Merge branch 'dygraph' into pgnet-postpro
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- 2021.4.9 支持**80种**语言的检测和识别
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- 2021.4.9 支持**轻量高精度**英文模型检测识别
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PaddleOCR 旨在打造一套丰富、领先、且实用的OCR工具库,不仅提供了通用场景下的中英文模型,也提供了专门在英文场景下训练的模型,
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和覆盖[80个语言](#语种缩写)的小语种模型。
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其中英文模型支持,大小写字母和常见标点的检测识别,并优化了空格字符的识别:
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<div align="center">
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<img src="../imgs_results/multi_lang/en_1.jpg" width="400" height="600">
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</div>
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小语种模型覆盖了拉丁语系、阿拉伯语系、中文繁体、韩语、日语等等:
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<div align="center">
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<img src="../imgs_results/multi_lang/japan_2.jpg" width="600" height="300">
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<img src="../imgs_results/multi_lang/french_0.jpg" width="300" height="300">
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</div>
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本文档将简要介绍小语种模型的使用方法。
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- [1 安装](#安装)
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- [1.1 paddle 安装](#paddle安装)
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- [1.2 paddleocr package 安装](#paddleocr_package_安装)
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paddleocr --image_dir doc/imgs/japan_2.jpg --lang=japan
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```
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![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/imgs/japan_2.jpg)
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<div align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs/japan_2.jpg" width="800">
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</div>
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结果是一个list,每个item包含了文本框,文字和识别置信度
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```text
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```
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结果可视化:
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![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/imgs_results/korean.jpg)
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<div align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_results/korean.jpg" width="800">
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</div>
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* 识别预测
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print(line)
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```
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![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/imgs_words/german/1.jpg)
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![](../imgs_words/german/1.jpg)
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结果是一个tuple,只包含识别结果和识别置信度
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```
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结果可视化 :
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![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/imgs_results/whl/12_det.jpg)
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<div align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_results/whl/12_det.jpg" width="800">
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</div>
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ppocr 还支持方向分类, 更多使用方式请参考:[whl包使用说明](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.0/doc/doc_ch/whl.md)。
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-2021.4.9 supports the detection and recognition of 80 languages
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-2021.4.9 supports **lightweight high-precision** English model detection and recognition
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PaddleOCR aims to create a rich, leading, and practical OCR tool library, which not only provides
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Chinese and English models in general scenarios, but also provides models specifically trained
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in English scenarios. And multilingual models covering [80 languages](#language_abbreviations).
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Among them, the English model supports the detection and recognition of uppercase and lowercase
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letters and common punctuation, and the recognition of space characters is optimized:
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<div align="center">
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<img src="../imgs_results/multi_lang/en_1.jpg" width="400" height="600">
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</div>
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The multilingual models cover Latin, Arabic, Traditional Chinese, Korean, Japanese, etc.:
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<div align="center">
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<img src="../imgs_results/multi_lang/japan_2.jpg" width="600" height="300">
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<img src="../imgs_results/multi_lang/french_0.jpg" width="300" height="300">
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</div>
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This document will briefly introduce how to use the multilingual model.
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-[1 Installation](#Install)
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-[1.1 paddle installation](#paddleinstallation)
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-[1.2 paddleocr package installation](#paddleocr_package_install)
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