简体中文 | English
Open source OCR for the security of the digital world
Contents
- Completely open source, free and support offline deployment of multi-platform and multi-language OCR.
- Chinese Advertising: Welcome to join our QQ group to download the model and test program, QQ group number: 887298230
- Cause: Baidu paddlepaddle engineering is not very good, in order to facilitate everyone to perform OCR reasoning on various terminals, we convert it to onnx format, use
Python/C++/Java/Swift/C#to change It is ported to various platforms. - Name Source: Light, fast, economical and smart. OCR technology based on deep learning technology focuses on artificial intelligence advantages and small models, with speed as the mission and effect as the leading role.
- Usage:
- If the existing model in the repo meets the requirements → RapidOCR deployment can be used.
- Not meeting requirements → Based on PaddleOCR. Fine-tune your own data → RapidOCR deployment. -If this repo is helpful to you, please click on a small star ⭐ Bah!
- Wiki
- Python demo
- C++ demo(Windows/Linux/macOS)
- Jvm demo(Java/Kotlin)
- .Net demo(C#)
- Android demo
- API
- Web demo:
- RapidStructure
- Derivatives
- Related projects
- RapidOCRPDF：extract PDF content.
- RapidVideOCR: Extract hard subtitles in videos based on RapidOCR
- LGPMA_Infer: table structure restoration | blog interpretation papers and source code
- Document Unwarping-PaperEdge | Demo
- Text Removal-CTRNet | Demo
- Model Convert
- About model
- FAQ
Recently updates(more)
- Decouple the API from ocrweb and maintain it as a separate module. For details, see API
- After
rapidocr_web>0.1.6,pip install rapidocr_web[api]will not be supported for installation, you can directly install and usepip install rapidocr_api.
- Add desktop version of RapidOCRWeb, for details, please refer to RapidOCRWeb desktop version tutorial
- Add the return value of the interface version's return coordinate box (issue #85)
- API mode adds base64 format input
- For details, please refer to: link
flowchart LR
subgraph Step
direction TB
C(Text Det) --> D(Text Cls) --> E(Text Rec)
end
A[/OurSelf Dataset/] --> B(PaddleOCR) --Train--> Step --> F(PaddleOCRModelConverter)
F --ONNX--> G{RapidOCR Deploy\n<b>Python/C++/Java/C#</b>}
G --> H(Windows x86/x64) & I(Linux) & J(Android) & K(Web) & L(Raspberry Pi)
click B "https://github.com/PaddlePaddle/PaddleOCR" _blank
click F "https://github.com/RapidAI/PaddleOCRModelConverter" _blank
- Online demo
- For details, please refer to: ocrweb/README
- The model combination (optimal combination) used for the demo is:
ch_PP-OCRv3_det + ch_ppocr_mobile_v2.0_cls + ch_PP-OCRv3_rec - Demo:
- Hugging Face Demo
- The demo is built on Hugging Face's Spaces, generated by the Gradio library.
- Demo:
- See here: link
- Many thanks to DeliciaLaniD for fixing the misplaced start position of scan animation in ocrweb.
- Many thanks to zhsunlight for the suggestion about parameterized call GPU reasoning and the careful and thoughtful testing.
- Many thanks to lzh111222334 for fixing some bugs of rec preprocessing under python version.
- Many thanks to AutumnSun1996 for the suggestion in the #42.
- Many thanks to DeadWood8 for providing the document which packages rapidocr_web to exe by Nuitka.
- Many thanks to Loovelj for fixing the bug of sorting the text boxes. For details see issue 75.
| Sponsor | Applied Products |
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- If you want to sponsor the project, you can directly click the Sponsor button at the top of the current page, please write a note (e.g. your github account name) to facilitate adding to the sponsorship list above.
- The copyright of the OCR model belongs to Baidu, and the copyright of other engineering codes belongs to the owner of this warehouse.
- This software is licensed under Apache 2.0. You are welcome to contribute code, submit an issue or even PR.
- If you find this project useful in your research, please consider citing:
@misc{RapidOCR 2021, title={{Rapid OCR}: OCR Toolbox}, author={MindSpore Team}, howpublished = {\url{https://github.com/RapidAI/RapidOCR}}, year={2021} }
- For international developers, we regard RapidOCR Disscussions as our international community platform. All ideas and questions can be discussed here in English.
