Merge pull request #1049 from grasswolfs/update_readme_en_1028
update readme_en
This commit is contained in:
commit
9f548c2d4a
25
README.md
25
README.md
|
@ -1,13 +1,13 @@
|
|||
English | [简体中文](README_ch.md)
|
||||
|
||||
## Introduction
|
||||
PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice.
|
||||
PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.
|
||||
|
||||
**Recent updates**
|
||||
- 2020.9.22 Update the PP-OCR technical article, https://arxiv.org/abs/2009.09941
|
||||
- 2020.9.19 Update the ultra lightweight compressed ppocr_mobile_slim series models, the overall model size is 3.5M (see [PP-OCR Pipeline](#PP-OCR-Pipeline)), suitable for mobile deployment. [Model Downloads](#Supported-Chinese-model-list)
|
||||
- 2020.9.17 Update the ultra lightweight ppocr_mobile series and general ppocr_server series Chinese and English ocr models, which are comparable to commercial effects. [Model Downloads](#Supported-Chinese-model-list)
|
||||
- 2020.9.17 update [English recognition model](./doc/doc_en/models_list_en.md#english-recognition-model) and [Multilingual recognition model](doc/doc_en/models_list_en.md#english-recognition-model), `German`, `French`, `Japanese` and `Korean` have been supported. Models for more languages will continue to be updated.
|
||||
- 2020.9.17 update [English recognition model](./doc/doc_en/models_list_en.md#english-recognition-model) and [Multilingual recognition model](doc/doc_en/models_list_en.md#english-recognition-model), `English`, `Chinese`, `German`, `French`, `Japanese` and `Korean` have been supported. Models for more languages will continue to be updated.
|
||||
- 2020.8.24 Support the use of PaddleOCR through whl package installation,please refer [PaddleOCR Package](./doc/doc_en/whl_en.md)
|
||||
- 2020.8.21 Update the replay and PPT of the live lesson at Bilibili on August 18, lesson 2, easy to learn and use OCR tool spree. [Get Address](https://aistudio.baidu.com/aistudio/education/group/info/1519)
|
||||
- [more](./doc/doc_en/update_en.md)
|
||||
|
@ -64,6 +64,10 @@ Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Andr
|
|||
| Chinese and English ultra-lightweight OCR model (8.1M) | ch_ppocr_mobile_v1.1_xx | Mobile & server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_pre.tar) |
|
||||
| Chinese and English general OCR model (155.1M) | ch_ppocr_server_v1.1_xx | Server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_pre.tar) |
|
||||
| Chinese and English ultra-lightweight compressed OCR model (3.5M) | ch_ppocr_mobile_slim_v1.1_xx | Mobile | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_det_prune_opt.nb) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_cls_quant_opt.nb) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_rec_quant_opt.nb) |
|
||||
| French ultra-lightweight OCR model (4.6M) | french_ppocr_mobile_v1.1_xx | Mobile & server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | - | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/fr/french_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/fr/french_ppocr_mobile_v1.1_rec_train.tar) |
|
||||
| German ultra-lightweight OCR model (4.6M) | german_ppocr_mobile_v1.1_xx | Mobile & server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | - |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/ge/german_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/ge/german_ppocr_mobile_v1.1_rec_train.tar) |
|
||||
| Korean ultra-lightweight OCR model (5.9M) | korean_ppocr_mobile_v1.1_xx | Mobile & server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | - |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/kr/korean_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/kr/korean_ppocr_mobile_v1.1_rec_train.tar)|
|
||||
| Japan ultra-lightweight OCR model (6.2M) | japan_ppocr_mobile_v1.1_xx | Mobile & server | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | - |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/jp/japan_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/jp/japan_ppocr_mobile_v1.1_rec_train.tar) |
|
||||
|
||||
For more model downloads (including multiple languages), please refer to [PP-OCR v1.1 series model downloads](./doc/doc_en/models_list_en.md)
|
||||
|
||||
|
@ -136,6 +140,23 @@ PP-OCR is a practical ultra-lightweight OCR system. It is mainly composed of thr
|
|||
</div>
|
||||
|
||||
|
||||
<a name="language request"></a>
|
||||
## Guideline for new language request
|
||||
|
||||
If you want to request a new language support, a PR with 2 following files are needed:
|
||||
|
||||
1. In folder [ppocr/utils/dict](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/ppocr/utils/dict),
|
||||
it is necessary to submit the dict text to this path and name it with `{language}_dict.txt` that contains a list of all characters. Please see the format example from other files in that folder.
|
||||
|
||||
2. In folder [ppocr/utils/corpus](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/ppocr/utils/corpus),
|
||||
it is necessary to submit the corpus to this path and name it with `{language}_corpus.txt` that contains a list of words in your language.
|
||||
Maybe, 50000 words per language is necessary at least.
|
||||
Of course, the more, the better.
|
||||
|
||||
If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on.
|
||||
|
||||
More details, see [Multilingual OCR Development Plan](https://github.com/PaddlePaddle/PaddleOCR/issues/1048)
|
||||
|
||||
|
||||
<a name="LICENSE"></a>
|
||||
## License
|
||||
|
|
Loading…
Reference in New Issue