibabacloud-openapi-util 0.2.2 alibabacloud-pai-dlc20201203 1.0.0 alibabacloud-paistudio20220112 1.1.2 alibabacloud-tea 0.3.5 alibabacloud-tea-openapi 0.3.8 alibabacloud-tea-util 0.3.11 alibabacloud-tea-xml 0.0.2 alipai 0.1.7 aliyun-log-python-sdk 0.8.15 aliyun-python-sdk-core 2.14.0 aliyun-python-sdk-kms 2.16.2 aliyun-python-sdk-sts 3.1.2 annotated-types 0.7.0 astor 0.8.1 astroid 3.0.2 asttokens 2.4.1 attrs 23.1.0 autopep8 1.7.0 boltons 23.0.0 brotlipy 0.7.0 cachetools 5.3.2 certifi 2023.11.17 cffi 1.15.1 charset-normalizer 2.0.4 cloudpickle 3.0.0 colorama 0.4.6 comm 0.2.1 common-io 0.4.0+tunnel conda 23.9.0 conda-content-trust 0.2.0 conda-libmamba-solver 23.9.1 conda-package-handling 2.2.0 conda_package_streaming 0.9.0 configparser 6.0.0 contextlib2 21.6.0 contourpy 1.2.0 crcmod 1.7 cryptography 37.0.4 cvxopt 1.3.2 cycler 0.12.1 Cython 3.0.6 datasets 2.16.1 dateparser 1.2.0 debugpy 1.8.0 decorator 5.1.1 dill 0.3.7 dnspython 2.4.2 eas-prediction 0.12 easy-rec 0.1.6 einops 0.7.0 elastic-transport 8.11.0 elasticsearch 8.11.1 eval_type_backport 0.2.0 executing 2.0.1 fairscale 0.4.13 filelock 3.13.1 flake8 7.0.0 fonttools 4.47.0 frozenlist 1.4.1 fsspec 2023.12.2 future 0.18.3 gast 0.5.4 graphviz 0.20.1 huggingface-hub 0.20.2 hyperopt 0.1.2 idna 3.4 imageio 2.35.1 importlib-metadata 7.0.1 ipykernel 6.28.0 ipython 8.20.0 ipywidgets 8.1.1 isort 5.13.2 jedi 0.19.1 Jinja2 3.1.2 jmespath 0.10.0 joblib 1.3.2 json-tricks 3.17.3 jsonpatch 1.32 jsonpointer 2.1 jupyter_client 8.6.0 jupyter_core 5.7.1 jupyterlab-widgets 3.0.9 kiwisolver 1.4.5 lazy_loader 0.4 lazy-object-proxy 1.6.0 libmambapy 1.5.1 lightning-utilities 0.11.6 MarkupSafe 2.1.3 matplotlib 3.8.2 matplotlib-inline 0.1.6 mccabe 0.7.0 modelscope 1.11.0 mpmath 1.3.0 multidict 6.0.4 multiprocess 0.70.15 nest-asyncio 1.5.9 networkx 3.2.1 numpy 1.26.2 opencv-contrib-python 4.6.0.66 opencv-python 4.6.0.66 opencv-python-headless 4.10.0.84 opt-einsum 3.3.0 oss2 2.18.3 packaging 23.1 pai-nni 2.6 pandas 2.1.4 parso 0.8.3 patsy 0.5.5 pexpect 4.9.0 pillow 10.2.0 pip 23.3.1 platformdirs 4.1.0 plotly 5.18.0 pluggy 1.0.0 prettytable 3.9.0 prompt-toolkit 3.0.43 protobuf 3.20.3 psutil 5.9.7 ptyprocess 0.7.0 pure-eval 0.2.2 pyarrow 14.0.2 pyarrow-hotfix 0.6 pybind11 2.10.4 pybind11-global 2.10.4 pycodestyle 2.11.1 pycosat 0.6.6 pycparser 2.21 pycryptodome 3.19.0 pydantic 2.8.2 pydantic_core 2.20.1 pyflakes 3.2.0 Pygments 2.17.2 pylint 3.0.3 pymongo 4.6.1 pyodps 0.11.4.1 pyOpenSSL 23.2.0 pyparsing 3.1.1 PySocks 1.7.1 python-dateutil 2.8.2 PythonWebHDFS 0.2.3 pytorch-lightning 2.4.0 pytz 2023.3.post1 PyYAML 6.0.1 pyzmq 25.1.2 regex 2023.12.25 requests 2.31.0 responses 0.24.1 ruamel.yaml 0.17.21 safetensors 0.4.4 schema 0.7.5 scikit-image 0.24.0 scikit-learn 1.3.2 scipy 1.11.4 seaborn 0.13.0 setuptools 68.2.2 simplejson 3.19.2 six 1.16.0 sortedcontainers 2.4.0 stack-data 0.6.3 statsmodels 0.14.1 sympy 1.12 tabulate 0.9.0 tenacity 8.2.3 terminado 0.8.3 threadpoolctl 3.2.0 tifffile 2024.8.10 timm 1.0.8 toml 0.10.2 tomli 2.0.1 tomlkit 0.12.3 torch 2.1.0+cu118 torchaudio 2.1.0+cu118 torchmetrics 1.4.1 torchvision 0.16.0+cu118 tornado 6.4 tqdm 4.66.1 training-utils 1.0.6 traitlets 5.14.1 triton 2.1.0 truststore 0.8.0 typing_extensions 4.9.0 tzdata 2023.3 tzlocal 5.2 urllib3 1.26.16 wcwidth 0.2.13 websockets 12.0 wheel 0.41.2 widgetsnbextension 4.0.9 xgboost 2.0.3 xlrd 2.0.1 xxhash 3.4.1 yapf 0.40.2 yarl 1.9.4 zipp 3.17.0 zstandard 0.19.0
🌰 Minimal Reproducible Example (最小可复现问题的Demo)
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