Merge branch 'release/2.6' of https://github.com/PaddlePaddle/PaddleOCR into 26_doc

PPOCRLabel/README.md

@@ -103,7 +103,7 @@ python PPOCRLabel.py --kie True # [KIE mode] for [detection + recognition + keyw
 ```
 
 #### 1.2.3 Build and Install the Whl Package Locally
-Compile and install a new whl package, where 1.0.2 is the version number, you can specify the new version in 'setup.py'.
+Compile and install a new whl package, where 2.1.2 is the version number, you can specify the new version in 'setup.py'.
 ```bash
 cd ./PPOCRLabel
 python3 setup.py bdist_wheel

PPOCRLabel/README_ch.md

@@ -101,7 +101,7 @@ python PPOCRLabel.py --lang ch
 
 #### 1.2.3 本地构建whl包并安装
 
-编译与安装新的whl包，其中1.0.2为版本号，可在 `setup.py` 中指定新版本。
+编译与安装新的whl包，其中2.1.2为版本号，可在 `setup.py` 中指定新版本。
 
 ```bash
 cd ./PPOCRLabel

README.md

@@ -26,6 +26,13 @@ PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools
 </div>
 
 ## 📣 Recent updates
+- 💥 **Live Preview: Oct 24 - Oct 26, China Standard Time, 20:30**, Engineers@PaddleOCR will show PP-StructureV2 optimization strategy for 3 days. 
+  - Scan the QR code below 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.)
+
+<div align="center">
+<img src="https://user-images.githubusercontent.com/50011306/196944258-0eb82df1-d730-4b96-a350-c1d370fdc2b1.jpg"  width = "150" height = "150" />
+</div>
+
 - **🔥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;

README_ch.md

@@ -27,9 +27,15 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力
 
 ## 📣 近期更新
 
+- **💥 直播预告：10.24-10.26日每晚8点半**，PaddleOCR研发团队详解PP-StructureV2优化策略。微信扫描下方二维码，关注公众号并填写问卷后进入官方交流群，获取直播链接与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）
+
+<div align="center">
+<img src="https://user-images.githubusercontent.com/50011306/196944258-0eb82df1-d730-4b96-a350-c1d370fdc2b1.jpg"  width = "150" height = "150" />
+</div>
+
 - **🔥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**；
+  - 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%。

applications/README.md

@@ -58,8 +58,8 @@ PaddleOCR场景应用覆盖通用，制造、金融、交通行业的主要OCR
 | 类别              | 亮点                           | 模型下载       | 教程                                | 示例图                                                       |
 | ----------------- | ------------------------------ | -------------- | ----------------------------------- | ------------------------------------------------------------ |
 | 车牌识别          | 多角度图像、轻量模型、端侧部署 | [模型下载](#2) | [中文](./轻量级车牌识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/76b6a0939c2c4cf49039b6563c4b28e241e11285d7464e799e81c58c0f7707a7"  width = "200" height = "100" /> |
-| 驾驶证/行驶证识别 | 尽请期待                       |                |                                     |                                                              |
-| 快递单识别        | 尽请期待                       |                |                                     |                                                              |
+| 驾驶证/行驶证识别 | 敬请期待                       |                |                                     |                                                              |
+| 快递单识别        | 敬请期待                       |                |                                     |                                                              |
 
 <a name="2"></a>
 

applications/印章弯曲文字识别.md

@@ -75,6 +75,7 @@
 
 本项目中使用[PPOCRLabel](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6/PPOCRLabel)工具标注印章检测数据，标注内容包括印章的位置以及印章中文字的位置和文字内容。
 
+[标注好的8000张印章数据集下载地址](https://aistudio.baidu.com/aistudio/datasetdetail/154271)
 
 注：PPOCRLabel的使用方法参考[文档](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6/PPOCRLabel)。
 

deploy/cpp_infer/readme.md

@@ -158,7 +158,7 @@ build/paddle_inference_install_dir/
 <a name="21"></a>
 ### 2.1 Export the inference model
 
-* You can refer to [Model inference](../../doc/doc_ch/inference.md) and export the inference model. After the model is exported, assuming it is placed in the `inference` directory, the directory structure is as follows.
+* You can refer to [Model inference](../../doc/doc_en/inference_en.md) and export the inference model. After the model is exported, assuming it is placed in the `inference` directory, the directory structure is as follows.
 
 ```
 inference/

deploy/paddle2onnx/readme.md

-# Paddle2ONNX模型转化与预测
+# Paddle2ONNX model transformation and prediction
 
-本章节介绍 PaddleOCR 模型如何转化为 ONNX 模型，并基于 ONNXRuntime 引擎预测。
+This chapter describes how the PaddleOCR model is converted into an ONNX model and predicted based on the ONNXRuntime engine.
 
-## 1. 环境准备
+## 1. Environment preparation
 
-需要准备 PaddleOCR、Paddle2ONNX 模型转化环境，和 ONNXRuntime 预测环境
+Need to prepare PaddleOCR, Paddle2ONNX model conversion environment, and ONNXRuntime prediction environment
 
 ###  PaddleOCR
 
-克隆PaddleOCR的仓库，使用release/2.4分支，并进行安装，由于PaddleOCR仓库比较大，git clone速度比较慢，所以本教程已下载
+Clone the PaddleOCR repository, use the release/2.6 branch, and install it.
 
 ```
-git clone  -b release/2.4 https://github.com/PaddlePaddle/PaddleOCR.git
+git clone  -b release/2.6 https://github.com/PaddlePaddle/PaddleOCR.git
 cd PaddleOCR && python3.7 setup.py install
 ```
 
 ###  Paddle2ONNX
 
-Paddle2ONNX 支持将 PaddlePaddle 模型格式转化到 ONNX 模型格式，算子目前稳定支持导出 ONNX Opset 9~11，部分Paddle算子支持更低的ONNX Opset转换。
-更多细节可参考 [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX/blob/develop/README_zh.md)
+Paddle2ONNX supports converting the PaddlePaddle model format to the ONNX model format. The operator currently supports exporting ONNX Opset 9~11 stably, and some Paddle operators support lower ONNX Opset conversion.
+For more details, please refer to [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX/blob/develop/README_en.md)
 
-- 安装 Paddle2ONNX
+
+- install Paddle2ONNX
 ```
 python3.7 -m pip install paddle2onnx
 ```
 
-- 安装 ONNXRuntime
+- install ONNXRuntime
 ```
-# 建议安装 1.9.0 版本，可根据环境更换版本号
+# It is recommended to install version 1.9.0, and the version number can be changed according to the environment
 python3.7 -m pip install onnxruntime==1.9.0
 ```
 
-## 2. 模型转换
+## 2. Model conversion
 
 
-- Paddle 模型下载
+- Paddle model download
 
-有两种方式获取Paddle静态图模型：在 [model_list](../../doc/doc_ch/models_list.md) 中下载PaddleOCR提供的预测模型；
-参考[模型导出说明](../../doc/doc_ch/inference.md#训练模型转inference模型)把训练好的权重转为 inference_model。
+There are two ways to obtain the Paddle model: Download the prediction model provided by PaddleOCR in [model_list](../../doc/doc_en/models_list_en.md);
+Refer to [Model Export Instructions](../../doc/doc_en/inference_en.md#1-convert-training-model-to-inference-model) to convert the trained weights to inference_model.
 
-以 ppocr 中文检测、识别、分类模型为例：
+Take the PP-OCRv3 detection, recognition, and classification model as an example:
 
 ```
-wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar
-cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && cd ..
+wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar
+cd ./inference && tar xf en_PP-OCRv3_det_infer.tar && cd ..
 
-wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar
-cd ./inference && tar xf ch_PP-OCRv2_rec_infer.tar && cd ..
+wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar
+cd ./inference && tar xf en_PP-OCRv3_rec_infer.tar && cd ..
 
 wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar
 cd ./inference && tar xf ch_ppocr_mobile_v2.0_cls_infer.tar && cd ..
 ```
 
-- 模型转换
+- convert model
 
-使用 Paddle2ONNX 将Paddle静态图模型转换为ONNX模型格式：
+Convert Paddle inference model to ONNX model format using Paddle2ONNX:
 
 ```
-paddle2onnx --model_dir ./inference/ch_PP-OCRv2_det_infer \
+paddle2onnx --model_dir ./inference/en_PP-OCRv3_det_infer \
 --model_filename inference.pdmodel \
 --params_filename inference.pdiparams \
 --save_file ./inference/det_onnx/model.onnx \
@@ -65,7 +66,7 @@ paddle2onnx --model_dir ./inference/ch_PP-OCRv2_det_infer \
 --input_shape_dict="{'x':[-1,3,-1,-1]}" \
 --enable_onnx_checker True
 
-paddle2onnx --model_dir ./inference/ch_PP-OCRv2_rec_infer \
+paddle2onnx --model_dir ./inference/en_PP-OCRv3_rec_infer \
 --model_filename inference.pdmodel \
 --params_filename inference.pdiparams \
 --save_file ./inference/rec_onnx/model.onnx \
@@ -81,136 +82,89 @@ paddle2onnx --model_dir ./inference/ch_ppocr_mobile_v2.0_cls_infer \
 --input_shape_dict="{'x':[-1,3,-1,-1]}" \
 --enable_onnx_checker True
 ```
+After execution, the ONNX model will be saved in `./inference/det_onnx/`, `./inference/rec_onnx/`, `./inference/cls_onnx/` paths respectively
 
-执行完毕后，ONNX 模型会被分别保存在 `./inference/det_onnx/`，`./inference/rec_onnx/`，`./inference/cls_onnx/`路径下
-
-* 注意：对于OCR模型，转化过程中必须采用动态shape的形式，即加入选项--input_shape_dict="{'x': [-1, 3, -1, -1]}"，否则预测结果可能与直接使用Paddle预测有细微不同。
-  另外，以下几个模型暂不支持转换为 ONNX 模型：
-  NRTR、SAR、RARE、SRN
+* Note: For the OCR model, the conversion process must be in the form of dynamic shape, that is, add the option --input_shape_dict="{'x': [-1, 3, -1, -1]}", otherwise the prediction result may be the same as Predicting directly with Paddle is slightly different.
+  In addition, the following models do not currently support conversion to ONNX models:
+  NRTR, SAR, RARE, SRN
 
-## 3. 推理预测
+## 3. prediction
 
-以中文OCR模型为例，使用 ONNXRuntime 预测可执行如下命令：
+Take the English OCR model as an example, use **ONNXRuntime** to predict and execute the following commands:
 
 ```
 python3.7 tools/infer/predict_system.py --use_gpu=False --use_onnx=True \
 --det_model_dir=./inference/det_onnx/model.onnx  \
 --rec_model_dir=./inference/rec_onnx/model.onnx  \
 --cls_model_dir=./inference/cls_onnx/model.onnx  \
---image_dir=./deploy/lite/imgs/lite_demo.png
+--image_dir=doc/imgs_en/img_12.jpg \
+--rec_char_dict_path=ppocr/utils/en_dict.txt
 ```
 
-以中文OCR模型为例，使用 Paddle Inference 预测可执行如下命令：
+Taking the English OCR model as an example, use **Paddle Inference** to predict and execute the following commands:
 
 ```
 python3.7 tools/infer/predict_system.py --use_gpu=False \
 --cls_model_dir=./inference/ch_ppocr_mobile_v2.0_cls_infer \
---rec_model_dir=./inference/ch_PP-OCRv2_rec_infer \
---det_model_dir=./inference/ch_PP-OCRv2_det_infer \
---image_dir=./deploy/lite/imgs/lite_demo.png
+--rec_model_dir=./inference/en_PP-OCRv3_rec_infer \
+--det_model_dir=./inference/en_PP-OCRv3_det_infer \
+--image_dir=doc/imgs_en/img_12.jpg \
+--rec_char_dict_path=ppocr/utils/en_dict.txt
 ```
 
 
-执行命令后在终端会打印出预测的识别信息，并在 `./inference_results/` 下保存可视化结果。
+After executing the command, the predicted identification information will be printed out in the terminal, and the visualization results will be saved under `./inference_results/`.
 
-ONNXRuntime 执行效果：
+ONNXRuntime result：
 
 <div align="center">
-    <img src="./images/lite_demo_onnx.png" width=800">
+    <img src="../../doc/imgs_results/multi_lang/img_12.jpg" width=800">
 </div>
 
-Paddle Inference 执行效果：
+Paddle Inference result：
 
 <div align="center">
-    <img src="./images/lite_demo_paddle.png" width=800">
+    <img src="../../doc/imgs_results/multi_lang/img_12.jpg" width=800">
 </div>
 
 
-使用 ONNXRuntime 预测，终端输出：
-```
-[2022/02/22 17:48:27] root DEBUG: dt_boxes num : 38, elapse : 0.043187856674194336
-[2022/02/22 17:48:27] root DEBUG: rec_res num  : 38, elapse : 0.592170000076294
-[2022/02/22 17:48:27] root DEBUG: 0  Predict time of ./deploy/lite/imgs/lite_demo.png: 0.642s
-[2022/02/22 17:48:27] root DEBUG: The, 0.984
-[2022/02/22 17:48:27] root DEBUG: visualized, 0.882
-[2022/02/22 17:48:27] root DEBUG: etect18片, 0.720
-[2022/02/22 17:48:27] root DEBUG: image saved in./vis.jpg, 0.947
-[2022/02/22 17:48:27] root DEBUG: 纯臻营养护发素0.993604, 0.996
-[2022/02/22 17:48:27] root DEBUG: 产品信息/参数, 0.922
-[2022/02/22 17:48:27] root DEBUG: 0.992728, 0.914
-[2022/02/22 17:48:27] root DEBUG: （45元／每公斤，100公斤起订）, 0.926
-[2022/02/22 17:48:27] root DEBUG: 0.97417, 0.977
-[2022/02/22 17:48:27] root DEBUG: 每瓶22元，1000瓶起订）0.993976, 0.962
-[2022/02/22 17:48:27] root DEBUG: 【品牌】：代加工方式/0EMODM, 0.945
-[2022/02/22 17:48:27] root DEBUG: 0.985133, 0.980
-[2022/02/22 17:48:27] root DEBUG: 【品名】：纯臻营养护发素, 0.921
-[2022/02/22 17:48:27] root DEBUG: 0.995007, 0.883
-[2022/02/22 17:48:27] root DEBUG: 【产品编号】：YM-X-30110.96899, 0.955
-[2022/02/22 17:48:27] root DEBUG: 【净含量】：220ml, 0.943
-[2022/02/22 17:48:27] root DEBUG: Q.996577, 0.932
-[2022/02/22 17:48:27] root DEBUG: 【适用人群】：适合所有肤质, 0.913
-[2022/02/22 17:48:27] root DEBUG: 0.995842, 0.969
-[2022/02/22 17:48:27] root DEBUG: 【主要成分】：鲸蜡硬脂醇、燕麦B-葡聚, 0.883
-[2022/02/22 17:48:27] root DEBUG: 0.961928, 0.964
-[2022/02/22 17:48:27] root DEBUG: 10, 0.812
-[2022/02/22 17:48:27] root DEBUG: 糖、椰油酰胺丙基甜菜碱、泛醒, 0.866
-[2022/02/22 17:48:27] root DEBUG: 0.925898, 0.943
-[2022/02/22 17:48:27] root DEBUG: （成品包材）, 0.974
-[2022/02/22 17:48:27] root DEBUG: 0.972573, 0.961
-[2022/02/22 17:48:27] root DEBUG: 【主要功能】：可紧致头发磷层，从而达到, 0.936
-[2022/02/22 17:48:27] root DEBUG: 0.994448, 0.952
-[2022/02/22 17:48:27] root DEBUG: 13, 0.998
-[2022/02/22 17:48:27] root DEBUG: 即时持久改善头发光泽的效果，给干燥的头, 0.994
-[2022/02/22 17:48:27] root DEBUG: 0.990198, 0.975
-[2022/02/22 17:48:27] root DEBUG: 14, 0.977
-[2022/02/22 17:48:27] root DEBUG: 发足够的滋养, 0.991
-[2022/02/22 17:48:27] root DEBUG: 0.997668, 0.918
-[2022/02/22 17:48:27] root DEBUG: 花费了0.457335秒, 0.901
-[2022/02/22 17:48:27] root DEBUG: The visualized image saved in ./inference_results/lite_demo.png
-[2022/02/22 17:48:27] root INFO: The predict total time is 0.7003889083862305
-```
-
-使用 Paddle Inference 预测，终端输出：
-
-```
-[2022/02/22 17:47:25] root DEBUG: dt_boxes num : 38, elapse : 0.11791276931762695
-[2022/02/22 17:47:27] root DEBUG: rec_res num  : 38, elapse : 2.6206860542297363
-[2022/02/22 17:47:27] root DEBUG: 0  Predict time of ./deploy/lite/imgs/lite_demo.png: 2.746s
-[2022/02/22 17:47:27] root DEBUG: The, 0.984
-[2022/02/22 17:47:27] root DEBUG: visualized, 0.882
-[2022/02/22 17:47:27] root DEBUG: etect18片, 0.720
-[2022/02/22 17:47:27] root DEBUG: image saved in./vis.jpg, 0.947
-[2022/02/22 17:47:27] root DEBUG: 纯臻营养护发素0.993604, 0.996
-[2022/02/22 17:47:27] root DEBUG: 产品信息/参数, 0.922
-[2022/02/22 17:47:27] root DEBUG: 0.992728, 0.914
-[2022/02/22 17:47:27] root DEBUG: （45元／每公斤，100公斤起订）, 0.926
-[2022/02/22 17:47:27] root DEBUG: 0.97417, 0.977
-[2022/02/22 17:47:27] root DEBUG: 每瓶22元，1000瓶起订）0.993976, 0.962
-[2022/02/22 17:47:27] root DEBUG: 【品牌】：代加工方式/0EMODM, 0.945
-[2022/02/22 17:47:27] root DEBUG: 0.985133, 0.980
-[2022/02/22 17:47:27] root DEBUG: 【品名】：纯臻营养护发素, 0.921
-[2022/02/22 17:47:27] root DEBUG: 0.995007, 0.883
-[2022/02/22 17:47:27] root DEBUG: 【产品编号】：YM-X-30110.96899, 0.955
-[2022/02/22 17:47:27] root DEBUG: 【净含量】：220ml, 0.943
-[2022/02/22 17:47:27] root DEBUG: Q.996577, 0.932
-[2022/02/22 17:47:27] root DEBUG: 【适用人群】：适合所有肤质, 0.913
-[2022/02/22 17:47:27] root DEBUG: 0.995842, 0.969
-[2022/02/22 17:47:27] root DEBUG: 【主要成分】：鲸蜡硬脂醇、燕麦B-葡聚, 0.883
-[2022/02/22 17:47:27] root DEBUG: 0.961928, 0.964
-[2022/02/22 17:47:27] root DEBUG: 10, 0.812
-[2022/02/22 17:47:27] root DEBUG: 糖、椰油酰胺丙基甜菜碱、泛醒, 0.866
-[2022/02/22 17:47:27] root DEBUG: 0.925898, 0.943
-[2022/02/22 17:47:27] root DEBUG: （成品包材）, 0.974
-[2022/02/22 17:47:27] root DEBUG: 0.972573, 0.961
-[2022/02/22 17:47:27] root DEBUG: 【主要功能】：可紧致头发磷层，从而达到, 0.936
-[2022/02/22 17:47:27] root DEBUG: 0.994448, 0.952
-[2022/02/22 17:47:27] root DEBUG: 13, 0.998
-[2022/02/22 17:47:27] root DEBUG: 即时持久改善头发光泽的效果，给干燥的头, 0.994
-[2022/02/22 17:47:27] root DEBUG: 0.990198, 0.975
-[2022/02/22 17:47:27] root DEBUG: 14, 0.977
-[2022/02/22 17:47:27] root DEBUG: 发足够的滋养, 0.991
-[2022/02/22 17:47:27] root DEBUG: 0.997668, 0.918
-[2022/02/22 17:47:27] root DEBUG: 花费了0.457335秒, 0.901
-[2022/02/22 17:47:27] root DEBUG: The visualized image saved in ./inference_results/lite_demo.png
-[2022/02/22 17:47:27] root INFO: The predict total time is 2.8338775634765625
+Using ONNXRuntime to predict, terminal output:
+```
+[2022/10/10 12:06:28] ppocr DEBUG: dt_boxes num : 11, elapse : 0.3568880558013916
+[2022/10/10 12:06:31] ppocr DEBUG: rec_res num  : 11, elapse : 2.6445000171661377
+[2022/10/10 12:06:31] ppocr DEBUG: 0  Predict time of doc/imgs_en/img_12.jpg: 3.021s
+[2022/10/10 12:06:31] ppocr DEBUG: ACKNOWLEDGEMENTS, 0.997
+[2022/10/10 12:06:31] ppocr DEBUG: We would like to thank all the designers and, 0.976
+[2022/10/10 12:06:31] ppocr DEBUG: contributors who have been involved in the, 0.979
+[2022/10/10 12:06:31] ppocr DEBUG: production of this book; their contributions, 0.989
+[2022/10/10 12:06:31] ppocr DEBUG: have been indispensable to its creation. We, 0.956
+[2022/10/10 12:06:31] ppocr DEBUG: would also like to express our gratitude to all, 0.991
+[2022/10/10 12:06:31] ppocr DEBUG: the producers for their invaluable opinions, 0.978
+[2022/10/10 12:06:31] ppocr DEBUG: and assistance throughout this project. And to, 0.988
+[2022/10/10 12:06:31] ppocr DEBUG: the many others whose names are not credited, 0.958
+[2022/10/10 12:06:31] ppocr DEBUG: but have made specific input in this book, we, 0.970
+[2022/10/10 12:06:31] ppocr DEBUG: thank you for your continuous support., 0.998
+[2022/10/10 12:06:31] ppocr DEBUG: The visualized image saved in ./inference_results/img_12.jpg
+[2022/10/10 12:06:31] ppocr INFO: The predict total time is 3.2482550144195557
+```
+
+Using Paddle Inference to predict, terminal output:
+
+```
+[2022/10/10 12:06:28] ppocr DEBUG: dt_boxes num : 11, elapse : 0.3568880558013916
+[2022/10/10 12:06:31] ppocr DEBUG: rec_res num  : 11, elapse : 2.6445000171661377
+[2022/10/10 12:06:31] ppocr DEBUG: 0  Predict time of doc/imgs_en/img_12.jpg: 3.021s
+[2022/10/10 12:06:31] ppocr DEBUG: ACKNOWLEDGEMENTS, 0.997
+[2022/10/10 12:06:31] ppocr DEBUG: We would like to thank all the designers and, 0.976
+[2022/10/10 12:06:31] ppocr DEBUG: contributors who have been involved in the, 0.979
+[2022/10/10 12:06:31] ppocr DEBUG: production of this book; their contributions, 0.989
+[2022/10/10 12:06:31] ppocr DEBUG: have been indispensable to its creation. We, 0.956
+[2022/10/10 12:06:31] ppocr DEBUG: would also like to express our gratitude to all, 0.991
+[2022/10/10 12:06:31] ppocr DEBUG: the producers for their invaluable opinions, 0.978
+[2022/10/10 12:06:31] ppocr DEBUG: and assistance throughout this project. And to, 0.988
+[2022/10/10 12:06:31] ppocr DEBUG: the many others whose names are not credited, 0.958
+[2022/10/10 12:06:31] ppocr DEBUG: but have made specific input in this book, we, 0.970
+[2022/10/10 12:06:31] ppocr DEBUG: thank you for your continuous support., 0.998
+[2022/10/10 12:06:31] ppocr DEBUG: The visualized image saved in ./inference_results/img_12.jpg
+[2022/10/10 12:06:31] ppocr INFO: The predict total time is 3.2482550144195557
 ```

deploy/pdserving/README.md

@@ -42,7 +42,7 @@ The introduction and tutorial of Paddle Serving service deployment framework ref
 
 PaddleOCR operating environment and Paddle Serving operating environment are needed.
 
-1. Please prepare PaddleOCR operating environment reference [link](../../doc/doc_ch/installation.md).
+1. Please prepare PaddleOCR operating environment reference [link](../../doc/doc_en/installation_en.md).
    Download the corresponding paddlepaddle whl package according to the environment, it is recommended to install version 2.2.2.
 
 2. The steps of PaddleServing operating environment prepare are as follows:

doc/doc_ch/algorithm_overview.md

@@ -99,9 +99,9 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广
 |SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
 |ViTSTR|ViTSTR| 79.82% | rec_vitstr_none_ce | [训练模型](https://paddleocr.bj.bcebos.com/rec_vitstr_none_ce_train.tar) |
 |ABINet|Resnet45| 90.75% | rec_r45_abinet | [训练模型](https://paddleocr.bj.bcebos.com/rec_r45_abinet_train.tar) |
-|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar) |
-|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | coming soon |
-|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | coming soon |
+|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar) |
+|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_r32_gaspin_bilstm_att.tar) |
+|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)|
 
 
 <a name="2"></a>

doc/doc_ch/algorithm_rec_visionlan.md

@@ -27,7 +27,7 @@
 
 |模型|骨干网络|配置文件|Acc|下载链接|
 | --- | --- | --- | --- | --- |
-|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)|
+|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)|
 
 <a name="2"></a>
 ## 2. 环境配置
@@ -80,7 +80,7 @@ python3 tools/infer_rec.py -c configs/rec/rec_r45_visionlan.yml -o Global.infer_
 
 <a name="4-1"></a>
 ### 4.1 Python推理
-首先将训练得到best模型，转换成inference model。这里以训练完成的模型为例（[模型下载地址](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar))，可以使用如下命令进行转换：
+首先将训练得到best模型，转换成inference model。这里以训练完成的模型为例（[模型下载地址](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar))，可以使用如下命令进行转换：
 
 ```shell
 # 注意将pretrained_model的路径设置为本地路径。
@@ -139,7 +139,7 @@ Predicts of ./doc/imgs_words/en/word_2.png:('yourself', 0.9999493)
 ## 5. FAQ
 
 1. MJSynth和SynthText两种数据集来自于[VisionLAN源repo](https://github.com/wangyuxin87/VisionLAN) 。
-2. 我们使用VisionLAN作者提供的预训练模型进行finetune训练。
+2. 我们使用VisionLAN作者提供的预训练模型进行finetune训练，预训练模型配套字典为'ppocr/utils/ic15_dict.txt'。
 
 ## 引用
 

doc/doc_en/algorithm_overview_en.md

@@ -96,9 +96,9 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
 |SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
 |ViTSTR|ViTSTR| 79.82% | rec_vitstr_none_ce | [trained model](https://paddleocr.bj.bcebos.com/rec_vitstr_none_none_train.tar) |
 |ABINet|Resnet45| 90.75% | rec_r45_abinet | [trained model](https://paddleocr.bj.bcebos.com/rec_r45_abinet_train.tar) |
-|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [trained model](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar) |
-|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | coming soon |
-|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | coming soon |
+|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [trained model](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar) |
+|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_r32_gaspin_bilstm_att.tar) |
+|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)|
 
 
 <a name="2"></a>

doc/doc_en/algorithm_rec_visionlan_en.md

@@ -25,7 +25,7 @@ Using MJSynth and SynthText two text recognition datasets for training, and eval
 
 |Model|Backbone|config|Acc|Download link|
 | --- | --- | --- | --- | --- |
-|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)|
+|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)|
 
 <a name="2"></a>
 ## 2. Environment
@@ -68,7 +68,7 @@ python3 tools/infer_rec.py -c configs/rec/rec_r45_visionlan.yml -o Global.infer_
 
 <a name="4-1"></a>
 ### 4.1 Python Inference
-First, the model saved during the VisionLAN text recognition training process is converted into an inference model. ( [Model download link](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)) ), you can use the following command to convert:
+First, the model saved during the VisionLAN text recognition training process is converted into an inference model. ( [Model download link](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)) ), you can use the following command to convert:
 
 ```
 python3 tools/export_model.py -c configs/rec/rec_r45_visionlan.yml -o Global.pretrained_model=./rec_r45_visionlan_train/best_accuracy Global.save_inference_dir=./inference/rec_r45_visionlan/
@@ -120,7 +120,7 @@ Not supported
 ## 5. FAQ
 
 1. Note that the MJSynth and SynthText datasets come from [VisionLAN repo](https://github.com/wangyuxin87/VisionLAN).
-2. We use the pre-trained model provided by the VisionLAN authors for finetune training.
+2. We use the pre-trained model provided by the VisionLAN authors for finetune training. The dictionary for the pre-trained model is 'ppocr/utils/ic15_dict.txt'.
 
 ## Citation
 

doc/doc_en/inference_ppocr_en.md

@@ -84,9 +84,9 @@ For English recognition model inference, you can execute the following commands,
 
 ```
 # download en model：
-wget https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar
-tar xf en_PP-OCRv3_det_infer.tar
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./en_PP-OCRv3_det_infer/" --rec_char_dict_path="ppocr/utils/en_dict.txt"
+wget https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar
+tar xf en_PP-OCRv3_rec_infer.tar
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./en_PP-OCRv3_rec_infer/" --rec_char_dict_path="ppocr/utils/en_dict.txt"
 ```
 
 ![](../imgs_words/en/word_1.png)

doc/doc_en/ppocr_introduction_en.md

@@ -64,7 +64,7 @@ For more details, please refer to [PP-OCRv3 technical report](https://arxiv.org/
 For the performance comparison between PP-OCR series models, please check the [benchmark](./benchmark_en.md) documentation.
 
 <a name="4"></a>
-## 4. Visualization [more](./visualization.md)
+## 4. Visualization [more](./visualization_en.md)
 
 <details open>
 <summary>PP-OCRv3 Chinese model</summary>

doc/doc_en/recognition_en.md

@@ -26,7 +26,7 @@
 
 ### 1.1 DataSet Preparation
 
-To prepare datasets, refer to [ocr_datasets](./dataset/ocr_datasets.md) .
+To prepare datasets, refer to [ocr_datasets](./dataset/ocr_datasets_en.md) .
 
 PaddleOCR provides label files for training the icdar2015 dataset, which can be downloaded in the following ways:
 

doc/doc_i18n/README_Ру́сский язы́к.md

+English | [简体中文](README_ch.md)
+
+<p align="center">
+ <img src="../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>
+
+
+## Введение
+
+PaddleOCR стремится создавать многоязычные, потрясающие, передовые и практичные инструменты OCR, которые помогают пользователям обучать лучшие модели и применять их на практике
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/187821591-6cb09459-fdbf-4ad3-8c5a-26af611c211d.png" width="800">
+</div>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_4.png" width="800">
+</div>
+
+
+
+<div align="center">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+
+
+## 📣 Последние обновления
+- **🔥2022.8.24 Выпуск PaddleOCR [Выпуск /2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+     - Выпускать [PP-Structurev2](./ppstructure/)，с полностью обновленными функциями и производительностью, адаптированными для китайских сцен и новой поддержкой pаспознавание таблиц
+     [Восстановление макета](./ppstructure/recovery) и **однострочная команда для преобразования PDF в Word**;
+     - [Анализ макета](./ppstructure/layout) оптимизация: память модели уменьшена на 95%, а скорость увеличена в 11 раз, а среднее время процессорного времени составляет всего 41 мс;
+     - [Распознавание таблиц](./ppstructure/table) оптимизация: разработано 3 стратегии оптимизации, а точность модели улучшена на 6% при сопоставимых затратах времени;
+     - [Извлечение ключевой информации](./ppstructure/kie) оптимизация: разработана визуально независимая структура модели, точность распознавания семантической сущности увеличена на 2,8%, а точность извлечения отношения увеличена на 9,1%.
+- **🔥2022.7 Выпуск [Коллекция приложений сцены OCR](../../applications/README_en.md)**
+- Выпуск **9 вертикальных моделей**, таких как цифровая трубка, ЖК-экран, номерной знак, модель распознавания рукописного ввода, высокоточная модель SVTR и т. д., охватывающих основные вертикальные приложения OCR в целом, производственной, финансовой и транспортной отраслях.
+- **🔥2022.5.9 Выпуск PaddleOCR [Выпуск /2.5](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.5)**
+- Выпускать [PP-OCRv3](../doc_en/ppocr_introduction_en.md#pp-ocrv3): При сопоставимой скорости эффект китайской сцены улучшен на 5% по сравнению с ПП-OCRRv2, эффект английской сцены улучшен на 11%, а средняя точность распознавания 80 языковых многоязычных моделей улучшена более чем на 5%.   
+ - Выпускать [PPOCRLabelv2](./PPOCRLabel): Добавьте функцию аннотации для задачи распознавания таблиц, задачи извлечения ключевой информации и изображения неправильного текста.
+     - Выпустить интерактивную электронную книгу [*"Погружение в OCR"*](../doc_en/ocr_book_en.md), охватывает передовую теорию и практику кодирования технологии полного стека OCR.
+- [подробнее](../doc_en/update_en.md)
+
+
+## 🌟 Функции  
+
+PaddleOCR поддерживает множество передовых алгоритмов, связанных с распознаванием текста, и разработала промышленные модели/решения. [PP-OCR](../doc_en/ppocr_introduction_en.md) и [PP-Structure](./ppstructure/README.md) на этой основе и пройти весь процесс производства данных, обучения модели, сжатия, логического вывода и развертывания.
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/196963669-f53b0ee5-3cb4-481c-b73c-97c4b3e2efb8.png">
+</div>
+
+
+
+
+## ⚡ Быстрый опыт
+
+```bash
+pip3 install paddlepaddle # for gpu user please install paddlepaddle-gpu
+pip3 install paddleocr
+paddleocr --image_dir /your/test/image.jpg --lang=ru
+```
+
+> Если у вас нет среды Python, выполните [Подготовка среды](../doc_en/environment_en.md). Мы рекомендуем вам начать с [Учебники](#Tutorials).
+
+<a name="книга"></a>
+
+## 📚 Электронная книга: *Погружение в OCR*
+- [Погружение в распознавание символов](../doc_en/ocr_book_en.md)
+
+<a name="Сообщество"></a>
+
+## 👫 Сообщество 
+
+Что касается международных разработчиков, мы рассматриваем [Обсуждения PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR/discussions) как нашу платформу для международного сообщества. Все идеи и вOCRосы можно обсудить здесь на английском языке.
+
+<a name="Список-поддерживаемых-китайских-моделей"></a>
+
+## 🛠️ Список моделей серии ПП -OCR
+
+| Введение модели | Название модели | Рекомендуемая сцена | Модель обнаружения | Модель распознавания |
+| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| Ру́сский язы́к：Ру́сский язы́к Сверхлегкая модель ПП-OCRv3 (13.4M) | cyrillic_PP-OCRv3_xx | Мобильный и сервер |[модель вывода](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar)/[обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) | [модель вывода](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar)/[обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_train.tar)  |
+| Английский сверхлегкая модель ПП-OCRv3 (13,4 Мб) | en\_ПП-OCRv3_xx |Мобильный и сервер | [модель вывода](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [вывод модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+| Сверхлегкая китайская и английская модель ПП-OCRv3 (16,2M) | ch\_ПП-OCRv3_xx | Мобильный и сервер | [вывод модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [вывод модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [обученный модель](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+
+- Для получения дополнительных загрузок моделей (включая несколько языков) см. [Загрузки моделей серии ПП-OCR](../doc_en/models_list_en.md).
+- Для запроса нового языка см [Руководство для новых языковых_запросов](#language_requests).
+- Модели структурного анализа документов см [PP-Structure модельs](./ppstructure/docs/модельs_list_en.md).
+
+<a name=" Учебники "></a>
+
+## 📖 Учебники 
+
+- [Подготовка окружающей среды](../doc_en/environment_en.md)
+- [PP-OCR 🔥](../doc_en/ppocr_introduction_en.md)
+  
+	- [Быстрый старт](../doc_en/quickstart_en.md)
+    - [Модель Zoo](../doc_en/модельs_en.md)
+    - [Модель тренировки](../doc_en/training_en.md)
+    - [Обнаружение текста](../doc_en/detection_en.md)
+      - [Распознавание текста](../doc_en/recognition_en.md)
+      - [Классификация направления текста](../doc_en/angle_class_en.md)
+    - Модель Сжатие
+        - [Модель квантования](./deploy/slim/quantization/README_en.md)
+        - [Модель Обрезка](./deploy/slim/prune/README_en.md)
+        - [Дистилляция знаний](../doc_en/knowledge_distillation_en.md)
+    - [Вывод и развертывание](./deploy/README.md)
+        - [Python Вывод](../doc_en/ inference _ppocr_en.md)
+        - [Вывод C++](./deploy/cpp_infer/readme.md)
+        -[Подача](./deploy/pdserving/README.md)
+        - [Мобильный](./deploy/lite/readme.md)
+        - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
+        -[ВеслоОблако](./deploy/paddlecloud/README.md)
+        - [Benchmark](../doc_en/benchmark_en.md)  
+- [PP-Structure 🔥](../../ppstructure/README.md)
+  - [Быстрый старт](../../ppstructure/docs/quickstart_en.md)
+    - [Модель Zoo](../../ppstructure/docs/models_list_en.md)
+    - [Модель тренировки](../doc_en/training_en.md)  
+   - [Анализ макета](../../ppstructure/layout/README.md)
+        - [Распознавание таблиц](../../ppstructure/table/README.md)
+        - [Извлечение ключевой информации](../../ppstructure/kie/README.md)
+    - [Вывод и развертывание](./deploy/README.md)
+        - [Вывод Python](../../ppstructure/docs/inference_en.md)
+        - [Вывод С++](../../deploy/cpp_infer/readme.md)
+        - [Обслуживание](../../deploy/hubserving/readme_en.md)
+- [Академические алгоритмы](../doc_en/algorithm_overview_en.md)
+    - [Обнаружение текста](../doc_en/algorithm_overview_en.md)
+- [Распознавание текста](../doc_en/algorithm_overview_en.md)
+    - [Непрерывной цепью OCR](../doc_en/algorithm_overview_en.md)
+    - [Распознавание таблиц](../doc_en/algorithm_overview_en.md)
+    - [Извлечение ключевой информации](../doc_en/algorithm_overview_en.md) 
+    - [Добавьте новые алгоритмы в PaddleOCR](../doc_en/add_new_algorithm_en.md)
+- Аннотации и синтез данных
+  - [Полуавтоматический инструмент аннотации данных: метка ППOCRR](./PPOCRLabel/README.md)
+  - [Инструмент синтеза данных: Стиль-текст](./StyleText/README.md)
+  - [Другие инструменты аннотирования данных](../doc_en/data_annotation_en.md)
+  - [Другие инструменты синтеза данных](../doc_en/data_synthesis_en.md)
+- Наборы данных
+    - [Общие наборы данных OCR (китайский/английский)](../doc_en/dataset/datasets_en.md)
+    - [Наборы данных Рукописный/_OCR_ наборы данных (китайский)](../doc_en/dataset/handwritten_datasets_en.md)
+    - [Различные наборы данных OCR (многоязычные)](../doc_en/dataset/vertical_and_multilingual_datasets_en.md)
+    - [Анализ макета](../doc_en/dataset/layout_datasets_en.md)
+    - [Распознавание таблиц](../doc_en/dataset/table_datasets_en.md)
+    - [Извлечение ключевой информации](../doc_en/dataset/kie_datasets_en.md)
+- [Структура кода](../doc_en/tree_en.md)
+- [Визуализация](#Visualization)
+- [Сообщество](#Community)
+- [Новые языковые запросы](#language_requests)
+- [ЧАСТО ЗАДАВАЕМЫЕ ВOCRОСЫ](../doc_en/FAQ_en.md)
+- [Использованная литература](../doc_en/reference_en.md)
+- [ЛИЦЕНЗИЯ](#LICENSE)
+
+<a name="language_requests"></a>
+
+## 🇺🇳 Руководство по запросам на новый язык
+
+Если вы хотите **запросить новую языковую модель**, проголосуйте в [Голосуйте за обновление многоязычной модели](https://github.com/PaddlePaddle/PaddleOCR/discussions/7253). Мы будем регулярно обновлять модель по результату. **Пригласите друзей проголосовать вместе!**
+
+Если вам нужно **обучить новую языковую модель** на основе вашего сценария, учебное пособие в [Проекте обучения многоязычной модели](https://github.com/PaddlePaddle/PaddleOCR/discussions/7252) поможет вам подготовить набор данных и показать вам весь процесс шаг за шагом.
+
+Оригинальный [Многоязычный план разработки OCR](https://github.com/PaddlePaddle/PaddleOCR/issues/1048) по-прежнему показывает вам много полезных корпусов и словарей.
+
+<a name=" Визуализация "></a>
+
+## 👀 Визуализация [больше](../doc_en/visualization_en.md) 
+
+<details open>
+<summary>PP-OCRv3 Многоязычная модель </summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-OCRv3 Aнглийская модель </summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="../imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+</details>
+<details open>
+<summary>PP-OCRv3 Kитайская модель </summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-Structurev2</summary>
+1. анализ макета + распознавание таблиц
+<div align="center">
+    <img src="../../ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+2. SER (Семантическое распознавание объектов)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094456-01a1dd11-1433-4437-9ab2-6480ac94ec0a.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>
+3. RE (Извлечение отношений)
+<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="ЛИЦЕНЗИЯ"></a>
+
+## 📄 Лицензия 
+Этот проект выпущен под <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>

doc/doc_i18n/README_हिन्द.md

+English | [简体中文](README_ch.md)
+
+<p align="center">
+ <img src="../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>
+
+
+## प्रस्तावना
+पैडलओसीआर का उद्देश्य बहुभाषी,शानदार , ओसीआर और व्यावहारिक ओसीआरउपकरण बनाना है जो यूजर्स को बेहतर मॉडलों  के लिए प्रशिक्षित करने और उन्हें व्यवहार में लागू करने में मदद करते हैं।
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/187821591-6cb09459-fdbf-4ad3-8c5a-26af611c211d.png" width="800">
+</div>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_4.png" width="800">
+</div>
+
+
+<div align="center">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+
+## 📣 हाल के अद्यतन
+- **🔥2022.8.24 रिलीज Paddleओसीआर [रिलीज/2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+  -  रिलीज [PP-Structurev2](../../ppstructure)，फंक्शन और परफॉरमेंस के साथ पूरी तरह से उन्नत, चायनीज शीन्स के अनुकूल, और मदद के लिए [लेआउट रिकवरी](../../ppstructure/recovery) और **पीडीएफ को वर्ड में बदलने के लिए वन लाइन कमांड**;
+  - [लेआउट एनालाइस](../../ppstructure/layout) ऑप्टिमाइजेशन: मॉडल स्टोरेज में 95% की कमी, जबकि स्पीड में 11 गुना वृद्धि , और एवरेज CPU स टाइम-कॉस्ट केवल 41ms है;
+  - [टेबल रिकोगनाइजेशन](../../ppstructure/table) ऑप्टिमाइजेशन: 3 ऑप्टिमाइज़ेशन के तरीके डिजाइन किए गए हैं, और तुलनात्मक समय की खपत के तहत मॉडल सटीकता में 6% का सुधार हुआ है;
+  - [की इंफॉर्मेशन एक्स्ट्रेक्शन](../../ppstructure/kie) ऑप्टिमाइजेशन : एक बिजुवल-स्वतंत्र मॉडल संरचना डिजाइन की गई है, सिमेंटिक एन्टाइटी रिकग्निशन की सटीकता में 2.8% की वृद्धि हुई है, और रिलेशन एक्सट्रैक्शन की सटीकता में 9.1% की वृद्धि हुई है।
+
+- **🔥2022.7 रिलीज [ओसीआर दृश्य आवेदन संग्रह](../../applications/README_en.md)**
+  - रिलीज **9 वर्टिकल मॉडल** जैसे कि डिजिटल ट्यूब, एलसीडी स्क्रीन, लाइसेंस प्लेट, हस्तलेखन पहचान मॉडल, उच्च-सटीक एसवीटीआर मॉडल, आदि, जो सामान्य रूप से मुख्य ओसीआर वर्टिकल अनुप्रयोगों, विनिर्माण, वित्त और परिवहन उद्योगों को कवर करते हैं।
+
+- **🔥2022.5.9 रिलीज Paddleओसीआर [रिलीज/2.5](https://github.com/PaddlePaddle/Paddleओसीआर/tree/release/2.5)**
+    - रिलीज [PP-OCRv3](../doc_en/ppocr_introduction_en.md#pp-ocrv3):      तुलनात्मक स्पीड के साथ, चाइनीज शीन्स का प्रभाव PP-ओसीआर v2 की तुलना में 5% की और वृद्धि हुयी है इंगलिस शीन्स के प्रभाव में 11% का  सुधार हुआ है, और 80 भाषाओं के बहुभाषी मॉडलों की औसत पहचान सटीकता में 5% से अधिक सुधार हुआ है।
+    - रिलीज़ [PPOCRLabelv2](./PPOCRLabel): टेबल टेबल रिकोगनाइजेशन टास्क की इंफॉर्मेशन एक्स्ट्रेक्शन टास्क और अनियमित  टेक्सट इमेज के लिए एनोटेशन फ़ंक्शन एड करे।
+
+    - इंटरएक्टिव ई-बुक जारी करें [*"ओसीआर में गोता लगाएँ"*](../doc_en/ocr_book_en.md), ओसीआर पूर्ण स्टैक तकनीक के अत्याधुनिक सिद्धांत और कोड प्रेक्टिस को कवर करता है।
+
+- [और अधिक](../doc_en/update_en.md)
+
+
+## 🌟 विशेषताएँ 
+
+Paddleओसीआर से संबंधित विभिन्न प्रकार के अत्याधुनिक एल्गोरिथ्म को सपोर्ट करता है, और विकसित औद्योगिक विशेष रुप से प्रदर्शित मॉडल/समाधान [PP- OCR](../doc_en/ppocr_introduction_en.md) और [PP-Structure](../../ppstructure/README.md) इस आधार पर और डेटा प्रोडक्शन की पूरी प्रोसेस के माध्यम से प्राप्त करें, मॉडल ट्रेनिंग, दबाव, अनुमान और  तैनाती।
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/196920323-9d386ab0-1233-4415-8508-99d459d256bb.png">
+</div>
+
+## ⚡ शीघ्र अनुभव 
+
+```bash
+pip3 install paddlepaddle # for gpu user please install paddlepaddle-gpu
+pip3 install paddleocr
+paddleocr --image_dir /your/test/image.jpg --lang=hi
+```
+
+> यदि आपके पास पायथन एनवायरनमेंट नहीं है, कृपया फॉलो कीजिए [एनवायरनमेंट प्रिपेरेशन](../doc_en/environment_en.md).    हम अनुशंसा करते हैं कि आप इसके साथ शुरुआत करें [ट्यूटोरियल](#Tutorials).
+
+<a name="किताब"></a>
+
+## 📚 ई-बुक: *ओसीआर में गोता लगाएँ*
+- [ओसीआर में गोता लगाएँ](../doc_en/ocr_book_en.md)
+
+<a name="कम्युनिटी"></a>
+
+## 👫 समुदाय
+
+अंतरराष्ट्रीय डेवलपर्स के लिए, हम सम्मान करते हैं [पैडलओसीआर चर्चाएँ] (https://github.com/PaddlePaddle/PaddleOCR/discussions) हमारे अंतरराष्ट्रीय कम्युनिटी मंच के रूप में। यहां सभी विचारों और प्रश्नों पर अंग्रेजी में चर्चा की जा सकती है।
+
+<a name="समर्थित-चीनी-मॉडल-लिस्ट"></a>
+
+## 🛠️ PP-ओसीआर श्रृंखला मॉडल सूची
+
+|     मॉडल   प्रस्तावना                                                                                    |          मॉडल    नाम                 | रिकमेंडिड  सीन    |   डिटेक्शन मॉडल                                                                                 | रिकोगनाइजेशन मॉडल                                                                        |
+| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| हिन्दी：हिन्दी अल्ट्रा-लाइटवेट PP-ओसीआरv3 सिस्टम (9.9M) | devanagari_PP-ओसीआरv3_xx | मोबाइल और सर्वर |[इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar) / [प्रशिक्षितमॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) | [इन्फरन्समॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_train.tar) |
+| इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल （13.4M） | en_PP-ओसीआरv3_xx  | मोबाइल और  सर्वर  | [इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [प्रशिक्षितमॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar)| [इन्फरन्समॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+| चाइनीस और इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल（16.2M）     | ch_PP-ओसीआरv3_xx          | मोबाइल और सर्वर | [इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+
+
+- अधिक मॉडल डाउनलोड (एकाधिक भाषाओं सहित) के लिए, कृपया [PP-ओसीआर सीरीज मॉडल डाउनलोड](../doc_en/models_list_en.md) देखें।
+- एक नए भाषा अनुरोध के लिए, कृपया [नई भाषा अनुरोधों के लिए दिशानिर्देश](#language_requests).
+- स्ट्रक्चर मॉडल डोकोमेंट एनालाइज के लिए, कृपया देखें [PP-Structure models](../../ppstructure/docs/models_list_en.md).
+
+<a name="ट्यूटोरियल"></a>
+
+## 📖 ट्यूटोरियल
+
+- [एनवायरनमेंट प्रिपरेशन](../doc_en/environment_en.md)
+- [PP-OCR 🔥](../doc_en/ppocr_introduction_en.md)
+    - [क्विक स्टार्ट](../doc_en/quickstart_en.md)
+    - [मॉडल जू](../doc_en/models_en.md)
+    - [मॉडल ट्रेनिंग](../doc_en/training_en.md)
+        - [टेक्सट डिटेक्शन](../doc_en/detection_en.md)
+        - [टेक्सट रिकोगनीशन](../doc_en/recognition_en.md)
+        - [टेक्सट डायरेक्शन क्लासिफिकेशन](../doc_en/angle_class_en.md)
+    - मॉडल कम्प्रेशन 
+        - [मॉडल परिमाणीकरण](./deploy/slim/quantization/README_en.md)
+        - [मॉडल प्रूनिंग](./deploy/slim/prune/README_en.md)
+        - [ज्ञान आसवन](../doc_en/knowledge_distillation_en.md)
+    - [इन्फरन्स और डिप्लोमेन्ट](./deploy/README.md)
+        - [Python इन्फरन्स](../doc_en/inference_ppocr_en.md)
+        - [C++ इन्फरन्स](./deploy/cpp_infer/readme.md)
+        - [सरविंग](./deploy/pdserving/README.md)
+        - [मोबाइल](./deploy/lite/readme.md)
+        - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
+        - [पैडल क्लाउड](./deploy/paddlecloud/README.md)
+        - [Benchmark](../doc_en/benchmark_en.md)
+- [PP-Structure 🔥](../../ppstructure/README.md)
+    - [क्विक स्टार्ट](../../ppstructure/docs/quickstart_en.md)
+    - [मॉडल जू](../../ppstructure/docs/models_list_en.md)
+    - [मॉडल ट्रेनिंग](../doc_en/training_en.md)  
+        - [लेआउट एनालाइस](../../ppstructure/layout/README.md)
+        - [टेबल रिकोगनाइजेशन](../../ppstructure/table/README.md)
+        - [की इंफॉर्मेशन एक्स्ट्रेक्शन](../../ppstructure/kie/README.md)
+    - [इन्फरन्स और डिप्लोमेन्ट](./deploy/README.md)
+        - [Python इन्फरन्स](../../ppstructure/docs/inference_en.md)
+        - [C++ इन्फरन्स](./deploy/cpp_infer/readme.md)
+        - [सरविंग](./deploy/hubserving/readme_en.md)
+- [एकेडमिक एल्गोरिथम](../doc_en/algorithm_overview_en.md)
+    - [टेक्स्ट डिनेक्शन](../doc_en/algorithm_overview_en.md)
+    - [टेक्स्ट रिकोगनाइजेशन](../doc_en/algorithm_overview_en.md)
+    - [एंड-टू-एंड ओसीआर](../doc_en/algorithm_overview_en.md)
+    - [टेबल रिकोगनाइजेशन](../doc_en/algorithm_overview_en.md)
+    - [की इंफॉर्मेशन एक्स्ट्रेक्शन](../doc_en/algorithm_overview_en.md)    
+    - [पैडलओसीआर में नए एल्गोरिदम जोड़ें](../doc_en/add_new_algorithm_en.md)
+- डेटा एनोटेशन और सिंथेसिस
+    - [सेमी-ऑटोमैटिक एनोटेशन टूल: PPओसीआरलेबल](./PPOCRLabel/README.md)
+    - [डेटा सिंथेसिस टूल: स्टाइल-टेक्सट](./StyleText/README.md)
+    - [अन्य डेटा एनोटेशन टूल](../doc_en/data_annotation_en.md)
+    - [अन्य डेटा सिंथेसिस टूल](../doc_en/data_synthesis_en.md)
+- डेटा सेट
+    - [सामान्य ओसीआर डेटासेट (चीनी/अंग्रेज़ी)](../doc_en/dataset/datasets_en.md)
+    - [हस्तलिखित_ओसीआर_डेटासेट (चीनी)](../doc_en/dataset/handwritten_datasets_en.md)
+    - [विभिन्न ओसीआर 
+    डेटासेट (बहुभाषी)](../doc_en/dataset/vertical_and_multilingual_datasets_en.md)
+    - [लेआउट एनालाइस](../doc_en/dataset/layout_datasets_en.md)
+    - [टेबल रिकोगनाइजेशन](../doc_en/dataset/table_datasets_en.md)
+    - [की इंफॉर्मेशन एक्स्ट्रेक्शन](../doc_en/dataset/kie_datasets_en.md)
+- [कोड संरचना](../doc_en/tree_en.md)
+- [विसुमलाइजेशन](#Visualization)
+- [कम्युनिटी](#Community)
+- [नई भाषा के लिए अनुरोध](#language_requests)
+- [सामान्य प्रश्न](../doc_en/FAQ_en.md)
+- [रेफरेन्सेस](../doc_en/reference_en.md)
+- [लाइसेंस](#LICENSE)
+
+<a name="language_requests"></a>
+
+## 🇺🇳 नई भाषा अनुरोधों के लिए संयुक्त राष्ट्र दिशानिर्देश
+
+अगर आप **एक नए भाषा मॉडल का अनुरोध करना चाहते हैं**, तो कृपया [बहुभाषी मॉडल अपग्रेड के लिए वोट करें](https://github.com/PaddlePaddle/PaddleOCR/discussions/7253) में वोट करें। हम नियमित रूप से परिणाम के अनुसार मॉडल को अपग्रेड करेंगे। **अपने दोस्तों को एक साथ वोट करने के लिए आमंत्रित करें!**
+
+यदि आपको **एक नए भाषा मॉडल को प्रशिक्षित करने** अपने परिदृश्य के आधार पर, तो यह [बहुभाषी  मॉडल  ट्रेनिंग  प्रोजेक्ट  ट्रेनिंग](https://github.com/PaddlePaddle/PaddleOCR/discussions/7252) ट्यूटोरियल आपको डेटासेट तैयार करने में मदद करेगा और आपको स्टेप बाए स्टेप पूरा प्रोसेस दिखाएगा
+
+मूल [बहुभाषी ओसीआर विकास योजना](https://github.com/PaddlePaddle/PaddleOCR/issues/1048) अभी भी आपको बहुत सारे उपयोगी संग्रह और शब्दकोश दिखाता है
+
+<a name="विसुमलाइजेशन"></a>
+
+## 👀 विज़ुअलाइज़ेशन [अधिक](../doc_en/visualization_en.md)
+
+<details open>
+<summary>PP-OCRv3 बहुभाषी मॉडल</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-OCRv3 अंग्रेजी मॉडल</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="../imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+</details>
+<details open>
+<summary>PP-OCRv3 चीनी मॉडल</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-Structurev2</summary>
+1. लेआउट एनालाइस + टेबल रिकोगनाइजेशन
+<div align="center">
+    <img src="../../ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+2. SER (सिमेंटिक एंटिटी रिकोगनाइजेशन)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094456-01a1dd11-1433-4437-9ab2-6480ac94ec0a.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>
+3. RE (रिलेशन एक्सट्रैक्शन)
+<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="लाइसेंस"></a>
+
+## 📄 लाइसेंस
+इस प्रोजेक्ट को इन परियोजना के तहत जारी किया गया है <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>

doc/doc_i18n/README_日本語.md

+English | [简体中文](README_ch.md)
+
+<p align="center">
+<img src="../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>
+
+
+## 紹介
+
+PaddleOCR は、さまざまな言語で、優れた最先端かつ実用的な OCR ツールを作成することを目的とし、ユーザーがより優れたモデルをトレーニングし、実践的に対応できるようになるために役立つAIOCRです。
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/187821591-6cb09459-fdbf-4ad3-8c5a-26af611c211d.png" width="800">
+</div>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_4.png" width="800">
+</div>
+
+
+
+<div align="center">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+## 📣 最新アップデート
+- **🔥2022.8.24 リリース PaddleOCR [release/2.6 ](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+  -  [PP-Structurev2](../../ppstructure/)がリリース。機能と使いやすさがアップグレード、中国語のさまざまな文字に適応、 [レイアウトの復旧](../../ppstructure/recovery)  さらに**1 行のコマンドをPDFへ転換、そして Word**に変換可能。
+  - [レイアウト分析](../../ppstructure/layout) の最適化：モデルのストレージが 95% 削減、速度が 11 倍向上、平均 CPU 時間コストはわずか 41 ミリ秒です。
+  - [表認識](../../ppstructure/table) 最適化：3つの最適化戦略設計、モデルの精度が従来より同時間比が 6% 向上。
+  - [キー情報抽出](../../ppstructure/kie) 最適化:視覚に依存しないモデル構造設計、語彙の実態識別精度が 2.8% 向上、関係抽出の精度が 9.1% 向上。
+
+- **🔥2022.7 リリース [OCR scene application collection](../../applications/README_en.md)**
+   - デジタルチューブ、液晶画面、ナンバー プレート、手書き認識モデル、高精度 SVTR モデルなど、**9つの垂直モデル**をリリース、一般、製造、金融、運輸業界の主要な OCR 垂直アプリケーションをカバー。
+
+- **🔥2022.5.9 リリース PaddleOCR [release/2.5](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.5)**
+    -  [PP-OCRv3](../doc_en/ppocr_introduction_en.md#pp-ocrv3)リリース: 同等の速度で、中国語の識別効果は PP-OCRv2 より 5% 向上、英語の識別効果は 11% 向上し、80 言語の多言語モデルの平均認識精度は 5% 以上向上。
+    -  [PPOCRLabelv2](./PPOCRLabel)リリース: 表認識タスク、キー情報抽出タスク、イレギュラーテキスト画像のアノテーション機能を追加。
+    - インタラクティブな電子書籍 [*"OCR に没入"*](../doc_en/ocr_book_en.md)、 をリリース。 OCRフルスタック技術の最先端の理論とコードの実践をカバー。
+
+- [もっと](../doc_en/update_en.md)
+
+
+## 🌟 PaddleOCRとは？
+
+PaddleOCRは、OCRに関連するさまざまな最先端のアルゴリズムに対応する、産業用の機能モデル/ソリューション [PP-OCR](../doc_en/ppocr_introduction_en.md) や [PP-Structure](../../ppstructure/README.md) を開発。これに基づき、データの生成、モデルのトレーニング、圧縮、推論、展開の全プロセスを実行可能。
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/195771471-fad5eb1d-190d-4a7b-8b0c-0433fb32445f.png">
+</div>
+
+## ⚡ 今すぐトライアル
+
+```bash
+pip3 install paddlepaddle # for gpu user please install paddlepaddle-gpu
+pip3 install paddleocr
+paddleocr --image_dir /your/test/image.jpg --lang=japan # change for i18n abbr
+```
+
+>Python環境がない場合は [環境の準備](../doc_en/environment_en.md)に従ってください。[チュートリアル](#Tutorials) から始めることをお勧めします。
+
+<a name="本"></a>
+
+## 📚 電子書籍：*OCRに入る*
+- [OCRに没入](../doc_en/ocr_book_en.md)
+
+<a name="コミュニティ"></a>
+
+## 👫コミュニティー
+
+他国の開発者の方は [PaddleOCR Discussions](https://github.com/PaddlePaddle/PaddleOCR/discussions) を国際的なコミュニティ プラットフォームとして使用します。みなさんのアイデアや質問がある場合、ここで英語で話し合うことができます。
+
+<a name="対応中国機種一覧"></a>
+
+## 🛠️ シリーズ モデル式一覧
+
+| モデル紹介                                           | モデル名                   | 推奨のシーン | 検出モデル                                             | 認識モデル                                           |
+| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| 日本語超軽量 PP-OCRv3 モデル(14.8M) | japan_PP-OCRv3_xx | モバイル & サーバー |[推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar)/[トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) |[推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar)/[トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_train.tar) |
+| 英語超軽量PP-OCRv3モデル（13.4M） | en_PP-OCRv3_xx | モバイル & サーバー | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+| 中国語と英語の超軽量 PP-OCRv3 モデル（16.2M）    | ch_PP-OCRv3_xx          | モバイル & サーバー | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+
+
+- その他のモデルのダウンロード (多言語を含む) については、[PP-OCR シリーズ モデルのダウンロード] (../doc_en/models_list_en.md)をご参照ください。
+- 新しい言語のリクエストについては、 [新しい言語_リクエストのガイドライン](#language_requests)を参照してください。
+- 構造文書分析モデルについては、[PP-Structure models](../../ppstructure/docs/models_list_en.md)をご参照ください。
+
+<a name="チュートリアル"></a>
+
+## 📖 チュートリアル
+
+- [環境の準備](../doc_en/environment_en.md)
+- [PP-OCR 🔥](../doc_en/ppocr_introduction_en.md)
+    - [クイックスタート](../doc_en/quickstart_en.md)
+    - [Model Zoo](../doc_en/models_en.md)
+    - [トレーニング モデル](../doc_en/training_en.md)
+        - [テキスト検出](../doc_en/detection_en.md)
+        - [テキスト認識](../doc_en/recognition_en.md)
+        - [テキスト方向の分類](../doc_en/angle_class_en.md)
+    - モデル圧縮
+        - [モデルの量子化](./deploy/slim/quantization/README_en.md)
+        - [モデルの剪裁](./deploy/slim/prune/README_en.md)
+        - [知識の蒸留](../doc_en/knowledge_distillation_en.md)
+    - [推論と展開](./deploy/README.md)
+        - [Python 推論](../doc_en/inference_ppocr_en.md)
+        - [C++ 推論](./deploy/cpp_infer/readme.md)
+        - [サービング](./deploy/pdserving/README.md)
+        - [モバイル](./deploy/lite/readme.md)
+        - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
+        - [PaddleCloud](./deploy/paddlecloud/README.md)
+        - [Benchmark](../doc_en/benchmark_en.md)  
+- [PP-Structure 🔥](../../ppstructure/README.md)
+    - [クイックスタート](../../ppstructure/docs/quickstart_en.md)
+    - [Model Zoo](../../ppstructure/docs/models_list_en.md)
+    - [トレーニング モデル](../doc_en/training_en.md)  
+        - [レイアウト分析](../../ppstructure/layout/README.md)
+        - [表認識](../../ppstructure/table/README.md)
+        - [キー情報抽出](../../ppstructure/kie/README.md)
+    - [推論と展開](./deploy/README.md)
+        - [Python 推論](../../ppstructure/docs/inference_en.md)
+        - [C++ 推論](./deploy/cpp_infer/readme.md)
+        - [サービング](./deploy/hubserving/readme_en.md)
+- [アカデミックアリゴリズム](../doc_en/algorithm_overview_en.md)
+    - [テキスト検出](../doc_en/algorithm_overview_en.md)
+    - [テキスト認識](../doc_en/algorithm_overview_en.md)
+    - [エンド・ツー・エンド OCR](../doc_en/algorithm_overview_en.md)
+    - [表認識](../doc_en/algorithm_overview_en.md)
+    - [キー情報抽出](../doc_en/algorithm_overview_en.md)    
+    - [PaddleOCR に新しいアルゴリズムを追加する](../doc_en/add_new_algorithm_en.md)
+- データの注釈と合成
+    - [半自動注釈ツール: PPOCRLabel](./PPOCRLabel/README.md)
+    - [データ合成ツール: Style-Text](./StyleText/README.md)
+    - [その他のデータ注釈ツール](../doc_en/data_annotation_en.md)
+    - [その他のデータ合成ツール](../doc_en/data_synthesis_en.md)
+- データセット
+    - [一般OCRデータセット(中国語/英語)](../doc_en/dataset/datasets_en.md)
+    - [HandWritten_OCR_Datasets(中国語)](../doc_en/dataset/handwritten_datasets_en.md)
+    - [各種OCRデータセット(多言語対応)](../doc_en/dataset/vertical_and_multilingual_datasets_en.md)
+    - [レイアウト分析](../doc_en/dataset/layout_datasets_en.md)
+    - [表認識](../doc_en/dataset/table_datasets_en.md)
+    - [キー情報抽出](../doc_en/dataset/kie_datasets_en.md)
+- [コード構造](../doc_en/tree_en.md)
+- [視覚化](#Visualization)
+- [コミュニティ](#Community)
+- [新言語のリクエスト](#language_requests)
+- [よくある質問](../doc_en/FAQ_en.md)
+- [参考文献](../doc_en/reference_en.md)
+- [ライセンス](#LICENSE)
+
+<a name="language_requests"></a>
+
+## 🇺🇳 新しい言語リクエストのガイドライン
+
+**新言語モデルをリクエスト**したい場合、[多言語モデルのアップグレードへの投票](https://github.com/PaddlePaddle/PaddleOCR/discussions/7253)で投票してください。投票結果に応じて定期的にモデルがアップグレードされます。**友達を招待して一緒に投票しましょう!**
+
+シナリオに基づいて**新しい言語モデルをトレーニング** する必要がある場合は、[多言語モデル トレーニング プロジェクト](https://github.com/PaddlePaddle/PaddleOCR/discussions/7252) のチュートリアルがデータセットの準備にご利用でき、 プロセス全体を段階的に表示することができます。
+
+元の[多言語 OCR 開発計画](https://github.com/PaddlePaddle/PaddleOCR/issues/1048) には、まだ多くの有用なコーパスと辞書が表示されています
+
+<a name="ビジュアリゼーション"></a>
+
+## 👀 ビジュアリゼーション [more](../doc_en/visualization_en.md)
+
+<details open>
+<summary>PP-OCRv3 多言語モデル</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-OCRv3 英語 モデル</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="../imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+</details>
+<details open>
+<summary>PP-OCRv3 中国語 モデル</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+</details>
+
+<details open>
+<summary>PP-Structurev2</summary>
+1. レイアウト分析＋テーブル認識
+<div align="center">
+    <img src="../../ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+2. SER (セマンティックエンティティ認識)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094456-01a1dd11-1433-4437-9ab2-6480ac94ec0a.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>
+3. RE (関係抽出)
+<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="ライセンス"></a>
+
+## 📄 ライセンス
+このプロジェクトは以下の場所でリリースされています <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>

doc/doc_i18n/README_한국어.md

+English | [简体中文](README_ch.md)
+
+<p align="center">
+ <img src="../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>
+
+## 소개
+
+PaddleOCR은 사용자들이 보다 나은 모델을 훈련하여 실전에 투입하는데 도움을 주는 다중 언어로 된 엄청나게 멋지고 주도적이며 실용적인 OCR 툴을 만드는데 목표를 두고 있습니다. 
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/187821591-6cb09459-fdbf-4ad3-8c5a-26af611c211d.png" width="800">
+</div>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_4.png" width="800">
+</div>
+
+
+<div align="center">
+    <img src="../imgs_results/ch_ppocr_mobile_v2.0/00006737.jpg" width="800">
+</div>
+
+
+## 📣최근 업데이트
+- **🔥2022년 8월 24일에 패들 OCR 출시 [출시/2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)**
+  차이니즈 씬에 맞춘 완전 업그레이드 된 기능과 성능을 갖춘 ; [PP-Structurev2](../../ppstructure/) 출시, 그리고 레이아웃 리커버리 ](../../ppstructure/recovery) 신규 지원 및 PDF 를 워드로 전환하는 원 라인 명령
+  - [레이아웃 분석](../../ppstructure/layout)  최적화: 95% 감소된 모델 저장, while 반면 속도는 11배 증가하고, 평균 CPU 시간 비용은 41ms에 불과함;
+  - [표 인식](../../ppstructure/table) 최적화: 3 최적화 전략이 디자인되고 모델 정확도는 비교 가능한 시간 소비 하에 6% 개선됨;
+  - [핵심 정보 추출](../../ppstructure/kie)  최적화： 시각에 의존하지 않는 모델 구조가 디자인되고, 의미체 인식 정확도가 2.8% 증가되며 관계 추출 정확도는 9.1% 증가됨.
+  
+- **🔥2022년 7월 출시[OCR 씬 애플리케이션 컬렉션](../../applications/README_en.md)**
+    디지털 튜브, LCD 스크린, 라이선스 플레이트, 수기 인식 모델, 고정밀 SVTR 모델 등등과 같은 “9수직 모델” 출시로, 일반적으로 주된 OCR 수직 애플리케이션, 제조, 금융 및 수송 산업 커버
+
+- **🔥2022년 5월 9일에 패들 OCR 출시 [출시/2.5](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.5)**
+    - [PP-OCRv3](../doc_en/ppocr_introduction_en.md#pp-ocrv3)출시: 5%.비교 가능한 속도로, 차이니즈 씬의 효과는 PP-OCRv2와 비교해 볼 때 추가로 5% 정도 더 개선되고, 잉글리쉬 씬 효과는 11% 개선되었으며, 80개 언어 다중 언어 모델 평균 인식 정확도는 5% 이상 개선됨. 
+    - [PPOCRLabelv2](./PPOCRLabel)출시: 표 인식 업무, 핵심 정보 추출 업무 및 불규칙한 텍스트 이미지주석 기능 추가.
+    -  쌍방향e-북 출시 [*"OCR 뛰어들기"*](../doc_en/ocr_book_en.md), 첨단 이론 및 OCR 정식 스택 기술 코드 연습 포함.
+
+- [추가](../doc_en/update_en.md)
+
+
+## 🌟특징
+패들OCR은 OCR 관련 다양한 첨단 알고리즘 지원  [PP-OCR](../doc_en/ppocr_introduction_en.md) 및 [PP-Structure](../../ppstructure/README.md)  이를 기반으로, 그리고 전체 데이터 생산 처리, 모델 훈련, 압축, 추론 및 배치를 통해 획득.
+
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/50011306/196963392-6cd1b251-109b-49c3-9b3d-ccf203dcec49.png">
+</div>
+
+
+## ⚡ 신속한 경험
+
+```bash
+pip3 install paddlepaddle # for gpu user please install paddlepaddle-gpu
+pip3 install paddleocr
+paddleocr --image_dir /your/test/image.jpg --lang=korean
+```
+
+>만일 당신이 파이톤 환경이 없다면 [환경 준비]를 따르기 바람(../doc_en/environment_en.md). 우리는 당신이[사용지침 프로그램]으로 시작할 것을 권장합니다.(#Tutorials).
+
+<a name="북"></a>
+
+## 📚 E-북: *OCR로 뛰어들기*
+- [OCR로 뛰어들기](../doc_en/ocr_book_en.md)
+
+<a name="커뮤니티"></a>
+
+## 👫 커뮤니티로
+
+국제 개발자들을 위해 우리는 [PaddleOCR 논의하기](https://github.com/PaddlePaddle/PaddleOCR/discussions) 를 우리의 국제 커뮤니티로 간주. 모든 아이디어와 질문은 여기서 영어로 논의 가능.
+
+<a name="지원됨 – 차이니즈-모델-목록- "></a>
+
+## PP-OCR 시리즈 모델 목록
+
+| 모델 소개                                          |모델 명                   | 권장 씬| 감지 모델                                              |인식 모델                                            |
+| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| 한국어 초경량 PP-OCRv3 모델(14.8M) | korean_PP-OCRv3_xx | 모바일 & 서버 | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_train.tar) |
+| 영어 초경량 PP-OCRv3 모델（13.4M） | en_PP-OCRv3_xx | 모바일 & 서버 | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
+| 중국어 및 영어 초경량 PP-OCRv3 model（16.2M）     | ch_PP-OCRv3_xx          | 모바일 & 서버 | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar) | [추론 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [훈련 모델](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
+
+
+- (다중 언어를 포함하여)더 많은 모델을 다운로드 하려면, [PP-OCR 시리즈 모델 다운로드](../doc_en/models_list_en.md)를 참조할 것.
+- 신규 언어 요청에 대해서는, [신규 언어 요청 지침](#language_requests)을 참조할 것.
+- 구조적 문서 분석 모델에 대해서는, [PP-Structure models](../../ppstructure/docs/models_list_en.md).을 참조할 것.
+
+<a name="사용 지침 프로그램"></a>
+
+## 📖 사용 지침 프로그램
+
+- [환경 준비](../doc_en/environment_en.md)
+- [PP-OCR 🔥](../doc_en/ppocr_introduction_en.md)
+    - [신속한 시작](../doc_en/quickstart_en.md)
+    - [동물원 모델](../doc_en/models_en.md)
+    - [모델 훈련](../doc_en/training_en.md)
+        - [텍스트 감지](../doc_en/detection_en.md)
+        - [텍스트 인식](../doc_en/recognition_en.md)
+        - [텍스트 방향 분류](../doc_en/angle_class_en.md)
+    - 모델 압축
+        - [모델 계량화](./deploy/slim/quantization/README_en.md)
+        - [모델 전지작업](./deploy/slim/prune/README_en.md)
+        - [지식 정제](../doc_en/knowledge_distillation_en.md)
+    - [추론 및 배치](./deploy/README.md)
+        - [파이톤 추론](../doc_en/inference_ppocr_en.md)
+        - [C++ 추론](./deploy/cpp_infer/readme.md)
+        - [서빙](./deploy/pdserving/README.md)
+        - [모바일](./deploy/lite/readme.md)
+        - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
+        - [패들 클라우드](./deploy/paddlecloud/README.md)
+        - [Benchmark](../doc_en/benchmark_en.md)  
+- [PP-Structure 🔥](../../ppstructure/README.md)
+    - [신속한 시작](../../ppstructure/docs/quickstart_en.md)
+    - [동물원 모델](../../ppstructure/docs/models_list_en.md)
+    - [모델 훈련](../doc_en/training_en.md)  
+        - [레이아웃 분석](../../ppstructure/layout/README.md)
+        - [표 인식](../../ppstructure/table/README.md)
+        - [핵심 정보 추출](../../ppstructure/kie/README.md)
+    - [추론 및 배치](./deploy/README.md)
+        - [파이톤 추론](../../ppstructure/docs/inference_en.md)
+        - [C++ 추론](./deploy/cpp_infer/readme.md)
+        - [서빙](./deploy/hubserving/readme_en.md)
+- [학문적 알고리즘](../doc_en/algorithm_overview_en.md)
+    - [텍스트 감지](../doc_en/algorithm_overview_en.md)
+    - [텍스트 인식](../doc_en/algorithm_overview_en.md)
+    - [종단종OCR](../doc_en/algorithm_overview_en.md)
+    - [표 인식](../doc_en/algorithm_overview_en.md)
+    - [핵심 정보 추출](../doc_en/algorithm_overview_en.md)    
+    - [PaddleOCR에 신규 알고리즘 추가](../doc_en/add_new_algorithm_en.md)
+-  데이터 주석 및 합성 
+    - [반-자동 주석 툴: PPOCRLabel](./PPOCRLabel/README.md)
+    - [데이터 합성 툴: 스타일-텍스트](./StyleText/README.md)
+    - [기타 데이터 주석 툴](../doc_en/data_annotation_en.md)
+    - [기타 데이터 합성 툴](../doc_en/data_synthesis_en.md)
+-  데이터세트
+    - [일반 OCR 데이터세트(중국어/영어)](../doc_en/dataset/datasets_en.md)
+    - [수기_OCR_데이터세트(중국어)](../doc_en/dataset/handwritten_datasets_en.md)
+    - [다양한 OCR 데이터세트(다중언어)](../doc_en/dataset/vertical_and_multilingual_datasets_en.md)
+    - [레이아웃 분석](../doc_en/dataset/layout_datasets_en.md)
+    - [표 인식](../doc_en/dataset/table_datasets_en.md)
+    - [핵심 정보 추출](../doc_en/dataset/kie_datasets_en.md)
+- [코드 구조](../doc_en/tree_en.md)
+- [시각화](#Visualization)
+- [커뮤니티](#Community)
+- [신규 언어 요청](#language_requests)
+- [자주 묻는 질문](../doc_en/FAQ_en.md)
+- [추론](../doc_en/reference_en.md)
+- [라이선스](#LICENSE)
+
+<a name="language_requests"></a>
+
+## 신규 언어 요청에 대한 유엔 가이드라인 
+
+만일 신규 언어 모델을 요청하고자 한다면**, [다중 언어 모델 업그레이드 투표하기](https://github.com/PaddlePaddle/PaddleOCR/discussions/7253)에서 투표하기 바람. 우리는 결과에 따라 규칙적으로 모델을 업그레이드 시킬 것임**함께 투표하고자 당신의 친구들을 초대할 것!**
+만일 당신이 시나리오 기반 “신규 언어 모델”을 훈련하고자 한다면, [다중 언어 모델 훈련 프로젝트](https://github.com/PaddlePaddle/PaddleOCR/discussions/7252) 를 통해 당신의 데이터세트를 작성하는데 도움이 되고 단계별로 전체 절차를 보여줄 것입니다. 
+원본[다중 언어 OCR 개발 계획](https://github.com/PaddlePaddle/PaddleOCR/issues/1048)은 여전히 수많은 유용한 말뭉치와 사전을 보여줍니다.
+
+<a name="시각화"></a>
+
+## 👀 시각화[추가](../doc_en/visualization_en.md)
+
+<details open>
+<summary>PP-OCRv3 다중 언어 모델</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/japan_2.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/multi_lang/korean_1.jpg" width="800">
+</div>
+</details>
+
+
+<details open>
+<summary>PP-OCRv3 영어 모델</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/en/en_1.png" width="800">
+    <img src="../imgs_results/PP-OCRv3/en/en_2.png" width="800">
+</div>
+</details>
+<details open>
+<summary>PP-OCRv3 중국어 모델</summary>
+<div align="center">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic001.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic002.jpg" width="800">
+    <img src="../imgs_results/PP-OCRv3/ch/PP-OCRv3-pic003.jpg" width="800">
+</div>
+</details>
+
+
+<details open>
+<summary>PP-Structurev2</summary>
+1.  레이아웃 분석 + 표 인식
+<div align="center">
+    <img src="./ppstructure/docs/table/ppstructure.GIF" width="800">
+</div>
+2. SER (의미체 인식)
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/25809855/186094456-01a1dd11-1433-4437-9ab2-6480ac94ec0a.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>
+3. RE (관계 추출)
+<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="라이선스"></a>
+
+## 📄 라이선스
+본 프로젝트는 <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a> 하에 출시됨.

paddleocr.py

@@ -47,7 +47,7 @@ __all__ = [
 ]
 
 SUPPORT_DET_MODEL = ['DB']
-VERSION = '2.6.0.1'
+VERSION = '2.6.0.3'
 SUPPORT_REC_MODEL = ['CRNN', 'SVTR_LCNet']
 BASE_DIR = os.path.expanduser("~/.paddleocr/")
 

ppocr/data/imaug/label_ops.py

@@ -1344,8 +1344,6 @@ class VLLabelEncode(BaseRecLabelEncode):
                  **kwargs):
         super(VLLabelEncode, self).__init__(
             max_text_length, character_dict_path, use_space_char, lower)
-        self.character = self.character[10:] + self.character[
-            1:10] + [self.character[0]]
         self.dict = {}
         for i, char in enumerate(self.character):
             self.dict[char] = i

ppocr/data/imaug/random_crop_data.py

@@ -52,6 +52,7 @@ def split_regions(axis):
             region = axis[min_axis:i]
             min_axis = i
             regions.append(region)
+    regions.append(axis[min_axis:])  # 添加的一行
     return regions
 
 

ppocr/postprocess/rec_postprocess.py

@@ -26,6 +26,7 @@ class BaseRecLabelDecode(object):
         self.end_str = "eos"
         self.reverse = False
         self.character_str = []
+
         if character_dict_path is None:
             self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
             dict_character = list(self.character_str)
@@ -720,8 +721,6 @@ class VLLabelDecode(BaseRecLabelDecode):
         super(VLLabelDecode, self).__init__(character_dict_path, use_space_char)
         self.max_text_length = kwargs.get('max_text_length', 25)
         self.nclass = len(self.character) + 1
-        self.character = self.character[10:] + self.character[
-            1:10] + [self.character[0]]
 
     def decode(self, text_index, text_prob=None, is_remove_duplicate=False):
         """ convert text-index into text-label. """

ppstructure/docs/quickstart.md

@@ -49,12 +49,6 @@ pip3 install "paddleocr>=2.6"
 
 # 安装 图像方向分类依赖包paddleclas（如不需要图像方向分类功能，可跳过）
 pip3 install paddleclas>=2.4.3
-
-# 安装 关键信息抽取 依赖包（如不需要KIE功能，可跳过）
-pip3 install -r ppstructure/kie/requirements.txt
-
-# 安装 版面恢复 依赖包（如不需要版面恢复功能，可跳过）
-pip3 install -r ppstructure/recovery/requirements.txt
 ```
 
 <a name="2"></a>

ppstructure/docs/quickstart_en.md

@@ -51,12 +51,6 @@ pip3 install "paddleocr>=2.6"
 
 # Install the image direction classification dependency package paddleclas (if you do not use the image direction classification, you can skip it)
 pip3 install paddleclas>=2.4.3
-
-# Install the KIE dependency packages (if you do not use the KIE, you can skip it)
-pip3 install -r kie/requirements.txt
-
-# Install the layout recovery dependency packages (if you do not use the layout recovery, you can skip it)
-pip3 install -r recovery/requirements.txt
 ```
 
 <a name="2"></a>

ppstructure/pdf2word/README.md

 # PDF2Word
 
-PDF2Word是PaddleOCR社区开发者[whjdark](https://github.com/whjdark) 基于PP-Structure智能文档分析模型实现的PDF转换Word应用程序，提供可直接安装的exe，方便windows用户运行
+PDF2Word是PaddleOCR社区开发者 [whjdark](https://github.com/whjdark) 基于PP-StructureV2版面分析与恢复模型实现的PDF转换Word应用程序，提供可直接安装的exe应用程序，**方便Windows用户离线、免环境配置运行**
 
 ## 1.使用
 
 ### 应用程序
 
-1. 下载与安装：针对Windows用户，根据[软件下载]()一节下载软件后，运行 `启动程序.exe` 。若您下载的是lite版本，安装过程中会在线下载环境依赖、模型等必要资源，安装时间较长，请确保网络畅通。serve版本打包了相关依赖，安装时间较短，可按需下载。
+1. 下载与安装：针对Windows用户，根据[软件下载](#download)一节下载软件并解压后，运行 `启动程序.exe` 。
 
-2. 转换：由于PP-Structure根据中英文数据分别进行适配，在转换相应文件时可**根据文档语言进行相应选择**。
+2. **打开文件与转换：**
 
-### 脚本运行
+   - `中文转换、英文转换` ：针对 `图片型PDF` 文件的转换方法，即**当PDF文件中的文字无法复制粘贴时**，推荐使用本方法通过OCR转换文件，由于PP-Structure根据中英文数据分别进行适配，在转换相应文件时可**根据文档语言进行相应选择**。
+   - `PDF解析` ： 针对可以复制文字的PDF文件，推荐直接点击 `PDF解析`，获得更加精准的效果。
+
+3. 打开结果：点击`显示结果`，即可打开转换完成后的文件夹
+
+> 注意：
+>
+> - 初次安装程序根据不同设备需要等待1-2分钟不等
+> - 使用Office与WPS打开的Word结果会出现不同，推荐以Office为准
+> - 本程序使用 [QPT](https://github.com/QPT-Family/QPT) 进行应用程序打包，感谢 [GT-ZhangAcer](https://github.com/GT-ZhangAcer) 对打包过程的支持
+
+### 脚本启动界面
 
 首次运行需要将切换路径到 `/ppstructure/pdf2word` ，然后运行代码
 
@@ -18,11 +29,25 @@ PDF2Word是PaddleOCR社区开发者[whjdark](https://github.com/whjdark) 基于P
 python pdf2word.py
 ```
 
+### PaddleOCR whl包
+
+针对Linux、Mac用户或已经拥有Python环境的用户，**推荐安装 `paddleocr` whl包直接应用版面恢复功能**，详情可查看[链接](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/ppstructure/docs/quickstart.md)
+
+<a name="download"></a>
+
 ## 2.软件下载
 
-如需获取已打包程序，可以扫描下方二维码，关注公众号填写问卷后，加入PaddleOCR官方交流群免费获取20G OCR学习大礼包，内含OCR场景应用集合（包含数码管、液晶屏、车牌、高精度SVTR模型等7个垂类模型）、《动手学OCR》电子书、课程回放视频、前沿论文等重磅资料
+如需获取已打包程序，可以扫描下方二维码，关注公众号填写问卷后，加入PaddleOCR官方交流群免费获取20G OCR学习大礼包，内含OCR场景应用集合（包含数码管、液晶屏、车牌、高精度SVTR模型等10个垂类模型）、《动手学OCR》电子书、课程回放视频、前沿论文等重磅资料
 
 <div align="center">
 <img src="https://user-images.githubusercontent.com/50011306/186369636-35f2008b-df5a-4784-b1f5-cebebcb2b7a5.jpg"  width = "150" height = "150" />
 </div>
+## 3.版本说明
+
+v0.2版：新加入PDF解析功能，仅提供full版本，打包了所有依赖包与模型文件，尽可能避免安装失败问题
+
+v0.1版：最初版本，分为3个版本：
 
+- mini版：体积较小，在安装过程中会自动下载依赖包、模型等必要资源，安装时间较长，需要确保网络畅通。
+- env版：仅打包了项目依赖，避免出现运行过程中找不到cv等资源的情况。
+- full版：打包了依赖包与模型文件，故压缩包较大，相对等待时间较短，可按需下载。

ppstructure/pdf2word/pdf2word.py

@@ -7,8 +7,11 @@ import functools
 import cv2
 import platform
 import numpy as np
+import fitz
+from PIL import Image
+from pdf2docx.converter import Converter
 from qtpy.QtWidgets import QApplication, QWidget, QPushButton, QProgressBar, \
-                           QGridLayout, QMessageBox, QLabel, QFileDialog
+                           QGridLayout, QMessageBox, QLabel, QFileDialog, QCheckBox
 from qtpy.QtCore import Signal, QThread, QObject
 from qtpy.QtGui import QImage, QPixmap, QIcon
 
@@ -17,6 +20,7 @@ root = os.path.abspath(os.path.join(file, '../../'))
 sys.path.append(file)
 sys.path.insert(0, root)
 
+
 from ppstructure.predict_system import StructureSystem, save_structure_res
 from ppstructure.utility import parse_args, draw_structure_result
 from ppocr.utils.network import download_with_progressbar
@@ -24,7 +28,7 @@ from ppstructure.recovery.recovery_to_doc import sorted_layout_boxes, convert_in
 # from ScreenShotWidget import ScreenShotWidget
 
 __APPNAME__ = "pdf2word"
-__VERSION__ = "0.1.1"
+__VERSION__ = "0.2.2"
 
 URLs_EN = {
     # 下载超英文轻量级PP-OCRv3模型的检测模型并解压
@@ -75,9 +79,7 @@ def QImageToCvMat(incomingImage) -> np.array:
 
 
 def readImage(image_file) -> list:
-    if os.path.basename(image_file)[-3:] in ['pdf']:
-        import fitz
-        from PIL import Image
+    if os.path.basename(image_file)[-3:] == 'pdf':
         imgs = []
         with fitz.open(image_file) as pdf:
             for pg in range(0, pdf.pageCount):
@@ -102,17 +104,22 @@ def readImage(image_file) -> list:
 
 class Worker(QThread):
     progressBarValue = Signal(int)
+    progressBarRange = Signal(int)
     endsignal = Signal()
+    exceptedsignal = Signal(str) #发送一个异常信号
     loopFlag = True
 
-    def __init__(self, predictors, save_pdf, vis_font_path):
+    def __init__(self, predictors, save_pdf, vis_font_path, use_pdf2docx_api):
         super(Worker, self).__init__()
         self.predictors = predictors
         self.save_pdf = save_pdf
         self.vis_font_path = vis_font_path
         self.lang = 'EN'
         self.imagePaths = []
+        self.use_pdf2docx_api = use_pdf2docx_api
         self.outputDir = None
+        self.totalPageCnt = 0
+        self.pageCnt = 0
         self.setStackSize(1024*1024)
 
     def setImagePath(self, imagePaths):
@@ -124,60 +131,90 @@ class Worker(QThread):
     def setOutputDir(self, outputDir):
         self.outputDir = outputDir
     
-    def predictAndSave(self, imgs, img_name):
+    def setPDFParser(self, enabled):
+        self.use_pdf2docx_api = enabled
+
+    def resetPageCnt(self):
+        self.pageCnt = 0
+
+    def resetTotalPageCnt(self):
+        self.totalPageCnt = 0
+
+    def ppocrPrecitor(self, imgs, img_name):
         all_res = []
+        # update progress bar ranges
+        self.totalPageCnt += len(imgs)
+        self.progressBarRange.emit(self.totalPageCnt)
+        # processing pages
         for index, img in enumerate(imgs):
             res, time_dict = self.predictors[self.lang](img)
 
             # save output
             save_structure_res(res, self.outputDir, img_name)
-            draw_img = draw_structure_result(img, res, self.vis_font_path)
-            img_save_path = os.path.join(self.outputDir, img_name, 'show_{}.jpg'.format(index))
-            if res != []:
-                cv2.imwrite(img_save_path, draw_img)
+            # draw_img = draw_structure_result(img, res, self.vis_font_path)
+            # img_save_path = os.path.join(self.outputDir, img_name, 'show_{}.jpg'.format(index))
+            # if res != []:
+            #     cv2.imwrite(img_save_path, draw_img)
 
             # recovery
             h, w, _ = img.shape
             res = sorted_layout_boxes(res, w)
             all_res += res
+            self.pageCnt += 1
+            self.progressBarValue.emit(self.pageCnt)
 
+        if all_res != []:
             try:
-            convert_info_docx(img, all_res, self.outputDir, img_name, self.save_pdf)
+                convert_info_docx(imgs, all_res, self.outputDir, img_name)
             except Exception as ex:
-            print(self,
-                "error in layout recovery image:{}, err msg: {}".format(
-                img_name, ex))
-
+                print("error in layout recovery image:{}, err msg: {}".
+                    format(img_name, ex))
+        print("Predict time : {:.3f}s".format(time_dict['all']))
         print('result save to {}'.format(self.outputDir)) 
 
     def run(self):
+        self.resetPageCnt()
+        self.resetTotalPageCnt()
         try:
-            findex = 0
             os.makedirs(self.outputDir, exist_ok=True)
             for i, image_file in enumerate(self.imagePaths):
-                if self.loopFlag == True:
+                if not self.loopFlag:
+                    break
+                # using use_pdf2docx_api for PDF parsing
+                if self.use_pdf2docx_api \
+                    and os.path.basename(image_file)[-3:] == 'pdf':
+                    self.totalPageCnt += 1
+                    self.progressBarRange.emit(self.totalPageCnt)
+                    print('===============using use_pdf2docx_api===============')
+                    img_name = os.path.basename(image_file).split('.')[0]
+                    docx_file = os.path.join(
+                        self.outputDir, '{}.docx'.format(img_name))
+                    cv = Converter(image_file)
+                    cv.convert(docx_file)
+                    cv.close()
+                    print('docx save to {}'.format(docx_file))
+                    self.pageCnt += 1
+                    self.progressBarValue.emit(self.pageCnt)
+                else:
+                    # using PPOCR for PDF/Image parsing
                     imgs = readImage(image_file)
                     if len(imgs) == 0:
                         continue
                     img_name = os.path.basename(image_file).split('.')[0]
                     os.makedirs(os.path.join(self.outputDir, img_name), exist_ok=True)
-                    self.predictAndSave(imgs, img_name)
-                    findex += 1
-                    self.progressBarValue.emit(findex)
-                else:
-                    break
+                    self.ppocrPrecitor(imgs, img_name)
+                # file processed
             self.endsignal.emit()
-            self.exec()
+            # self.exec()
         except Exception as e:
-            print(e)
-            raise
+            self.exceptedsignal.emit(str(e)) # 将异常发送给UI进程
 
 
 class APP_Image2Doc(QWidget):
     def __init__(self):
         super().__init__()
-        self.setFixedHeight(90)
-        self.setFixedWidth(400)
+        self.setFixedHeight(100)
+        self.setFixedWidth(420)
 
         # settings
         self.imagePaths = []
@@ -187,6 +224,7 @@ class APP_Image2Doc(QWidget):
         self.output_dir = None
         self.vis_font_path = os.path.join(root,
                 "doc", "fonts", "simfang.ttf")
+        self.use_pdf2docx_api = False
 
         # ProgressBar
         self.pb = QProgressBar()
@@ -207,10 +245,12 @@ class APP_Image2Doc(QWidget):
         }
 
         # 设置工作进程
-        self._thread = Worker(predictors, self.save_pdf, self.vis_font_path)
-        self._thread.progressBarValue.connect(self.handleProgressBarSingal)
+        self._thread = Worker(predictors, self.save_pdf, self.vis_font_path, self.use_pdf2docx_api)
+        self._thread.progressBarValue.connect(self.handleProgressBarUpdateSingal)
         self._thread.endsignal.connect(self.handleEndsignalSignal)
-        self._thread.finished.connect(QObject.deleteLater)
+        # self._thread.finished.connect(QObject.deleteLater)
+        self._thread.progressBarRange.connect(self.handleProgressBarRangeSingal)
+        self._thread.exceptedsignal.connect(self.handleThreadException)
         self.time_start = 0  # save start time
 
     def setupUi(self):
@@ -233,25 +273,30 @@ class APP_Image2Doc(QWidget):
         self.startCNButton.setIcon(QIcon(QPixmap("./icons/chinese.png")))
         layout.addWidget(self.startCNButton, 0, 1, 1, 1)
         self.startCNButton.clicked.connect(
-            functools.partial(self.handleStartSignal, 'CN'))
+            functools.partial(self.handleStartSignal, 'CN', False))
 
         self.startENButton = QPushButton("英文转换")
         self.startENButton.setIcon(QIcon(QPixmap("./icons/english.png")))
         layout.addWidget(self.startENButton, 0, 2, 1, 1)
         self.startENButton.clicked.connect(
-            functools.partial(self.handleStartSignal, 'EN'))
+            functools.partial(self.handleStartSignal, 'EN', False))
+
+        self.PDFParserButton = QPushButton('PDF解析', self)
+        layout.addWidget(self.PDFParserButton, 0, 3, 1, 1)
+        self.PDFParserButton.clicked.connect(
+            functools.partial(self.handleStartSignal, 'CN', True))
         
         self.showResultButton = QPushButton("显示结果")
         self.showResultButton.setIcon(QIcon(QPixmap("./icons/folder-open.png")))
-        layout.addWidget(self.showResultButton, 0, 3, 1, 1)
+        layout.addWidget(self.showResultButton, 0, 4, 1, 1)
         self.showResultButton.clicked.connect(self.handleShowResultSignal)
 
         # ProgressBar
-        layout.addWidget(self.pb, 2, 0, 1, 4)
+        layout.addWidget(self.pb, 2, 0, 1, 5)
         # time estimate label
         self.timeEstLabel = QLabel(
             ("Time Left: --"))
-        layout.addWidget(self.timeEstLabel, 3, 0, 1, 4)
+        layout.addWidget(self.timeEstLabel, 3, 0, 1, 5)
 
         self.setLayout(layout)
 
@@ -355,7 +400,6 @@ class APP_Image2Doc(QWidget):
         if len(selectedFiles) > 0:
             self.imagePaths = selectedFiles
             self.screenShot = None # discard screenshot temp image
-            self.pb.setRange(0, len(self.imagePaths))
             self.pb.setValue(0)
 
     # def screenShotSlot(self):
@@ -370,7 +414,7 @@ class APP_Image2Doc(QWidget):
     #         self.pb.setRange(0, 1)
     #         self.pb.setValue(0)
 
-    def handleStartSignal(self, lang):
+    def handleStartSignal(self, lang='EN', pdfParser=False):
         if self.screenShot: # for screenShot
             img_name = 'screenshot_' + time.strftime("%Y%m%d%H%M%S", time.localtime())
             image = QImageToCvMat(self.screenShot)
@@ -386,10 +430,12 @@ class APP_Image2Doc(QWidget):
             self._thread.setOutputDir(self.output_dir)
             self._thread.setImagePath(self.imagePaths)
             self._thread.setLang(lang)
+            self._thread.setPDFParser(pdfParser)
             # disenble buttons
             self.openFileButton.setEnabled(False)
             self.startCNButton.setEnabled(False)
             self.startENButton.setEnabled(False)
+            self.PDFParserButton.setEnabled(False)
             # 启动工作进程
             self._thread.start()
             self.time_start = time.time() # log start time
@@ -411,7 +457,7 @@ class APP_Image2Doc(QWidget):
             QMessageBox.information(self, 
                 u'Information', "输出文件不存在")
 
-    def handleProgressBarSingal(self, i):
+    def handleProgressBarUpdateSingal(self, i):
         self.pb.setValue(i)
         # calculate time left of recognition
         lenbar = self.pb.maximum()
@@ -419,13 +465,24 @@ class APP_Image2Doc(QWidget):
         time_left = str(datetime.timedelta(seconds=avg_time * (lenbar - i))).split(".")[0]  # Remove microseconds
         self.timeEstLabel.setText(f"Time Left: {time_left}")  # show time left
 
+    def handleProgressBarRangeSingal(self, max):
+        self.pb.setRange(0, max)
+
     def handleEndsignalSignal(self):
         # enble buttons
         self.openFileButton.setEnabled(True)
         self.startCNButton.setEnabled(True)
         self.startENButton.setEnabled(True)
+        self.PDFParserButton.setEnabled(True)
         QMessageBox.information(self, u'Information', "转换结束")
 
+    def handleCBChangeSignal(self):
+        self._thread.setPDFParser(self.checkBox.isChecked())
+
+    def handleThreadException(self, message):
+        self._thread.quit()
+        QMessageBox.information(self, message)
+
 
 def main():
     app = QApplication(sys.argv)

setup.py

@@ -16,9 +16,17 @@ from setuptools import setup
 from io import open
 from paddleocr import VERSION
 
-with open('requirements.txt', encoding="utf-8-sig") as f:
-    requirements = f.readlines()
-    requirements.append('tqdm')
+
+def load_requirements(file_list=None):
+    if file_list is None:
+        file_list = ['requirements.txt']
+    if isinstance(file_list, str):
+        file_list = [file_list]
+    requirements = []
+    for file in file_list:
+        with open(file, encoding="utf-8-sig") as f:
+            requirements.extend(f.readlines())
+    return requirements
 
 
 def readme():
@@ -34,7 +42,8 @@ setup(
     include_package_data=True,
     entry_points={"console_scripts": ["paddleocr= paddleocr.paddleocr:main"]},
     version=VERSION,
-    install_requires=requirements,
+    install_requires=load_requirements(
+        ['requirements.txt', 'ppstructure/recovery/requirements.txt']),
     license='Apache License 2.0',
     description='Awesome OCR toolkits based on PaddlePaddle （8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embeded and IoT devices',
     long_description=readme(),