# Multi-language model **Recent Update** - 2021.4.9 supports the detection and recognition of 80 languages - 2021.4.9 supports **lightweight high-precision** English model detection and recognition PaddleOCR aims to create a rich, leading, and practical OCR tool library, which not only provides Chinese and English models in general scenarios, but also provides models specifically trained in English scenarios. And multilingual models covering [80 languages](#language_abbreviations). Among them, the English model supports the detection and recognition of uppercase and lowercase letters and common punctuation, and the recognition of space characters is optimized:
The multilingual models cover Latin, Arabic, Traditional Chinese, Korean, Japanese, etc.:
This document will briefly introduce how to use the multilingual model. - [1 Installation](#Install) - [1.1 paddle installation](#paddleinstallation) - [1.2 paddleocr package installation](#paddleocr_package_install) - [2 Quick Use](#Quick_Use) - [2.1 Command line operation](#Command_line_operation) - [2.1.1 Prediction of the whole image](#bash_detection+recognition) - [2.1.2 Recognition](#bash_Recognition) - [2.1.3 Detection](#bash_detection) - [2.2 python script running](#python_Script_running) - [2.2.1 Whole image prediction](#python_detection+recognition) - [2.2.2 Recognition](#python_Recognition) - [2.2.3 Detection](#python_detection) - [3 Custom Training](#Custom_Training) - [4 Supported languages and abbreviations](#language_abbreviations) ## 1 Installation ### 1.1 paddle installation ``` # cpu pip install paddlepaddle # gpu pip instll paddlepaddle-gpu ``` ### 1.2 paddleocr package installation pip install ``` pip install "paddleocr>=2.0.4" # 2.0.4 version is recommended ``` Build and install locally ``` python3 setup.py bdist_wheel pip3 install dist/paddleocr-x.x.x-py3-none-any.whl # x.x.x is the version number of paddleocr ``` ## 2 Quick use ### 2.1 Command line operation View help information ``` paddleocr -h ``` * Whole image prediction (detection + recognition) Paddleocr currently supports 80 languages, which can be switched by modifying the --lang parameter. The specific supported [language] (#language_abbreviations) can be viewed in the table. ``` bash paddleocr --image_dir doc/imgs/japan_2.jpg --lang=japan ``` ![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs/japan_2.jpg) The result is a list, each item contains a text box, text and recognition confidence ```text [[[671.0, 60.0], [847.0, 63.0], [847.0, 104.0], [671.0, 102.0]], ('もちもち', 0.9993342)] [[[394.0, 82.0], [536.0, 77.0], [538.0, 127.0], [396.0, 132.0]], ('自然の', 0.9919842)] [[[880.0, 89.0], [1014.0, 93.0], [1013.0, 127.0], [879.0, 124.0]], ('とろっと', 0.9976762)] [[[1067.0, 101.0], [1294.0, 101.0], [1294.0, 138.0], [1067.0, 138.0]], ('后味のよい', 0.9988712)] ...... ``` * Recognition ```bash paddleocr --image_dir doc/imgs_words/japan/1.jpg --det false --lang=japan ``` ![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_words/japan/1.jpg) The result is a tuple, which returns the recognition result and recognition confidence ```text ('したがって', 0.99965394) ``` * Detection ``` paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --rec false ``` The result is a list, each item contains only text boxes ``` [[26.0, 457.0], [137.0, 457.0], [137.0, 477.0], [26.0, 477.0]] [[25.0, 425.0], [372.0, 425.0], [372.0, 448.0], [25.0, 448.0]] [[128.0, 397.0], [273.0, 397.0], [273.0, 414.0], [128.0, 414.0]] ...... ``` ### 2.2 python script running ppocr also supports running in python scripts for easy embedding in your own code: * Whole image prediction (detection + recognition) ``` from paddleocr import PaddleOCR, draw_ocr # Also switch the language by modifying the lang parameter ocr = PaddleOCR(lang="korean") # The model file will be downloaded automatically when executed for the first time img_path ='doc/imgs/korean_1.jpg' result = ocr.ocr(img_path) # Print detection frame and recognition result for line in result: print(line) # Visualization from PIL import Image image = Image.open(img_path).convert('RGB') boxes = [line[0] for line in result] txts = [line[1][0] for line in result] scores = [line[1][1] for line in result] im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc/korean.ttf') im_show = Image.fromarray(im_show) im_show.save('result.jpg') ``` Visualization of results: ![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_results/korean.jpg) * Recognition ``` from paddleocr import PaddleOCR ocr = PaddleOCR(lang="german") img_path ='PaddleOCR/doc/imgs_words/german/1.jpg' result = ocr.ocr(img_path, det=False, cls=True) for line in result: print(line) ``` ![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_words/german/1.jpg) The result is a tuple, which only contains the recognition result and recognition confidence ``` ('leider auch jetzt', 0.97538936) ``` * Detection ```python from paddleocr import PaddleOCR, draw_ocr ocr = PaddleOCR() # need to run only once to download and load model into memory img_path ='PaddleOCR/doc/imgs_en/img_12.jpg' result = ocr.ocr(img_path, rec=False) for line in result: print(line) # show result from PIL import Image image = Image.open(img_path).convert('RGB') im_show = draw_ocr(image, result, txts=None, scores=None, font_path='/path/to/PaddleOCR/doc/fonts/simfang.ttf') im_show = Image.fromarray(im_show) im_show.save('result.jpg') ``` The result is a list, each item contains only text boxes ```bash [[26.0, 457.0], [137.0, 457.0], [137.0, 477.0], [26.0, 477.0]] [[25.0, 425.0], [372.0, 425.0], [372.0, 448.0], [25.0, 448.0]] [[128.0, 397.0], [273.0, 397.0], [273.0, 414.0], [128.0, 414.0]] ...... ``` Visualization of results: ![](https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.1/doc/imgs_results/whl/12_det.jpg) ppocr also supports direction classification. For more usage methods, please refer to: [whl package instructions](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.0/doc/doc_ch/whl.md). ## 3 Custom training ppocr supports using your own data for custom training or finetune, where the recognition model can refer to [French configuration file](../../configs/rec/multi_language/rec_french_lite_train.yml) Modify the training data path, dictionary and other parameters. For specific data preparation and training process, please refer to: [Text Detection](../doc_en/detection_en.md), [Text Recognition](../doc_en/recognition_en.md), more functions such as predictive deployment, For functions such as data annotation, you can read the complete [Document Tutorial](../../README.md). ## 4 Support languages and abbreviations | Language | Abbreviation | | --- | --- | |chinese and english|ch| |english|en| |french|fr| |german|german| |japan|japan| |korean|korean| |chinese traditional |ch_tra| | Italian |it| |Spanish |es| | Portuguese|pt| |Russia|ru| |Arabic|ar| |Hindi|hi| |Uyghur|ug| |Persian|fa| |Urdu|ur| | Serbian(latin) |rs_latin| |Occitan |oc| |Marathi|mr| |Nepali|ne| |Serbian(cyrillic)|rs_cyrillic| |Bulgarian |bg| |Ukranian|uk| |Belarusian|be| |Telugu |te| |Kannada |kn| |Tamil |ta| |Afrikaans |af| |Azerbaijani |az| |Bosnian|bs| |Czech|cs| |Welsh |cy| |Danish|da| |Estonian |et| |Irish |ga| |Croatian |hr| |Hungarian |hu| |Indonesian|id| |Icelandic|is| |Kurdish|ku| |Lithuanian |lt| |Latvian |lv| |Maori|mi| |Malay|ms| |Maltese |mt| |Dutch |nl| |Norwegian |no| |Polish |pl| |Romanian |ro| |Slovak |sk| |Slovenian |sl| |Albanian |sq| |Swedish |sv| |Swahili |sw| |Tagalog |tl| |Turkish |tr| |Uzbek |uz| |Vietnamese |vi| |Mongolian |mn| |Abaza |abq| |Adyghe |ady| |Kabardian |kbd| |Avar |ava| |Dargwa |dar| |Ingush |inh| |Lak |lbe| |Lezghian |lez| |Tabassaran |tab| |Bihari |bh| |Maithili |mai| |Angika |ang| |Bhojpuri |bho| |Magahi |mah| |Nagpur |sck| |Newari |new| |Goan Konkani|gom| |Saudi Arabia|sa|