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