From d7d04f41446a9443068e70a9eede125459fd07f1 Mon Sep 17 00:00:00 2001
From: WenmuZhou <572459439@qq.com>
Date: Wed, 30 Mar 2022 14:46:35 +0000
Subject: [PATCH] add update log

---
 deploy/hubserving/readme.md    | 46 ++++++++++++++++++---------------
 deploy/hubserving/readme_en.md | 47 +++++++++++++++++++---------------
 2 files changed, 51 insertions(+), 42 deletions(-)

diff --git a/deploy/hubserving/readme.md b/deploy/hubserving/readme.md
index f8f7cf03..3280df5d 100755
--- a/deploy/hubserving/readme.md
+++ b/deploy/hubserving/readme.md
@@ -1,16 +1,17 @@
 [English](readme_en.md) | 简体中文
 
 - [基于PaddleHub Serving的服务部署](#基于paddlehub-serving的服务部署)
-  - [快速启动服务](#快速启动服务)
-    - [1. 准备环境](#1-准备环境)
-    - [2. 下载推理模型](#2-下载推理模型)
-    - [3. 安装服务模块](#3-安装服务模块)
-    - [4. 启动服务](#4-启动服务)
-      - [方式1. 命令行命令启动（仅支持CPU）](#方式1-命令行命令启动仅支持cpu)
-      - [方式2. 配置文件启动（支持CPU、GPU）](#方式2-配置文件启动支持cpugpu)
-  - [发送预测请求](#发送预测请求)
-  - [返回结果格式说明](#返回结果格式说明)
-  - [自定义修改服务模块](#自定义修改服务模块)
+  - [1. 近期更新](#1-近期更新)
+  - [2. 快速启动服务](#2-快速启动服务)
+    - [2.1 准备环境](#21-准备环境)
+    - [2.2 下载推理模型](#22-下载推理模型)
+    - [2.3 安装服务模块](#23-安装服务模块)
+    - [2.4 启动服务](#24-启动服务)
+      - [2.4.1. 命令行命令启动（仅支持CPU）](#241-命令行命令启动仅支持cpu)
+      - [2.4.2 配置文件启动（支持CPU、GPU）](#242-配置文件启动支持cpugpu)
+  - [3. 发送预测请求](#3-发送预测请求)
+  - [4. 返回结果格式说明](#4-返回结果格式说明)
+  - [5. 自定义修改服务模块](#5-自定义修改服务模块)
 
 
 PaddleOCR提供2种服务部署方式：
@@ -19,7 +20,7 @@ PaddleOCR提供2种服务部署方式：
 
 # 基于PaddleHub Serving的服务部署
 
-hubserving服务部署目录下包括检测、识别、2阶段串联和表格识别四种服务包，请根据需求选择相应的服务包进行安装和启动。目录结构如下：
+hubserving服务部署目录下包括检测、识别、2阶段串联，表格识别和PP-Structure四种服务包，请根据需求选择相应的服务包进行安装和启动。目录结构如下：
 ```
 deploy/hubserving/
   └─  ocr_cls     分类模块服务包
@@ -38,17 +39,20 @@ deploy/hubserving/ocr_system/
   └─  module.py      主模块，必选，包含服务的完整逻辑
   └─  params.py      参数文件，必选，包含模型路径、前后处理参数等参数
 ```
+## 1. 近期更新
 
-## 快速启动服务
+* 2022.03.30 新增PP-Structure和表格识别两种服务。
+
+## 2. 快速启动服务
 以下步骤以检测+识别2阶段串联服务为例，如果只需要检测服务或识别服务，替换相应文件路径即可。
-### 1. 准备环境
+### 2.1 准备环境
 ```shell
 # 安装paddlehub  
 # paddlehub 需要 python>3.6.2
 pip3 install paddlehub==2.1.0 --upgrade -i https://mirror.baidu.com/pypi/simple
 ```
 
-### 2. 下载推理模型
+### 2.2 下载推理模型
 安装服务模块前，需要准备推理模型并放到正确路径。默认使用的是PP-OCRv2模型，默认模型路径为：
 ```
 检测模型：./inference/ch_PP-OCRv2_det_infer/
@@ -59,7 +63,7 @@ pip3 install paddlehub==2.1.0 --upgrade -i https://mirror.baidu.com/pypi/simple
 
 **模型路径可在`params.py`中查看和修改。** 更多模型可以从PaddleOCR提供的模型库[PP-OCR](../../doc/doc_ch/models_list.md)和[PP-Structure](../../ppstructure/docs/models_list.md)下载，也可以替换成自己训练转换好的模型。
 
-### 3. 安装服务模块
+### 2.3 安装服务模块
 PaddleOCR提供5种服务模块，根据需要安装所需模块。
 
 * 在Linux环境下，安装示例如下：
@@ -104,8 +108,8 @@ hub install deploy\hubserving\structure_table\
 hub install deploy\hubserving\structure_system\
 ```
 
-### 4. 启动服务
-#### 方式1. 命令行命令启动（仅支持CPU）
+### 2.4 启动服务
+#### 2.4.1. 命令行命令启动（仅支持CPU）
 **启动命令：**  
 ```shell
 $ hub serving start --modules [Module1==Version1, Module2==Version2, ...] \
@@ -127,7 +131,7 @@ $ hub serving start --modules [Module1==Version1, Module2==Version2, ...] \
 
 这样就完成了一个服务化API的部署，使用默认端口号8866。
 
-#### 方式2. 配置文件启动（支持CPU、GPU）
+#### 2.4.2 配置文件启动（支持CPU、GPU）
 **启动命令：**  
 ```hub serving start -c config.json```  
 
@@ -164,7 +168,7 @@ export CUDA_VISIBLE_DEVICES=3
 hub serving start -c deploy/hubserving/ocr_system/config.json
 ```  
 
-## 发送预测请求
+## 3. 发送预测请求
 配置好服务端，可使用以下命令发送预测请求，获取预测结果:  
 
 ```python tools/test_hubserving.py server_url image_path```  
@@ -186,7 +190,7 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 访问示例：  
 ```python tools/test_hubserving.py --server_url=http://127.0.0.1:8868/predict/ocr_system --image_dir./doc/imgs/ --visualize=false```
 
-## 返回结果格式说明
+## 4. 返回结果格式说明
 返回结果为列表（list），列表中的每一项为词典（dict），词典一共可能包含3种字段，信息如下：
 
 |字段名称|数据类型|意义|
@@ -211,7 +215,7 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 
 **说明：** 如果需要增加、删除、修改返回字段，可在相应模块的`module.py`文件中进行修改，完整流程参考下一节自定义修改服务模块。
 
-## 自定义修改服务模块
+## 5. 自定义修改服务模块
 如果需要修改服务逻辑，你一般需要操作以下步骤（以修改`ocr_system`为例）：  
 
 - 1、 停止服务  
diff --git a/deploy/hubserving/readme_en.md b/deploy/hubserving/readme_en.md
index 79a07687..f360edbe 100755
--- a/deploy/hubserving/readme_en.md
+++ b/deploy/hubserving/readme_en.md
@@ -1,16 +1,17 @@
 English | [简体中文](readme.md)
 
 - [Service deployment based on PaddleHub Serving](#service-deployment-based-on-paddlehub-serving)
-  - [Quick start service](#quick-start-service)
-    - [1. Prepare the environment](#1-prepare-the-environment)
-    - [2. Download inference model](#2-download-inference-model)
-    - [3. Install Service Module](#3-install-service-module)
-    - [4. Start service](#4-start-service)
-      - [Way 1. Start with command line parameters (CPU only)](#way-1-start-with-command-line-parameters-cpu-only)
-      - [Way 2. Start with configuration file（CPU、GPU）](#way-2-start-with-configuration-filecpugpu)
-  - [Send prediction requests](#send-prediction-requests)
-  - [Returned result format](#returned-result-format)
-  - [User defined service module modification](#user-defined-service-module-modification)
+  - [1. Update](#1-update)
+  - [2. Quick start service](#2-quick-start-service)
+    - [2.1 Prepare the environment](#21-prepare-the-environment)
+    - [2.2 Download inference model](#22-download-inference-model)
+    - [2.3 Install Service Module](#23-install-service-module)
+    - [2.4 Start service](#24-start-service)
+      - [2.4.1 Start with command line parameters (CPU only)](#241-start-with-command-line-parameters-cpu-only)
+      - [2.4.2 Start with configuration file（CPU、GPU）](#242-start-with-configuration-filecpugpu)
+  - [3. Send prediction requests](#3-send-prediction-requests)
+  - [4. Returned result format](#4-returned-result-format)
+  - [5. User defined service module modification](#5-user-defined-service-module-modification)
 
 
 PaddleOCR provides 2 service deployment methods:
@@ -19,7 +20,7 @@ PaddleOCR provides 2 service deployment methods:
 
 # Service deployment based on PaddleHub Serving  
 
-The hubserving service deployment directory includes three service packages: text detection, text recognition, two-stage series connection and table recognition. Please select the corresponding service package to install and start service according to your needs. The directory is as follows:  
+The hubserving service deployment directory includes five service packages: text detection, text recognition, two-stage series connection, table recognition and PP-Structure. Please select the corresponding service package to install and start service according to your needs. The directory is as follows:  
 ```
 deploy/hubserving/
   └─  ocr_det     text detection module service package
@@ -38,18 +39,22 @@ deploy/hubserving/ocr_system/
   └─  module.py      Main module file, required, contains the complete logic of the service
   └─  params.py      Parameter file, required, including parameters such as model path, pre- and post-processing parameters
 ```
+## 1. Update
 
-## Quick start service
+* 2022.03.30 add PP-Structure and table recognition services。
+
+
+## 2. Quick start service
 The following steps take the 2-stage series service as an example. If only the detection service or recognition service is needed, replace the corresponding file path.
 
-### 1. Prepare the environment
+### 2.1 Prepare the environment
 ```shell
 # Install paddlehub  
 # python>3.6.2 is required bt paddlehub
 pip3 install paddlehub==2.1.0 --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
 ```
 
-### 2. Download inference model
+### 2.2 Download inference model
 Before installing the service module, you need to prepare the inference model and put it in the correct path. By default, the PP-OCRv2 models are used, and the default model path is:  
 ```
 text detection model: ./inference/ch_PP-OCRv2_det_infer/
@@ -60,7 +65,7 @@ tanle recognition: ./inference/en_ppocr_mobile_v2.0_table_structure_infer/
 
 **The model path can be found and modified in `params.py`.** More models provided by PaddleOCR can be obtained from the [model library](../../doc/doc_en/models_list_en.md). You can also use models trained by yourself.
 
-### 3. Install Service Module
+### 2.3 Install Service Module
 PaddleOCR provides 5 kinds of service modules, install the required modules according to your needs.
 
 * On Linux platform, the examples are as follows.
@@ -105,8 +110,8 @@ hub install deploy/hubserving/structure_table/
 hub install deploy\hubserving\structure_system\
 ```
 
-### 4. Start service
-#### Way 1. Start with command line parameters (CPU only)
+### 2.4 Start service
+#### 2.4.1 Start with command line parameters (CPU only)
 
 **start command：**  
 ```shell
@@ -131,7 +136,7 @@ hub serving start -m ocr_system
 
 This completes the deployment of a service API, using the default port number 8866.  
 
-#### Way 2. Start with configuration file（CPU、GPU）
+#### 2.4.2 Start with configuration file（CPU、GPU）
 **start command：**  
 ```shell
 hub serving start --config/-c config.json
@@ -168,7 +173,7 @@ export CUDA_VISIBLE_DEVICES=3
 hub serving start -c deploy/hubserving/ocr_system/config.json
 ```  
 
-## Send prediction requests
+## 3. Send prediction requests
 After the service starts, you can use the following command to send a prediction request to obtain the prediction result:  
 ```shell
 python tools/test_hubserving.py server_url image_path
@@ -194,7 +199,7 @@ For example, if using the configuration file to start the text angle classificat
 python tools/test_hubserving.py --server_url=http://127.0.0.1:8868/predict/ocr_system --image_dir./doc/imgs/ --visualize=false`
 ```
 
-## Returned result format
+## 4. Returned result format
 The returned result is a list. Each item in the list is a dict. The dict may contain three fields. The information is as follows:
 
 |field name|data type|description|
@@ -219,7 +224,7 @@ The fields returned by different modules are different. For example, the results
 
 **Note：** If you need to add, delete or modify the returned fields, you can modify the file `module.py` of the corresponding module. For the complete process, refer to the user-defined modification service module in the next section.
 
-## User defined service module modification
+## 5. User defined service module modification
 If you need to modify the service logic, the following steps are generally required (take the modification of `ocr_system` for example):
 
 - 1. Stop service
-- 
GitLab