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# Multi-language model
**Recent Update**
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- 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:
< div align = "center" >
< img src = "../imgs_results/multi_lang/en_1.jpg" width = "400" height = "600" >
< / div >
The multilingual models cover Latin, Arabic, Traditional Chinese, Korean, Japanese, etc.:
< div align = "center" >
< img src = "../imgs_results/multi_lang/japan_2.jpg" width = "600" height = "300" >
< img src = "../imgs_results/multi_lang/french_0.jpg" width = "300" height = "300" >
< / div >
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 )
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< a name = "Install" > < / a >
## 1 Installation
< a name = "paddle_install" > < / a >
### 1.1 paddle installation
```
# cpu
pip install paddlepaddle
# gpu
pip instll paddlepaddle-gpu
```
< a name = "paddleocr_package_install" > < / a >
### 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
```
< a name = "Quick_use" > < / a >
## 2 Quick use
< a name = "Command_line_operation" > < / a >
### 2.1 Command line operation
View help information
```
paddleocr -h
```
* Whole image prediction (detection + recognition)
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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.
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``` bash
paddleocr --image_dir doc/imgs/japan_2.jpg --lang=japan
```
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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)]
......
```
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* Recognition
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```bash
paddleocr --image_dir doc/imgs_words/japan/1.jpg --det false --lang=japan
```
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The result is a tuple, which returns the recognition result and recognition confidence
```text
('したがって', 0.99965394)
```
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* Detection
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```
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]]
......
```
< a name = "python_script_running" > < / a >
### 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:
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* Recognition
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```
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)
```
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The result is a tuple, which only contains the recognition result and recognition confidence
```
('leider auch jetzt', 0.97538936)
```
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* Detection
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```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:
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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 ).
< a name = "Custom_training" > < / a >
## 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.
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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,
For functions such as data annotation, you can read the complete [Document Tutorial ](../../README.md ).
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< a name = "language_abbreviation" > < / a >
## 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|
