update doc

README.md

 English [README](./README_en.md) (`out-dated`).
 
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 # cnocr
 
-**cnocr** 是 **Python 3** 下的**文字识别**（**Optical Character Recognition**，简称**OCR**）工具包，支持**中文**、**英文**的常见字符识别，自带了多个训练好的识别模型，安装后即可直接使用。欢迎扫码加入QQ交流群：
+**cnocr** 是 **Python 3** 下的**文字识别**（**Optical Character Recognition**，简称**OCR**）工具包，支持**中文**、**英文**的常见字符识别，自带了多个训练好的识别模型，安装后即可直接使用。欢迎扫码加入微信交流群：
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+![QQ群二维码](./docs/cnocr-wx.png)
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+作者也维护 **知识星球** [**CnOCR/CnSTD私享群**](https://t.zsxq.com/FEYZRJQ)，欢迎加入。**知识星球私享群**会陆续发布一些CnOCR/CnSTD相关的私有资料，包括**更详细的训练教程**，**未公开的模型**，使用过程中遇到的难题解答等。本群也会发布OCR/STD相关的最新研究资料。此外，**私享群中作者每月提供两次免费特有数据的训练服务**。
 
-![QQ群二维码](./docs/cnocr-qq.jpg)
 
 
 ## 详细文档
@@ -16,28 +20,24 @@ English [README](./README_en.md) (`out-dated`).
 
 **cnocr** 主要针对的是**排版简单的印刷体文字图片**，如截图图片，扫描件等。目前内置的文字检测和分行模块无法处理复杂的文字排版定位。如果要用于场景文字图片的识别，需要结合其他的场景文字检测引擎使用，例如文字检测引擎 **[cnstd](https://github.com/breezedeus/cnstd)** 。
 
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 ## 示例
 
-| 图片                                                         | OCR结果                                                      |
-| ------------------------------------------------------------ | ------------------------------------------------------------ |
-| ![docs/examples/helloworld.jpg](./docs/examples/helloworld.jpg)        | Hello world!你好世界                                         |
-| ![docs/examples/chn-00199989.jpg](./docs/examples/chn-00199989.jpg)    | 铑泡胭释邑疫反隽寥缔                                         |
-| ![docs/examples/chn-00199980.jpg](./docs/examples/chn-00199980.jpg)    | 拇箬遭才柄腾戮胖惬炫                                         |
-| ![docs/examples/chn-00199984.jpg](./docs/examples/chn-00199984.jpg)    | 寿猿嗅髓孢刀谎弓供捣                                         |
-| ![docs/examples/chn-00199985.jpg](./docs/examples/chn-00199985.jpg)    | 马靼蘑熨距额猬要藕萼                                         |
-| ![docs/examples/chn-00199981.jpg](./docs/examples/chn-00199981.jpg)    | 掉江悟厉励.谌查门蠕坑                                        |
-| ![docs/examples/00199975.jpg](./docs/examples/00199975.jpg)            | nd-chips fructed ast                                         |
-| ![docs/examples/00199978.jpg](./docs/examples/00199978.jpg)            | zouna unpayably Raqu                                         |
-| ![docs/examples/00199979.jpg](./docs/examples/00199979.jpg)            | ape fissioning Senat                                         |
-| ![docs/examples/00199971.jpg](./docs/examples/00199971.jpg)            | ling oughtlins near                                          |
-| ![docs/examples/multi-line_cn1.png](./docs/examples/multi-line_cn1.png) | 网络支付并无本质的区别，因为<br />每一个手机号码和邮件地址背后<br />都会对应着一个账户--这个账<br />户可以是信用卡账户、借记卡账<br />户，也包括邮局汇款、手机代<br />收、电话代收、预付费卡和点卡<br />等多种形式。 |
-| ![docs/examples/multi-line_cn2.png](./docs/examples/multi-line_cn2.png) | 当然，在媒介越来越多的情形下,<br />意味着传播方式的变化。过去主流<br />的是大众传播,现在互动性和定制<br />性带来了新的挑战——如何让品牌<br />与消费者更加互动。 |
+| 图片                                                                                | OCR结果                                                                                                                                                                                                                                                                                                                                                                     |
+| --------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| ![docs/examples/helloworld.jpg](./docs/examples/helloworld.jpg)                   | Hello world!你好世界                                                                                                                                                                                                                                                                                                                                                          |
+| ![docs/examples/chn-00199989.jpg](./docs/examples/chn-00199989.jpg)               | 铑泡胭释邑疫反隽寥缔                                                                                                                                                                                                                                                                                                                                                                |
+| ![docs/examples/chn-00199980.jpg](./docs/examples/chn-00199980.jpg)               | 拇箬遭才柄腾戮胖惬炫                                                                                                                                                                                                                                                                                                                                                                |
+| ![docs/examples/chn-00199984.jpg](./docs/examples/chn-00199984.jpg)               | 寿猿嗅髓孢刀谎弓供捣                                                                                                                                                                                                                                                                                                                                                                |
+| ![docs/examples/chn-00199985.jpg](./docs/examples/chn-00199985.jpg)               | 马靼蘑熨距额猬要藕萼                                                                                                                                                                                                                                                                                                                                                                |
+| ![docs/examples/chn-00199981.jpg](./docs/examples/chn-00199981.jpg)               | 掉江悟厉励.谌查门蠕坑                                                                                                                                                                                                                                                                                                                                                               |
+| ![docs/examples/00199975.jpg](./docs/examples/00199975.jpg)                       | nd-chips fructed ast                                                                                                                                                                                                                                                                                                                                                      |
+| ![docs/examples/00199978.jpg](./docs/examples/00199978.jpg)                       | zouna unpayably Raqu                                                                                                                                                                                                                                                                                                                                                      |
+| ![docs/examples/00199979.jpg](./docs/examples/00199979.jpg)                       | ape fissioning Senat                                                                                                                                                                                                                                                                                                                                                      |
+| ![docs/examples/00199971.jpg](./docs/examples/00199971.jpg)                       | ling oughtlins near                                                                                                                                                                                                                                                                                                                                                       |
+| ![docs/examples/multi-line_cn1.png](./docs/examples/multi-line_cn1.png)           | 网络支付并无本质的区别，因为<br />每一个手机号码和邮件地址背后<br />都会对应着一个账户--这个账<br />户可以是信用卡账户、借记卡账<br />户，也包括邮局汇款、手机代<br />收、电话代收、预付费卡和点卡<br />等多种形式。                                                                                                                                                                                                                                             |
+| ![docs/examples/multi-line_cn2.png](./docs/examples/multi-line_cn2.png)           | 当然，在媒介越来越多的情形下,<br />意味着传播方式的变化。过去主流<br />的是大众传播,现在互动性和定制<br />性带来了新的挑战——如何让品牌<br />与消费者更加互动。                                                                                                                                                                                                                                                                             |
 | ![docs/examples/multi-line_en_white.png](./docs/examples/multi-line_en_white.png) | This chapter is currently only available in this web version. ebook and print will follow.<br />Convolutional neural networks learn abstract features and concepts from raw image pixels. Feature<br />Visualization visualizes the learned features by activation maximization. Network Dissection labels<br />neural network units (e.g. channels) with human concepts. |
-| ![docs/examples/multi-line_en_black.png](./docs/examples/multi-line_en_black.png) | transforms the image many times. First, the image goes through many convolutional layers. In those<br />convolutional layers, the network learns new and increasingly complex features in its layers. Then the <br />transformed image information goes through the fully connected layers and turns into a classification<br />or prediction. |
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+| ![docs/examples/multi-line_en_black.png](./docs/examples/multi-line_en_black.png) | transforms the image many times. First, the image goes through many convolutional layers. In those<br />convolutional layers, the network learns new and increasingly complex features in its layers. Then the <br />transformed image information goes through the fully connected layers and turns into a classification<br />or prediction.                            |
 
 ## 安装
 
@@ -47,19 +47,14 @@ English [README](./README_en.md) (`out-dated`).
 pip install cnocr
 ```
 
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 安装速度慢的话，可以指定国内的安装源，如使用豆瓣源：
 
 ```bash
 pip install cnocr -i https://pypi.doubanio.com/simple
 ```
 
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 > 注意：请使用 **Python3**（3.6以及之后版本应该都行），没测过Python2下是否ok。
 
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 ## 未来工作
 
 * [x] 支持图片包含多行文字 (`Done`)
@@ -72,4 +67,3 @@ pip install cnocr -i https://pypi.doubanio.com/simple
 * [x] 由 MXNet 改为 PyTorch 架构（since `V2.0.0`）
 * [x] 基于 PyTorch 训练更高效的模型
 * [ ] 支持列格式的文字识别
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