README.md

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    Introduction

    PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.

    Recent updates

    • 🔥2022.8.24 Release PaddleOCR release/2.6

      • Release PP-Structurev2,with functions and performance fully upgraded, adapted to Chinese scenes, and new support for Layout Recovery and one line command to convert PDF to Word;
      • Layout Analysis optimization: model storage reduced by 95%, while speed increased by 11 times, and the average CPU time-cost is only 41ms;
      • Table Recognition optimization: 3 optimization strategies are designed, and the model accuracy is improved by 6% under comparable time consumption;
      • Key Information Extraction optimization:a visual-independent model structure is designed, the accuracy of semantic entity recognition is increased by 2.8%, and the accuracy of relation extraction is increased by 9.1%.
    • 🔥2022.7 Release OCR scene application collection

      • Release 9 vertical models such as digital tube, LCD screen, license plate, handwriting recognition model, high-precision SVTR model, etc, covering the main OCR vertical applications in general, manufacturing, finance, and transportation industries.
    • 🔥2022.5.9 Release PaddleOCR release/2.5

      • Release PP-OCRv3: With comparable speed, the effect of Chinese scene is further improved by 5% compared with PP-OCRv2, the effect of English scene is improved by 11%, and the average recognition accuracy of 80 language multilingual models is improved by more than 5%.
      • Release PPOCRLabelv2: Add the annotation function for table recognition task, key information extraction task and irregular text image.
      • Release interactive e-book "Dive into OCR", covers the cutting-edge theory and code practice of OCR full stack technology.
    • more

    Features

    PaddleOCR support a variety of cutting-edge algorithms related to OCR, and developed industrial featured models/solution PP-OCR and PP-Structure on this basis, and get through the whole process of data production, model training, compression, inference and deployment.

    It is recommended to start with the “quick experience” in the document tutorial

    Quick Experience

    E-book: Dive Into OCR

    Community

    • Join us👬: Scan the QR code below with your Wechat, you can join the official technical discussion group. Looking forward to your participation.

    PP-OCR Series Model List(Update on September 8th)

    Model introduction Model name Recommended scene Detection model Direction classifier Recognition model
    Chinese and English ultra-lightweight PP-OCRv3 model(16.2M) ch_PP-OCRv3_xx Mobile & Server inference model / trained model inference model / trained model inference model / trained model
    English ultra-lightweight PP-OCRv3 model(13.4M) en_PP-OCRv3_xx Mobile & Server inference model / trained model inference model / trained model inference model / trained model
    Chinese and English ultra-lightweight PP-OCRv2 model(11.6M) ch_PP-OCRv2_xx Mobile & Server inference model / trained model inference model / trained model inference model / trained model
    Chinese and English ultra-lightweight PP-OCR model (9.4M) ch_ppocr_mobile_v2.0_xx Mobile & server inference model / trained model inference model / trained model inference model / trained model
    Chinese and English general PP-OCR model (143.4M) ch_ppocr_server_v2.0_xx Server inference model / trained model inference model / trained model inference model / trained model

    Tutorials

    Visualization more

    PP-OCRv3 Chinese model
    PP-OCRv3 English model
    PP-OCRv3 Multilingual model
    PP-Structurev2
    • layout analysis + table recognition
    • SER (Semantic entity recognition)
    • RE (Relation Extraction)

    Guideline for New Language Requests

    If you want to request a new language support, a PR with 1 following files are needed:

    1. In folder ppocr/utils/dict, it is necessary to submit the dict text to this path and name it with {language}_dict.txt that contains a list of all characters. Please see the format example from other files in that folder.

    If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on.

    More details, please refer to Multilingual OCR Development Plan.

    License

    This project is released under Apache 2.0 license

    项目简介

    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)

    🚀 Github 镜像仓库 🚀

    源项目地址

    https://github.com/PaddlePaddle/PaddleOCR

    发行版本

    当前项目没有发行版本

    贡献者 67

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    开发语言

    • Python 79.1 %
    • C++ 17.6 %
    • Java 2.6 %
    • CMake 0.5 %
    • Makefile 0.2 %