Initial commit

PPOCRLabel/resources/icons/save-as.svg

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+     id="metadata590">
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PPOCRLabel/resources/strings/strings-en.properties

+openFile=Open
+openFileDetail=Open image or label file
+quit=Quit
+quitApp=Quit application
+openDir=Open Dir
+openDatasetDir=Open DatasetDir
+copyPrevBounding=Copy previous Bounding Boxes in the current image 
+changeSavedAnnotationDir=Change default saved Annotation dir
+openAnnotation=Open Annotation
+openAnnotationDetail=Open an annotation file
+changeSaveDir=Change Save Dir
+nextImg=Next Image
+nextImgDetail=Open the next Image
+prevImg=Prev Image
+prevImgDetail=Open the previous Image
+verifyImg=Verify Image
+verifyImgDetail=Verify Image
+save=Check
+saveDetail=Save the labels to a file
+changeSaveFormat=Change save format
+saveAs=Save As
+saveAsDetail=Save the labels to a different file
+closeCur=Close
+closeCurDetail=Close the current file
+deleteImg=Delete current image
+deleteImgDetail=Delete the current image
+resetAll=Reset Interface and Save Dir
+resetAllDetail=Reset All
+boxLineColor=Box Line Color
+boxLineColorDetail=Choose Box line color
+crtBox=Create RectBox
+crtBoxDetail=Draw a new box
+delBox=Delete RectBox
+delBoxDetail=Remove the box
+dupBox=Duplicate RectBox
+dupBoxDetail=Create a duplicate of the selected box
+tutorial=PaddleOCR url
+tutorialDetail=Show demo
+info=Information
+zoomin=Zoom In
+zoominDetail=Increase zoom level
+zoomout=Zoom Out
+zoomoutDetail=Decrease zoom level
+originalsize=Original size
+originalsizeDetail=Zoom to original size
+fitWin=Fit Window
+fitWinDetail=Zoom follows window size
+fitWidth=Fit Width
+fitWidthDetail=Zoom follows window width
+editLabel=Edit Label
+editLabelDetail=Modify the label of the selected Box
+shapeLineColor=Shape Line Color
+shapeLineColorDetail=Change the line color for this specific shape
+shapeFillColor=Shape Fill Color
+shapeFillColorDetail=Change the fill color for this specific shape
+showHide=Show/Hide Label Panel
+useDefaultLabel=Use default label
+useDifficult=Difficult
+boxLabelText=Box Labels
+labels=Labels
+autoSaveMode=Auto Save mode
+singleClsMode=Single Class Mode
+displayLabel=Display Labels
+displayIndex=Display box index
+fileList=File List
+files=Files
+advancedMode=Advanced Mode
+advancedModeDetail=Swtich to advanced mode
+showAllBoxDetail=Show all bounding boxes
+hideAllBoxDetail=Hide all bounding boxes
+annoPanel=anno Panel
+anno=anno
+addNewBbox=new bbox
+reLabel=reLabel
+choosemodel=Choose OCR model
+tipchoosemodel=Choose OCR model from dir
+ImageResize=Image Resize
+IR=Image Resize
+autoRecognition=Auto Recognition
+reRecognition=Re-recognition
+mfile=File
+medit=Edit
+mview=View
+mhelp=Help
+iconList=Icon List
+detectionBoxposition=Detection box position
+recognitionResult=Recognition result
+creatPolygon=Create PolygonBox
+rotateLeft=Left turn 90 degrees
+rotateRight=Right turn 90 degrees
+drawSquares=Draw Squares
+saveRec=Export Recognition Result
+tempLabel=TEMPORARY
+nullLabel=NULL
+steps=Steps
+keys=Shortcut Keys
+choseModelLg=Choose Model Language
+cancel=Cancel
+ok=OK
+autolabeling=Automatic Labeling
+hideBox=Hide All Box
+showBox=Show All Box
+saveLabel=Export Label
+singleRe=Re-recognition RectBox
+labelDialogOption=Pop-up Label Input Dialog
+undo=Undo
+undoLastPoint=Undo Last Point
+autoSaveMode=Auto Export Label Mode
+lockBox=Lock selected box/Unlock all box
+lockBoxDetail=Lock selected box/Unlock all box
+keyListTitle=Key List
+keyDialogTip=Enter object label
+keyChange=Change Box Key
+TableRecognition=Table Recognition
+cellreRecognition=Cell Re-Recognition
+exportJSON=Export Table Label

PPOCRLabel/resources/strings/strings-zh-CN.properties

+saveAsDetail=將标签保存到其他文件
+changeSaveDir=改变存放目录
+openFile=打开文件
+shapeLineColorDetail=更改线条颜色
+resetAll=重置界面与保存地址
+crtBox=矩形标注
+crtBoxDetail=创建一个新的区块
+dupBoxDetail=复制区块
+verifyImg=验证图像
+zoominDetail=放大
+verifyImgDetail=验证图像
+saveDetail=保存标签文件
+openFileDetail=打开图像文件
+fitWidthDetail=调整宽度适应到窗口宽度
+tutorial=PaddleOCR地址
+editLabel=编辑标签
+openAnnotationDetail=打开标签文件
+quit=退出
+shapeFillColorDetail=更改填充颜色
+closeCurDetail=关闭当前文件
+closeCur=关闭文件
+deleteImg=删除图像
+deleteImgDetail=删除当前图像
+fitWin=调整到窗口大小
+delBox=删除选择的区块
+boxLineColorDetail=选择线框颜色
+originalsize=原始大小
+resetAllDetail=重置所有设定
+zoomoutDetail=放大画面
+save=确认
+saveAs=另存为
+fitWinDetail=缩放到当前窗口大小
+openDir=打开目录
+openDatasetDir=打开数据集路径
+copyPrevBounding=复制当前图像中的上一个边界框
+showHide=显示/隐藏标签
+changeSaveFormat=更改存储格式
+shapeFillColor=填充颜色
+quitApp=退出程序
+dupBox=复制区块
+delBoxDetail=删除区块
+zoomin=放大画面
+info=信息
+openAnnotation=开启标签
+prevImgDetail=上一个图像
+fitWidth=缩放到当前画面宽度
+zoomout=缩小画面
+changeSavedAnnotationDir=更改保存标签文件的预设目录
+nextImgDetail=下一个图像
+originalsizeDetail=放大到原始大小
+prevImg=上一张
+tutorialDetail=显示示范内容
+shapeLineColor=形状线条颜色
+boxLineColor=区块线条颜色
+editLabelDetail=修改当前所选的区块颜色
+nextImg=下一张
+useDefaultLabel=使用预设标签
+useDifficult=有难度的
+boxLabelText=区块的标签
+labels=标签
+autoSaveMode=自动保存模式
+singleClsMode=单一类别模式
+displayLabel=显示类别
+displayIndex=显示box序号
+fileList=文件列表
+files=文件
+advancedMode=专家模式
+advancedModeDetail=切换到专家模式
+showAllBoxDetail=显示所有区块
+hideAllBoxDetail=隐藏所有区块
+annoPanel=标注面板
+anno=标注
+addNewBbox=新框
+reLabel=重标注
+choosemodel=选择模型
+tipchoosemodel=选择OCR模型
+ImageResize=图片缩放
+IR=图片缩放
+autoRecognition=自动标注
+reRecognition=重新识别
+mfile=文件
+medit=编辑
+mview=视图
+mhelp=帮助
+iconList=缩略图
+detectionBoxposition=检测框位置
+recognitionResult=识别结果
+creatPolygon=多点标注
+drawSquares=正方形标注
+rotateLeft=图片左旋转90度
+rotateRight=图片右旋转90度
+saveRec=导出识别结果
+tempLabel=待识别
+nullLabel=无法识别
+steps=操作步骤
+keys=快捷键
+choseModelLg=选择模型语言
+cancel=取消
+ok=确认
+autolabeling=自动标注中
+hideBox=隐藏所有标注
+showBox=显示所有标注
+saveLabel=导出标记结果
+singleRe=重识别此区块
+labelDialogOption=弹出标记输入框
+undo=撤销
+undoLastPoint=撤销上个点
+autoSaveMode=自动导出标记结果
+lockBox=锁定框/解除锁定框
+lockBoxDetail=若当前没有框处于锁定状态则锁定选中的框，若存在锁定框则解除所有锁定框的锁定状态
+keyListTitle=关键词列表
+keyDialogTip=请输入类型名称
+keyChange=更改Box关键字类别
+TableRecognition=表格识别
+cellreRecognition=单元格重识别
+exportJSON=导出表格标注
\ No newline at end of file

PPOCRLabel/setup.cfg

+[bumpversion]
+commit = True
+tag = True
+
+[bumpversion:file:setup.py]
+
+[bdist_wheel]
+universal = 1

PPOCRLabel/setup.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from setuptools import setup
+from io import open
+
+with open('requirements.txt', encoding="utf-8-sig") as f:
+    requirements = f.readlines()
+    requirements.append('tqdm')
+
+
+def readme():
+    with open('README.md', encoding="utf-8-sig") as f:
+        README = f.read()
+    return README
+
+
+setup(
+    name='PPOCRLabel',
+    packages=['PPOCRLabel'],
+    package_data = {'PPOCRLabel': ['libs/*','resources/strings/*','resources/icons/*']},
+    package_dir={'PPOCRLabel': ''},
+    include_package_data=True,
+    entry_points={"console_scripts": ["PPOCRLabel= PPOCRLabel.PPOCRLabel:main"]},
+    version='2.1.3',
+    install_requires=requirements,
+    license='Apache License 2.0',
+    description='PPOCRLabelv2 is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data. It is written in Python3 and PyQT5, supporting rectangular box, table, irregular text and key information annotation modes. Annotations can be directly used for the training of PP-OCR detection and recognition models.',
+    long_description=readme(),
+    long_description_content_type='text/markdown',
+    url='https://github.com/PaddlePaddle/PaddleOCR',
+    download_url='https://github.com/PaddlePaddle/PaddleOCR.git',
+    keywords=[
+        'ocr textdetection textrecognition paddleocr crnn east star-net rosetta ocrlite db chineseocr chinesetextdetection chinesetextrecognition'
+    ],
+    classifiers=[
+        'Intended Audience :: Developers', 'Operating System :: OS Independent',
+        'Natural Language :: English',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7', 'Topic :: Utilities'
+    ], )
\ No newline at end of file

README.md

+[English](README_en.md) | 简体中文 | [हिन्दी](./doc/doc_i18n/README_हिन्द.md) | [日本語](./doc/doc_i18n/README_日本語.md) | [한국인](./doc/doc_i18n/README_한국어.md) | [Pу́сский язы́к](./doc/doc_i18n/README_Ру́сский_язы́к.md)
+
+<p align="center">
+ <img src="./doc/PaddleOCR_log.png" align="middle" width = "600"/>
+<p align="center">
+<p align="left">
+    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleOCR/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleOCR?color=ffa"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href=""><img src="https://img.shields.io/pypi/format/PaddleOCR?color=c77"></a>
+    <a href="https://pypi.org/project/PaddleOCR/"><img src="https://img.shields.io/pypi/dm/PaddleOCR?color=9cf"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleOCR/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleOCR?color=ccf"></a>
+</p>
+
+## 简介
+
+PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力开发者训练出更好的模型，并应用落地。
+
+<div align="center">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
+</div>
+
+<div align="center">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+## 📣 近期更新
+- **🔨2023.11 发布 [PP-ChatOCRv2](https://aistudio.baidu.com/application/detail/10368)**: 一个SDK，覆盖20+高频应用场景，支持5种文本图像智能分析能力和部署，包括通用场景关键信息抽取（快递单、营业执照和机动车行驶证等）、复杂文档场景关键信息抽取（解决生僻字、特殊标点、多页pdf、表格等难点问题）、通用OCR、文档场景专用OCR、通用表格识别。针对垂类业务场景，也支持模型训练、微调和Prompt优化。
+- **🔥2023.8.7 发布 PaddleOCR [release/2.7](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.7)**
+    - 发布[PP-OCRv4](./doc/doc_ch/PP-OCRv4_introduction.md)，提供mobile和server两种模型
+      - PP-OCRv4-mobile：速度可比情况下，中文场景效果相比于PP-OCRv3再提升4.5%，英文场景提升10%，80语种多语言模型平均识别准确率提升8%以上
+      - PP-OCRv4-server：发布了目前精度最高的OCR模型，中英文场景上检测模型精度提升4.9%， 识别模型精度提升2%
+        可参考[快速开始](./doc/doc_ch/quickstart.md) 一行命令快速使用，同时也可在飞桨AI套件(PaddleX)中的[通用OCR产业方案](https://aistudio.baidu.com/aistudio/modelsdetail?modelId=286)中低代码完成模型训练、推理、高性能部署全流程
+    - 发布[PP-ChatOCR](https://aistudio.baidu.com/aistudio/modelsdetail?modelId=332) ,使用融合PP-OCR模型和文心大模型的通用场景关键信息抽取全新方案
+- 🔨**2022.11 新增实现[4种前沿算法](doc/doc_ch/algorithm_overview.md)**：文本检测 [DRRG](doc/doc_ch/algorithm_det_drrg.md),  文本识别 [RFL](doc/doc_ch/algorithm_rec_rfl.md), 文本超分[Text Telescope](doc/doc_ch/algorithm_sr_telescope.md)，公式识别[CAN](doc/doc_ch/algorithm_rec_can.md)
+- **2022.10 优化[JS版PP-OCRv3模型](./deploy/paddlejs/README_ch.md)**：模型大小仅4.3M，预测速度提升8倍，配套web demo开箱即用
+- **💥 直播回放：PaddleOCR研发团队详解PP-StructureV2优化策略**。微信扫描[下方二维码](#开源社区)，关注公众号并填写问卷后进入官方交流群，获取直播回放链接与20G重磅OCR学习大礼包（内含PDF转Word应用程序、10种垂类模型、《动手学OCR》电子书等）
+- **🔥2022.8.24 发布 PaddleOCR [release/2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+  - 发布[PP-StructureV2](./ppstructure/README_ch.md)，系统功能性能全面升级，适配中文场景，新增支持[版面复原](./ppstructure/recovery/README_ch.md)，支持**一行命令完成PDF转Word**；
+  - [版面分析](./ppstructure/layout/README_ch.md)模型优化：模型存储减少95%，速度提升11倍，平均CPU耗时仅需41ms；
+  - [表格识别](./ppstructure/table/README_ch.md)模型优化：设计3大优化策略，预测耗时不变情况下，模型精度提升6%；
+  - [关键信息抽取](./ppstructure/kie/README_ch.md)模型优化：设计视觉无关模型结构，语义实体识别精度提升2.8%，关系抽取精度提升9.1%。
+- 🔥**2022.8 发布 [OCR场景应用集合](./applications)**：包含数码管、液晶屏、车牌、高精度SVTR模型、手写体识别等**9个垂类模型**，覆盖通用，制造、金融、交通行业的主要OCR垂类应用。
+
+> [更多](./doc/doc_ch/update.md)
+
+## 🌟 特性
+
+支持多种OCR相关前沿算法，在此基础上打造产业级特色模型[PP-OCR](./doc/doc_ch/ppocr_introduction.md)、[PP-Structure](./ppstructure/README_ch.md)和[PP-ChatOCRv2](https://aistudio.baidu.com/projectdetail/paddlex/7050167)，并打通数据生产、模型训练、压缩、预测部署全流程。
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/tink2123/test/master/ppocrv4.png">
+</div>
+
+> 上述内容的使用方法建议从文档教程中的快速开始体验
+
+
+## ⚡ 快速开始
+
+- 在线免费体验：
+    - PP-OCRv4 在线体验地址：https://aistudio.baidu.com/application/detail/7658
+    - PP-ChatOCRv2 在线体验地址：https://aistudio.baidu.com/application/detail/10368
+  
+- 一行命令快速使用：[快速开始（中英文/多语言/文档分析）](./doc/doc_ch/quickstart.md)
+- 移动端demo体验：[安装包DEMO下载地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统)
+
+<a name="技术交流合作"></a>
+## 📖 技术交流合作
+
+- 飞桨低代码开发工具（PaddleX）—— 面向国内外主流AI硬件的飞桨精选模型一站式开发工具。包含如下核心优势：
+  - 【产业高精度模型库】：覆盖10个主流AI任务 40+精选模型，丰富齐全。
+  - 【特色模型产线】：提供融合大小模型的特色模型产线，精度更高，效果更好。
+  - 【低代码开发模式】：图形化界面支持统一开发范式，便捷高效。
+  - 【私有化部署多硬件支持】：适配国内外主流AI硬件，支持本地纯离线使用，满足企业安全保密需要。
+
+- PaddleX官网地址：https://aistudio.baidu.com/intro/paddlex
+
+- PaddleX官方交流频道：https://aistudio.baidu.com/community/channel/610
+
+<a name="电子书"></a>
+## 📚《动手学OCR》电子书
+- [《动手学OCR》电子书](./doc/doc_ch/ocr_book.md)
+
+<a name="开源共建"></a>
+## 🚀 开源共建
+- **👫 加入社区**：感谢大家长久以来对 PaddleOCR 的支持和关注，与广大开发者共同构建一个专业、和谐、相互帮助的开源社区是 PaddleOCR 的目标。我们非常欢迎各位开发者参与到飞桨社区的开源建设中，加入开源、共建飞桨。**为感谢社区开发者在 PaddleOCR release2.7 中做出的代码贡献，我们将为贡献者制作与邮寄[开源贡献证书](https://github.com/PaddlePaddle/community/blob/master/contributors/certificate-inspection.md)，烦请[填写问卷](https://paddle.wjx.cn/vm/wFNr6w7.aspx)提供必要的邮寄信息。**
+- **🤩 社区活动**：飞桨开源社区长期运营与发布各类丰富的活动与开发任务，在 PaddleOCR 社区，你可以关注以下社区活动，并选择自己感兴趣的内容参与开源共建：
+  - **🎁 飞桨套件快乐开源常规赛 | [传送门](https://github.com/PaddlePaddle/PaddleOCR/issues/10223)**：OCR 社区常规赛升级版，以建设更好用的 OCR 套件为目标，包括但不限于学术前沿模型训练与推理、打磨优化 OCR 工具与应用项目开发等，任何有利于社区意见流动和问题解决的行为都热切希望大家的参与。让我们共同成长为飞桨套件的重要 Contributor 🎉🎉🎉。
+  - **💡 新需求征集 | [传送门](https://github.com/PaddlePaddle/PaddleOCR/issues/10334)**：你在日常研究和实践深度学习过程中，有哪些你期望的 feature 亟待实现？请按照格式描述你想实现的 feature 和你提出的初步实现思路，我们会定期沟通与讨论这些需求，并将其纳入未来的版本规划中。
+  - **💬 PP-SIG 技术研讨会 | [传送门](https://github.com/PaddlePaddle/community/tree/master/ppsigs)**：PP-SIG 是飞桨社区开发者由于相同的兴趣汇聚在一起形成的虚拟组织，通过定期召开技术研讨会的方式，分享行业前沿动态、探讨社区需求与技术开发细节、发起社区联合贡献任务。PaddleOCR 希望可以通过 AI 的力量助力任何一位有梦想的开发者实现自己的想法，享受创造价值带来的愉悦。
+- **📑 项目合作**：如果你有企业中明确的 OCR 垂类应用需求，我们推荐你使用训压推一站式全流程高效率开发平台 PaddleX，助力 AI 技术快速落地。PaddleX 还支持联创开发，利润分成！欢迎广大的个人开发者和企业开发者参与进来，共创繁荣的 AI 技术生态！
+
+
+<a name="模型下载"></a>
+## 🛠️ PP-OCR系列模型列表（更新中）
+
+| 模型简介                              | 模型名称                | 推荐场景        | 检测模型                                                     | 方向分类器                                                   | 识别模型                                                     |
+| ------------------------------------- | ----------------------- | --------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| 中英文超轻量PP-OCRv4模型（15.8M）     | ch_PP-OCRv4_xx          | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_train.tar) |
+| 中英文超轻量PP-OCRv3模型（16.2M）     | ch_PP-OCRv3_xx          | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+| 英文超轻量PP-OCRv3模型（13.4M）     | en_PP-OCRv3_xx          | 移动端&服务器端 | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+
+- 超轻量OCR系列更多模型下载（包括多语言），可以参考[PP-OCR系列模型下载](./doc/doc_ch/models_list.md)，文档分析相关模型参考[PP-Structure系列模型下载](./ppstructure/docs/models_list.md)
+
+### PaddleOCR场景应用模型
+
+| 行业 | 类别         | 亮点                               | 文档说明                                                     | 模型下载                                      |
+| ---- | ------------ | ---------------------------------- | ------------------------------------------------------------ | --------------------------------------------- |
+| 制造 | 数码管识别   | 数码管数据合成、漏识别调优         | [光功率计数码管字符识别](./applications/光功率计数码管字符识别/光功率计数码管字符识别.md) | [下载链接](./applications/README.md#模型下载) |
+| 金融 | 通用表单识别 | 多模态通用表单结构化提取           | [多模态表单识别](./applications/多模态表单识别.md)           | [下载链接](./applications/README.md#模型下载) |
+| 交通 | 车牌识别     | 多角度图像处理、轻量模型、端侧部署 | [轻量级车牌识别](./applications/轻量级车牌识别.md)           | [下载链接](./applications/README.md#模型下载) |
+
+- 更多制造、金融、交通行业的主要OCR垂类应用模型（如电表、液晶屏、高精度SVTR模型等），可参考[场景应用模型下载](./applications)
+
+<a name="文档教程"></a>
+
+## 📖 文档教程
+
+- [运行环境准备](./doc/doc_ch/environment.md)
+- [PP-OCR文本检测识别🔥](./doc/doc_ch/ppocr_introduction.md)
+    - [快速开始](./doc/doc_ch/quickstart.md)
+    - [模型库](./doc/doc_ch/models_list.md)
+    - [模型训练](./doc/doc_ch/training.md)
+        - [文本检测](./doc/doc_ch/detection.md)
+        - [文本识别](./doc/doc_ch/recognition.md)
+        - [文本方向分类器](./doc/doc_ch/angle_class.md)
+    - 模型压缩
+        - [模型量化](./deploy/slim/quantization/README.md)
+        - [模型裁剪](./deploy/slim/prune/README.md)
+        - [知识蒸馏](./doc/doc_ch/knowledge_distillation.md)
+    - [推理部署](./deploy/README_ch.md)
+        - [基于Python预测引擎推理](./doc/doc_ch/inference_ppocr.md)
+        - [基于C++预测引擎推理](./deploy/cpp_infer/readme_ch.md)
+        - [服务化部署](./deploy/pdserving/README_CN.md)
+        - [端侧部署](./deploy/lite/readme.md)
+        - [Paddle2ONNX模型转化与预测](./deploy/paddle2onnx/readme.md)
+        - [云上飞桨部署工具](./deploy/paddlecloud/README.md)
+        - [Benchmark](./doc/doc_ch/benchmark.md)
+- [PP-Structure文档分析🔥](./ppstructure/README_ch.md)
+    - [快速开始](./ppstructure/docs/quickstart.md)
+    - [模型库](./ppstructure/docs/models_list.md)
+    - [模型训练](./doc/doc_ch/training.md)
+        - [版面分析](./ppstructure/layout/README_ch.md)
+        - [表格识别](./ppstructure/table/README_ch.md)
+        - [关键信息提取](./ppstructure/kie/README_ch.md)
+    - [推理部署](./deploy/README_ch.md)
+        - [基于Python预测引擎推理](./ppstructure/docs/inference.md)
+        - [基于C++预测引擎推理](./deploy/cpp_infer/readme_ch.md)
+        - [服务化部署](./deploy/hubserving/readme.md)
+- [前沿算法与模型🚀](./doc/doc_ch/algorithm_overview.md)
+    - [文本检测算法](./doc/doc_ch/algorithm_overview.md)
+    - [文本识别算法](./doc/doc_ch/algorithm_overview.md)
+    - [端到端OCR算法](./doc/doc_ch/algorithm_overview.md)
+    - [表格识别算法](./doc/doc_ch/algorithm_overview.md)
+    - [关键信息抽取算法](./doc/doc_ch/algorithm_overview.md)
+    - [使用PaddleOCR架构添加新算法](./doc/doc_ch/add_new_algorithm.md)
+- [场景应用](./applications)
+- 数据标注与合成
+    - [半自动标注工具PPOCRLabel](./PPOCRLabel/README_ch.md)
+    - [数据合成工具Style-Text](./StyleText/README_ch.md)
+    - [其它数据标注工具](./doc/doc_ch/data_annotation.md)
+    - [其它数据合成工具](./doc/doc_ch/data_synthesis.md)
+- 数据集
+    - [通用中英文OCR数据集](doc/doc_ch/dataset/datasets.md)
+    - [手写中文OCR数据集](doc/doc_ch/dataset/handwritten_datasets.md)
+    - [垂类多语言OCR数据集](doc/doc_ch/dataset/vertical_and_multilingual_datasets.md)
+    - [版面分析数据集](doc/doc_ch/dataset/layout_datasets.md)
+    - [表格识别数据集](doc/doc_ch/dataset/table_datasets.md)
+    - [关键信息提取数据集](doc/doc_ch/dataset/kie_datasets.md)
+- [代码组织结构](./doc/doc_ch/tree.md)
+- [效果展示](#效果展示)
+- [《动手学OCR》电子书📚](./doc/doc_ch/ocr_book.md)
+- [开源社区](#开源社区)
+- FAQ
+    - [通用问题](./doc/doc_ch/FAQ.md)
+    - [PaddleOCR实战问题](./doc/doc_ch/FAQ.md)
+- [参考文献](./doc/doc_ch/reference.md)
+- [许可证书](#许可证书)
+
+
+<a name="效果展示"></a>
+
+## 👀 效果展示 [more](./doc/doc_ch/visualization.md)
+
+<details open>
+<summary>PP-OCRv3 中文模型</summary>
+
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+
+</details>
+
+
+<details open>
+<summary>PP-OCRv3 英文模型</summary>
+
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+
+</details>
+
+
+<details open>
+<summary>PP-OCRv3 多语言模型</summary>
+
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+
+</details>
+
+<details open>
+<summary>PP-Structure 文档分析</summary>
+
+- 版面分析+表格识别  
+<div align="center">
+    <img src="./ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+
+- SER（语义实体识别）  
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185310636-6ce02f7c-790d-479f-b163-ea97a5a04808.jpg" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185539517-ccf2372a-f026-4a7c-ad28-c741c770f60a.png" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/197464552-69de557f-edff-4c7f-acbf-069df1ba097f.png" width="600">
+</div>
+
+- RE（关系提取）
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185393805-c67ff571-cf7e-4217-a4b0-8b396c4f22bb.jpg" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185540080-0431e006-9235-4b6d-b63d-0b3c6e1de48f.jpg" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094813-3a8e16cc-42e5-4982-b9f4-0134dfb5688d.png" width="600">
+</div>
+
+</details>
+
+<a name="许可证书"></a>
+
+## 许可证书
+本项目的发布受<a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>许可认证。

README_en.md

+English | [简体中文](README_ch.md) | [हिन्दी](./doc/doc_i18n/README_हिन्द.md) | [日本語](./doc/doc_i18n/README_日本語.md) | [한국인](./doc/doc_i18n/README_한국어.md) | [Pу́сский язы́к](./doc/doc_i18n/README_Ру́сский_язы́к.md)
+
+<p align="center">
+ <img src="./doc/PaddleOCR_log.png" align="middle" width = "600"/>
+<p align="center">
+<p align="left">
+    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleOCR/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleOCR?color=ffa"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href=""><img src="https://img.shields.io/pypi/format/PaddleOCR?color=c77"></a>
+    <a href="https://pypi.org/project/PaddleOCR/"><img src="https://img.shields.io/pypi/dm/PaddleOCR?color=9cf"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleOCR/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleOCR?color=ccf"></a>
+</p>
+
+## Introduction
+
+PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.
+
+<div align="center">
+    <img src="./doc/imgs_results/PP-OCRv3/en/en_4.png" width="800">
+</div>
+
+<div align="center">
+    <img src="./doc/imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+## 📣 Recent updates
+- **🔥2023.8.7 Release PaddleOCR[release/2.7](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.7)**
+  - Release [PP-OCRv4](./doc/doc_ch/PP-OCRv4_introduction.md), support mobile version and server version
+    - PP-OCRv4-mobile：When the speed is comparable, the effect of the Chinese scene is improved by 4.5% compared with PP-OCRv3, the English scene is improved by 10%, and the average recognition accuracy of the 80-language multilingual model is increased by more than 8%.
+    - PP-OCRv4-server：Release the OCR model with the highest accuracy at present, the detection model accuracy increased by 4.9% in the Chinese and English scenes, and the recognition model accuracy increased by 2%
+        refer [quickstart](./doc/doc_en/quickstart_en.md) quick use by one line command, At the same time, the whole process of model training, reasoning, and high-performance deployment can also be completed with few code in the [General OCR Industry Solution](https://aistudio.baidu.com/aistudio/modelsdetail?modelId=286) in PaddleX.
+  - Release[PP-ChatOCR](https://aistudio.baidu.com/aistudio/modelsdetail?modelId=332), a new scheme for extracting key information of general scenes using PP-OCR model and ERNIE LLM.
+- 🔨**2022.11 Add implementation of [4 cutting-edge algorithms](doc/doc_ch/algorithm_overview_en.md)**：Text Detection [DRRG](doc/doc_en/algorithm_det_drrg_en.md),  Text Recognition [RFL](./doc/doc_en/algorithm_rec_rfl_en.md), Image Super-Resolution [Text Telescope](doc/doc_en/algorithm_sr_telescope_en.md)，Handwritten Mathematical Expression Recognition [CAN](doc/doc_en/algorithm_rec_can_en.md)
+- **2022.10 release [optimized JS version PP-OCRv3 model](./deploy/paddlejs/README.md)** with 4.3M model size, 8x faster inference time, and a ready-to-use web demo
+- 💥 **Live Playback: Introduction to PP-StructureV2 optimization strategy**. Scan [the QR code below](#Community) using WeChat, follow the PaddlePaddle official account and fill out the questionnaire to join the WeChat group, get the live link and 20G OCR learning materials (including PDF2Word application, 10 models in vertical scenarios, etc.)
+
+
+- **🔥2022.8.24 Release PaddleOCR [release/2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+  - Release [PP-StructureV2](./ppstructure/)，with functions and performance fully upgraded, adapted to Chinese scenes, and new support for [Layout Recovery](./ppstructure/recovery) and **one line command to convert PDF to Word**;
+  - [Layout Analysis](./ppstructure/layout) optimization: model storage reduced by 95%, while speed increased by 11 times, and the average CPU time-cost is only 41ms;
+  - [Table Recognition](./ppstructure/table) optimization: 3 optimization strategies are designed, and the model accuracy is improved by 6% under comparable time consumption;
+  - [Key Information Extraction](./ppstructure/kie) 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%.
+- **🔥2022.8 Release [OCR scene application collection](./applications/README_en.md)**
+    - 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.
+- **2022.8 Add implementation of [8 cutting-edge algorithms](doc/doc_en/algorithm_overview_en.md)**
+  - Text Detection: [FCENet](doc/doc_en/algorithm_det_fcenet_en.md), [DB++](doc/doc_en/algorithm_det_db_en.md)
+  - Text Recognition: [ViTSTR](doc/doc_en/algorithm_rec_vitstr_en.md), [ABINet](doc/doc_en/algorithm_rec_abinet_en.md), [VisionLAN](doc/doc_en/algorithm_rec_visionlan_en.md), [SPIN](doc/doc_en/algorithm_rec_spin_en.md), [RobustScanner](doc/doc_en/algorithm_rec_robustscanner_en.md)
+  - Table Recognition: [TableMaster](doc/doc_en/algorithm_table_master_en.md)
+- **2022.5.9 Release PaddleOCR [release/2.5](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.5)**
+    - Release [PP-OCRv3](./doc/doc_en/ppocr_introduction_en.md#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](./PPOCRLabel): Add the annotation function for table recognition task, key information extraction task and irregular text image.
+    - Release interactive e-book [*"Dive into OCR"*](./doc/doc_en/ocr_book_en.md), covers the cutting-edge theory and code practice of OCR full stack technology.
+- [more](./doc/doc_en/update_en.md)
+
+
+## 🌟 Features
+
+PaddleOCR support a variety of cutting-edge algorithms related to OCR, and developed industrial featured models/solution [PP-OCR](./doc/doc_en/ppocr_introduction_en.md)、 [PP-Structure](./ppstructure/README.md) and [PP-ChatOCR](https://aistudio.baidu.com/aistudio/projectdetail/6488689) on this basis, and get through the whole process of data production, model training, compression, inference and deployment.
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186171245-40abc4d7-904f-4949-ade1-250f86ed3a90.png">
+</div>
+
+> It is recommended to start with the “quick experience” in the document tutorial
+
+
+## ⚡ Quick Experience
+
+- Web online experience
+    - PP-OCRv4 online experience：https://aistudio.baidu.com/application/detail/7658
+    - PP-ChatOCR online experience：https://aistudio.baidu.com/application/detail/7709
+
+- One line of code quick use: [Quick Start（Chinese/English/Multilingual/Document Analysis](./doc/doc_en/quickstart_en.md)
+- Full-process experience of training, inference, and high-performance deployment in the Paddle AI suite (PaddleX)：
+    - PP-OCRv4：https://aistudio.baidu.com/projectdetail/paddlex/6796224
+    - PP-ChatOCR：https://aistudio.baidu.com/projectdetail/paddlex/6796372
+- Mobile demo experience：[Installation DEMO](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)(Based on EasyEdge and Paddle-Lite, support iOS and Android systems)
+
+<a name="Technical exchange and cooperation"></a>
+
+## 📖 Technical exchange and cooperation
+- PaddleX —— A one-stop development platform for practical models of selected industries. Includes the following features:
+* [High-quality algorithm library] Contains 36 selected models in 10 major task areas, enabling the development of model algorithms for different tasks in one platform. More domain models continue to be enriched! PaddleX also provides complete model training and inference benchmark data, allowing developers to choose the most appropriate model based on business needs.
+* [Simple development method] Toolbox/developer dual-mode linkage, no-code + low-code development method, complete the full process of AI development of data, training, verification, and deployment in four steps.
+* [Efficient training deployment] Precipitate the best tuning strategy of Baidu algorithm team to achieve the fastest and optimal convergence of each model. Complete deployment SDK support enables rapid industrial-level deployment across platforms and hardware (service-based deployment capabilities are being improved).
+* [Rich domestic hardware support] In addition to being used on the AIStudio cloud, PaddleX has also precipitated the Windows local side and is enriching the Linux version, Kunlun Core version, Ascend version, and Cambrian version.
+* [Win-win joint creation and co-construction] In addition to conveniently developing AI applications, PaddleX also provides everyone with opportunities to obtain business benefits and explore more business space for enterprises.
+
+PaddleX Official website address：https://www.paddlepaddle.org.cn/paddle/paddleX
+
+Scan the QR code below on WeChat to add operation students, and reply [paddlex], operation students will invite you to join the official communication group for more efficient questions and answers.
+
+<div align="center">
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/dygraph/doc/joinus_paddlex.jpg"  width = "150" height = "150",caption='' />
+<p>[PaddleX] technology exchange group QR code</p>
+</div>
+
+<a name="book"></a>
+## 📚 E-book: *Dive Into OCR*
+- [Dive Into OCR ](./doc/doc_en/ocr_book_en.md)
+
+<a name="Community"></a>
+
+## 👫 Community
+
+- For international developers, we regard [PaddleOCR Discussions](https://github.com/PaddlePaddle/PaddleOCR/discussions) as our international community platform. All ideas and questions can be discussed here in English.
+
+- For Chinese develops, Scan the QR code below with your Wechat, you can join the official technical discussion group. For richer community content, please refer to [中文README](README_ch.md), looking forward to your participation.
+
+<div align="center">
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/dygraph/doc/joinus.PNG"  width = "150" height = "150" />
+</div>
+
+<a name="Supported-Chinese-model-list"></a>
+
+## 🛠️ 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-OCRv4 model（16.2M）     | ch_PP-OCRv4_xx          | Mobile & Server | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_distill_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_train.tar) |
+| Chinese and English ultra-lightweight PP-OCRv3 model（16.2M）     | ch_PP-OCRv3_xx          | Mobile & Server | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+| English ultra-lightweight PP-OCRv3 model（13.4M）     | en_PP-OCRv3_xx          | Mobile & Server | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+
+- For more model downloads (including multiple languages), please refer to [PP-OCR series model downloads](./doc/doc_en/models_list_en.md).
+- For a new language request, please refer to [Guideline for new language_requests](#language_requests).
+- For structural document analysis models, please refer to [PP-Structure models](./ppstructure/docs/models_list_en.md).
+
+<a name="tutorials"></a>
+## 📖 Tutorials
+- [Environment Preparation](./doc/doc_en/environment_en.md)
+- [PP-OCR 🔥](./doc/doc_en/ppocr_introduction_en.md)
+    - [Quick Start](./doc/doc_en/quickstart_en.md)
+    - [Model Zoo](./doc/doc_en/models_en.md)
+    - [Model training](./doc/doc_en/training_en.md)
+        - [Text Detection](./doc/doc_en/detection_en.md)
+        - [Text Recognition](./doc/doc_en/recognition_en.md)
+        - [Text Direction Classification](./doc/doc_en/angle_class_en.md)
+    - Model Compression
+        - [Model Quantization](./deploy/slim/quantization/README_en.md)
+        - [Model Pruning](./deploy/slim/prune/README_en.md)
+        - [Knowledge Distillation](./doc/doc_en/knowledge_distillation_en.md)
+    - [Inference and Deployment](./deploy/README.md)
+        - [Python Inference](./doc/doc_en/inference_ppocr_en.md)
+        - [C++ Inference](./deploy/cpp_infer/readme.md)
+        - [Serving](./deploy/pdserving/README.md)
+        - [Mobile](./deploy/lite/readme.md)
+        - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
+        - [PaddleCloud](./deploy/paddlecloud/README.md)
+        - [Benchmark](./doc/doc_en/benchmark_en.md)  
+- [PP-Structure 🔥](./ppstructure/README.md)
+    - [Quick Start](./ppstructure/docs/quickstart_en.md)
+    - [Model Zoo](./ppstructure/docs/models_list_en.md)
+    - [Model training](./doc/doc_en/training_en.md)  
+        - [Layout Analysis](./ppstructure/layout/README.md)
+        - [Table Recognition](./ppstructure/table/README.md)
+        - [Key Information Extraction](./ppstructure/kie/README.md)
+    - [Inference and Deployment](./deploy/README.md)
+        - [Python Inference](./ppstructure/docs/inference_en.md)
+        - [C++ Inference](./deploy/cpp_infer/readme.md)
+        - [Serving](./deploy/hubserving/readme_en.md)
+- [Academic Algorithms](./doc/doc_en/algorithm_overview_en.md)
+    - [Text detection](./doc/doc_en/algorithm_overview_en.md)
+    - [Text recognition](./doc/doc_en/algorithm_overview_en.md)
+    - [End-to-end OCR](./doc/doc_en/algorithm_overview_en.md)
+    - [Table Recognition](./doc/doc_en/algorithm_overview_en.md)
+    - [Key Information Extraction](./doc/doc_en/algorithm_overview_en.md)  
+    - [Add New Algorithms to PaddleOCR](./doc/doc_en/add_new_algorithm_en.md)
+- Data Annotation and Synthesis
+    - [Semi-automatic Annotation Tool: PPOCRLabel](./PPOCRLabel/README.md)
+    - [Data Synthesis Tool: Style-Text](./StyleText/README.md)
+    - [Other Data Annotation Tools](./doc/doc_en/data_annotation_en.md)
+    - [Other Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md)
+- Datasets
+    - [General OCR Datasets(Chinese/English)](doc/doc_en/dataset/datasets_en.md)
+    - [HandWritten_OCR_Datasets(Chinese)](doc/doc_en/dataset/handwritten_datasets_en.md)
+    - [Various OCR Datasets(multilingual)](doc/doc_en/dataset/vertical_and_multilingual_datasets_en.md)
+    - [Layout Analysis](doc/doc_en/dataset/layout_datasets_en.md)
+    - [Table Recognition](doc/doc_en/dataset/table_datasets_en.md)
+    - [Key Information Extraction](doc/doc_en/dataset/kie_datasets_en.md)
+- [Code Structure](./doc/doc_en/tree_en.md)
+- [Visualization](#Visualization)
+- [Community](#Community)
+- [New language requests](#language_requests)
+- [FAQ](./doc/doc_en/FAQ_en.md)
+- [References](./doc/doc_en/reference_en.md)
+- [License](#LICENSE)
+
+
+<a name="Visualization"></a>
+## 👀 Visualization [more](./doc/doc_en/visualization_en.md)
+
+<details open>
+<summary>PP-OCRv3 Chinese model</summary>
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-OCRv3 English model</summary>
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-OCRv3 Multilingual model</summary>
+<div align="center">
+    <img src="doc/imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="doc/imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-StructureV2</summary>
+
+- layout analysis + table recognition  
+<div align="center">
+    <img src="./ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+
+- SER (Semantic entity recognition)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/197464552-69de557f-edff-4c7f-acbf-069df1ba097f.png" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185310636-6ce02f7c-790d-479f-b163-ea97a5a04808.jpg" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185539517-ccf2372a-f026-4a7c-ad28-c741c770f60a.png" width="600">
+</div>
+
+- RE (Relation Extraction)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094813-3a8e16cc-42e5-4982-b9f4-0134dfb5688d.png" width="600">
+</div>  
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185393805-c67ff571-cf7e-4217-a4b0-8b396c4f22bb.jpg" width="600">
+</div>
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/14270174/185540080-0431e006-9235-4b6d-b63d-0b3c6e1de48f.jpg" width="600">
+</div>
+
+</details>
+
+<a name="language_requests"></a>
+## 🇺🇳 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](./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](https://github.com/PaddlePaddle/PaddleOCR/issues/1048).
+
+
+<a name="LICENSE"></a>
+## 📄 License
+This project is released under <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>

StyleText/README.md

+English | [简体中文](README_ch.md)
+
+## Style Text
+
+### Contents
+- [1. Introduction](#Introduction)
+- [2. Preparation](#Preparation)
+- [3. Quick Start](#Quick_Start)
+- [4. Applications](#Applications)
+- [5. Code Structure](#Code_structure)
+
+
+<a name="Introduction"></a>
+### Introduction
+
+<div align="center">
+    <img src="doc/images/3.png" width="800">
+</div>
+
+<div align="center">
+    <img src="doc/images/9.png" width="600">
+</div>
+
+
+The Style-Text data synthesis tool is a tool based on Baidu and HUST cooperation research work, "Editing Text in the Wild" [https://arxiv.org/abs/1908.03047](https://arxiv.org/abs/1908.03047).
+
+Different from the commonly used GAN-based data synthesis tools, the main framework of Style-Text includes:
+* (1) Text foreground style transfer module.
+* (2) Background extraction module.
+* (3) Fusion module.
+
+After these three steps, you can quickly realize the image text style transfer. The following figure is some results of the data synthesis tool.
+
+<div align="center">
+    <img src="doc/images/10.png" width="1000">
+</div>
+
+
+<a name="Preparation"></a>
+#### Preparation
+
+1. Please refer the [QUICK INSTALLATION](../doc/doc_en/installation_en.md) to install PaddlePaddle. Python3 environment is strongly recommended.
+2. Download the pretrained models and unzip:
+
+```bash
+cd StyleText
+wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/style_text_models.zip
+unzip style_text_models.zip
+```
+
+If you save the model in another location, please modify the address of the model file in `configs/config.yml`, and you need to modify these three configurations at the same time:
+
+```
+bg_generator:
+  pretrain: style_text_models/bg_generator
+...
+text_generator:
+  pretrain: style_text_models/text_generator
+...
+fusion_generator:
+  pretrain: style_text_models/fusion_generator
+```
+
+<a name="Quick_Start"></a>
+### Quick Start
+
+#### Synthesis single image
+
+1. You can run `tools/synth_image` and generate the demo image, which is saved in the current folder.
+
+```python
+python3 tools/synth_image.py -c configs/config.yml --style_image examples/style_images/2.jpg --text_corpus PaddleOCR --language en
+```
+
+* Note 1: The language options is correspond to the corpus. Currently, the tool only supports English(en), Simplified Chinese(ch) and Korean(ko).
+* Note 2: Synth-Text is mainly used to generate images for OCR recognition models.
+  So the height of style images should be around 32 pixels. Images in other sizes may behave poorly.
+* Note 3: You can modify `use_gpu` in `configs/config.yml` to determine whether to use GPU for prediction.
+
+
+
+For example, enter the following image and corpus `PaddleOCR`.
+
+<div align="center">
+    <img src="examples/style_images/2.jpg" width="300">
+</div>
+
+The result `fake_fusion.jpg` will be generated.
+
+<div align="center">
+    <img src="doc/images/4.jpg" width="300">
+</div>
+
+What's more, the medium result `fake_bg.jpg` will also be saved, which is the background output.
+
+<div align="center">
+    <img src="doc/images/7.jpg" width="300">
+</div>
+
+
+`fake_text.jpg` * `fake_text.jpg` is the generated image with the same font style as `Style Input`.
+
+
+<div align="center">
+    <img src="doc/images/8.jpg" width="300">
+</div>
+
+
+#### Batch synthesis
+
+In actual application scenarios, it is often necessary to synthesize pictures in batches and add them to the training set. StyleText can use a batch of style pictures and corpus to synthesize data in batches. The synthesis process is as follows:
+
+1. The referenced dataset can be specifed in `configs/dataset_config.yml`:
+
+   * `Global`：
+     * `output_dir:`：Output synthesis data path.
+   * `StyleSampler`：
+     * `image_home`：style images' folder.
+     * `label_file`：Style images' file list. If label is provided, then it is the label file path.
+     * `with_label`：Whether the `label_file` is label file list.
+   * `CorpusGenerator`：
+     * `method`：Method of CorpusGenerator，supports `FileCorpus` and `EnNumCorpus`. If `EnNumCorpus` is used，No other configuration is needed，otherwise you need to set `corpus_file` and `language`.
+     * `language`：Language of the corpus. Currently, the tool only supports English(en), Simplified Chinese(ch) and Korean(ko).
+     * `corpus_file`: Filepath of the corpus. Corpus file should be a text file which will be split by line-endings（'\n'）. Corpus generator samples one line each time.
+
+
+Example of corpus file:
+```
+PaddleOCR
+飞桨文字识别
+StyleText
+风格文本图像数据合成
+```
+
+We provide a general dataset containing Chinese, English and Korean (50,000 images in all) for your trial ([download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)), some examples are given below :
+
+<div align="center">
+     <img src="doc/images/5.png" width="800">
+</div>
+
+2. You can run the following command to start synthesis task:
+
+   ``` bash
+   python3 tools/synth_dataset.py -c configs/dataset_config.yml
+   ```
+
+We also provide example corpus and images in `examples` folder.
+    <div align="center">
+        <img src="examples/style_images/1.jpg" width="300">
+        <img src="examples/style_images/2.jpg" width="300">
+    </div>
+If you run the code above directly, you will get example output data in `output_data` folder.
+You will get synthesis images and labels as below:
+   <div align="center">
+       <img src="doc/images/12.png" width="800">
+   </div>
+There will be some cache under the `label` folder. If the program exit unexpectedly, you can find cached labels there.
+When the program finish normally, you will find all the labels in `label.txt` which give the final results.
+
+<a name="Applications"></a>
+### Applications
+We take two scenes as examples, which are metal surface English number recognition and general Korean recognition, to illustrate practical cases of using StyleText to synthesize data to improve text recognition. The following figure shows some examples of real scene images and composite images:
+
+<div align="center">
+    <img src="doc/images/11.png" width="800">
+</div>
+
+
+After adding the above synthetic data for training, the accuracy of the recognition model is improved, which is shown in the following table:
+
+
+| Scenario | Characters | Raw Data | Test Data | Only Use Raw Data</br>Recognition Accuracy | New Synthetic Data | Simultaneous Use of Synthetic Data</br>Recognition Accuracy | Index Improvement |
+| -------- | ---------- | -------- | -------- | -------------------------- | ------------ | ---------------------- | -------- |
+| Metal surface | English and numbers | 2203     | 650      | 59.38%                     | 20000        | 75.46%                 | 16.08%      |
+| Random background | Korean       | 5631     | 1230     | 30.12%                     | 100000       | 50.57%                 | 20.45%      |
+
+<a name="Code_structure"></a>
+### Code Structure
+
+```
+StyleText
+|-- arch                        // Network module files.
+|   |-- base_module.py
+|   |-- decoder.py
+|   |-- encoder.py
+|   |-- spectral_norm.py
+|   `-- style_text_rec.py
+|-- configs                     // Config files.
+|   |-- config.yml
+|   `-- dataset_config.yml
+|-- engine                      // Synthesis engines.
+|   |-- corpus_generators.py    // Sample corpus from file or generate random corpus.
+|   |-- predictors.py           // Predict using network.
+|   |-- style_samplers.py       // Sample style images.
+|   |-- synthesisers.py         // Manage other engines to synthesis images.
+|   |-- text_drawers.py         // Generate standard input text images.
+|   `-- writers.py              // Write synthesis images and labels into files.
+|-- examples                    // Example files.
+|   |-- corpus
+|   |   `-- example.txt
+|   |-- image_list.txt
+|   `-- style_images
+|       |-- 1.jpg
+|       `-- 2.jpg
+|-- fonts                       // Font files.
+|   |-- ch_standard.ttf
+|   |-- en_standard.ttf
+|   `-- ko_standard.ttf
+|-- tools                       // Program entrance.
+|   |-- __init__.py
+|   |-- synth_dataset.py        // Synthesis dataset.
+|   `-- synth_image.py          // Synthesis image.
+`-- utils                       // Module of basic functions.
+    |-- config.py
+    |-- load_params.py
+    |-- logging.py
+    |-- math_functions.py
+    `-- sys_funcs.py
+```

StyleText/README_ch.md

+简体中文 | [English](README.md)
+
+## Style Text
+
+
+### 目录
+- [一、工具简介](#工具简介)
+- [二、环境配置](#环境配置)
+- [三、快速上手](#快速上手)
+- [四、应用案例](#应用案例)
+- [五、代码结构](#代码结构)
+
+<a name="工具简介"></a>
+### 一、工具简介
+<div align="center">
+    <img src="doc/images/3.png" width="800">
+</div>
+
+<div align="center">
+    <img src="doc/images/1.png" width="600">
+</div>
+
+
+Style-Text数据合成工具是基于百度和华科合作研发的文本编辑算法《Editing Text in the Wild》https://arxiv.org/abs/1908.03047
+
+不同于常用的基于GAN的数据合成工具，Style-Text主要框架包括：1.文本前景风格迁移模块 2.背景抽取模块 3.融合模块。经过这样三步，就可以迅速实现图像文本风格迁移。下图是一些该数据合成工具效果图。
+
+<div align="center">
+    <img src="doc/images/2.png" width="1000">
+</div>
+
+<a name="环境配置"></a>
+### 二、环境配置
+
+1. 参考[快速安装](../doc/doc_ch/installation.md)，安装PaddleOCR。
+2. 进入`StyleText`目录，下载模型，并解压：
+
+```bash
+cd StyleText
+wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/style_text_models.zip
+unzip style_text_models.zip
+```
+
+如果您将模型保存再其他位置，请在`configs/config.yml`中修改模型文件的地址，修改时需要同时修改这三个配置：
+
+```
+bg_generator:
+  pretrain: style_text_models/bg_generator
+...
+text_generator:
+  pretrain: style_text_models/text_generator
+...
+fusion_generator:
+  pretrain: style_text_models/fusion_generator
+```
+
+<a name="快速上手"></a>
+### 三、快速上手
+
+#### 合成单张图
+输入一张风格图和一段文字语料，运行tools/synth_image，合成单张图片，结果图像保存在当前目录下：
+
+```python
+python3 tools/synth_image.py -c configs/config.yml --style_image examples/style_images/2.jpg --text_corpus PaddleOCR --language en
+```
+* 注1：语言选项和语料相对应，目前支持英文(en)、简体中文(ch)和韩语(ko)。
+* 注2：Style-Text生成的数据主要应用于OCR识别场景。基于当前PaddleOCR识别模型的设计，我们主要支持高度在32左右的风格图像。
+  如果输入图像尺寸相差过多，效果可能不佳。
+* 注3：可以通过修改配置文件`configs/config.yml`中的`use_gpu`(true或者false)参数来决定是否使用GPU进行预测。
+
+
+例如，输入如下图片和语料"PaddleOCR":
+
+<div align="center">
+    <img src="examples/style_images/2.jpg" width="300">
+</div>
+
+生成合成数据`fake_fusion.jpg`：
+<div align="center">
+    <img src="doc/images/4.jpg" width="300">
+</div>
+
+除此之外，程序还会生成并保存中间结果`fake_bg.jpg`：为风格参考图去掉文字后的背景；
+
+<div align="center">
+    <img src="doc/images/7.jpg" width="300">
+</div>
+
+`fake_text.jpg`：是用提供的字符串，仿照风格参考图中文字的风格，生成在灰色背景上的文字图片。
+
+<div align="center">
+    <img src="doc/images/8.jpg" width="300">
+</div>
+
+#### 批量合成
+在实际应用场景中，经常需要批量合成图片，补充到训练集中。Style-Text可以使用一批风格图片和语料，批量合成数据。合成过程如下：
+
+1. 在`configs/dataset_config.yml`中配置目标场景风格图像和语料的路径，具体如下：
+
+   * `Global`：
+     * `output_dir:`：保存合成数据的目录。
+   * `StyleSampler`：
+     * `image_home`：风格图片目录；
+     * `label_file`：风格图片路径列表文件，如果所用数据集有label，则label_file为label文件路径；
+     * `with_label`：标志`label_file`是否为label文件。
+   * `CorpusGenerator`：
+     * `method`：语料生成方法，目前有`FileCorpus`和`EnNumCorpus`可选。如果使用`EnNumCorpus`，则不需要填写其他配置，否则需要修改`corpus_file`和`language`；
+     * `language`：语料的语种，目前支持英文(en)、简体中文(ch)和韩语(ko)；
+     * `corpus_file`: 语料文件路径。语料文件应使用文本文件。语料生成器首先会将语料按行切分，之后每次随机选取一行。
+
+   语料文件格式示例：
+   ```
+   PaddleOCR
+   飞桨文字识别
+   StyleText
+   风格文本图像数据合成
+   ...
+   ```
+
+   Style-Text也提供了一批中英韩5万张通用场景数据用作文本风格图像，便于合成场景丰富的文本图像，下图给出了一些示例。
+
+   中英韩5万张通用场景数据: [下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)
+
+<div align="center">
+    <img src="doc/images/5.png" width="800">
+</div>
+
+2. 运行`tools/synth_dataset`合成数据：
+
+   ``` bash
+   python3 tools/synth_dataset.py -c configs/dataset_config.yml
+   ```
+   我们在examples目录下提供了样例图片和语料。
+    <div align="center">
+        <img src="examples/style_images/1.jpg" width="300">
+        <img src="examples/style_images/2.jpg" width="300">
+    </div>
+
+   直接运行上述命令，可以在output_data中产生样例输出，包括图片和用于训练识别模型的标注文件：
+   <div align="center">
+       <img src="doc/images/12.png" width="800">
+   </div>
+
+   其中label目录下的标注文件为程序运行过程中产生的缓存，如果程序在中途异常终止，可以使用缓存的标注文件。
+   如果程序正常运行完毕，则会在output_data下生成label.txt，为最终的标注结果。
+
+<a name="应用案例"></a>
+### 四、应用案例
+下面以金属表面英文数字识别和通用韩语识别两个场景为例，说明使用Style-Text合成数据，来提升文本识别效果的实际案例。下图给出了一些真实场景图像和合成图像的示例：
+
+<div align="center">
+    <img src="doc/images/6.png" width="800">
+</div>
+
+在添加上述合成数据进行训练后，识别模型的效果提升，如下表所示：
+
+| 场景     | 字符       | 原始数据 | 测试数据 | 只使用原始数据</br>识别准确率 | 新增合成数据 | 同时使用合成数据</br>识别准确率 | 指标提升 |
+| -------- | ---------- | -------- | -------- | -------------------------- | ------------ | ---------------------- | -------- |
+| 金属表面 | 英文和数字 | 2203     | 650      | 59.38%                     | 20000        | 75.46%                 | 16.08%      |
+| 随机背景 | 韩语       | 5631     | 1230     | 30.12%                     | 100000       | 50.57%                 | 20.45%      |
+
+
+<a name="代码结构"></a>
+### 五、代码结构
+
+```
+StyleText
+|-- arch                        // 网络结构定义文件
+|   |-- base_module.py
+|   |-- decoder.py
+|   |-- encoder.py
+|   |-- spectral_norm.py
+|   `-- style_text_rec.py
+|-- configs                     // 配置文件
+|   |-- config.yml
+|   `-- dataset_config.yml
+|-- engine                      // 数据合成引擎
+|   |-- corpus_generators.py    // 从文本采样或随机生成语料
+|   |-- predictors.py           // 调用网络生成数据
+|   |-- style_samplers.py       // 采样风格图片
+|   |-- synthesisers.py         // 调度各个模块，合成数据
+|   |-- text_drawers.py         // 生成标准文字图片，用作输入
+|   `-- writers.py              // 将合成的图片和标签写入本地目录
+|-- examples                    // 示例文件
+|   |-- corpus
+|   |   `-- example.txt
+|   |-- image_list.txt
+|   `-- style_images
+|       |-- 1.jpg
+|       `-- 2.jpg
+|-- fonts                       // 字体文件
+|   |-- ch_standard.ttf
+|   |-- en_standard.ttf
+|   `-- ko_standard.ttf
+|-- tools                       // 程序入口
+|   |-- __init__.py
+|   |-- synth_dataset.py        // 批量合成数据
+|   `-- synth_image.py          // 合成单张图片
+`-- utils                       // 其他基础功能模块
+    |-- config.py
+    |-- load_params.py
+    |-- logging.py
+    |-- math_functions.py
+    `-- sys_funcs.py
+```