Merge pull request #1423 from PaddlePaddle/dygraph_doc
update Readme.md
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MissPenguin
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README.md
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README.md
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English | [简体中文](README_ch.md)
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## Introduction
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PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice.
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PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.
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||||
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**Recent updates**
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- 2020.11.25 Update a new data annotation tool, i.e., [PPOCRLabel](./PPOCRLabel/README_en.md), which is helpful to improve the labeling efficiency. Moreover, the labeling results can be used in training of the PP-OCR system directly.
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- 2020.9.22 Update the PP-OCR technical article, https://arxiv.org/abs/2009.09941
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- 2020.9.19 Update the ultra lightweight compressed ppocr_mobile_slim series models, the overall model size is 3.5M (see [PP-OCR Pipline](#PP-OCR-Pipline)), suitable for mobile deployment. [Model Downloads](#Supported-Chinese-model-list)
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- 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)
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- 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)
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- 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.
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- 2020.8.24 Support the use of PaddleOCR through whl package installation，pelease refer [PaddleOCR Package](./doc/doc_en/whl_en.md)
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- 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.
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- 2020.8.24 Support the use of PaddleOCR through whl package installation，please refer [PaddleOCR Package](./doc/doc_en/whl_en.md)
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- 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)
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- [more](./doc/doc_en/update_en.md)
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@ -32,6 +33,15 @@ PaddleOCR aims to create rich, leading, and practical OCR tools that help users
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The above pictures are the visualizations of the general ppocr_server model. For more effect pictures, please see [More visualizations](./doc/doc_en/visualization_en.md).
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<a name="Community"></a>
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## Community
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- Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
|
||||
|
||||
<div align="center">
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<img src="./doc/joinus.PNG" width = "200" height = "200" />
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</div>
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## Quick Experience
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You can also quickly experience the ultra-lightweight OCR : [Online Experience](https://www.paddlepaddle.org.cn/hub/scene/ocr)
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@ -48,55 +58,65 @@ Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Andr
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<a name="Supported-Chinese-model-list"></a>
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## PP-OCR 1.1 series model list（Update on Sep 17）
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## PP-OCR 2.0 series model list（Update on Dec 15）
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| Model introduction | Model name | Recommended scene | Detection model | Direction classifier | Recognition model |
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| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| 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) |
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| 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) |
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| 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) |
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| Chinese and English ultra-lightweight OCR model (8.1M) | ch_ppocr_mobile_v2.0_xx | Mobile & server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) |
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| Chinese and English general OCR model (143M) | ch_ppocr_server_v2.0_xx | Server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_traingit.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) |
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For more model downloads (including multiple languages), please refer to [PP-OCR v1.1 series model downloads](./doc/doc_en/models_list_en.md)
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For more model downloads (including multiple languages), please refer to [PP-OCR v2.0 series model downloads](./doc/doc_en/models_list_en.md).
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For a new language request, please refer to [Guideline for new language_requests](#language_requests).
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## Tutorials
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- [Installation](./doc/doc_en/installation_en.md)
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- [Quick Start](./doc/doc_en/quickstart_en.md)
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- [Code Structure](./doc/doc_en/tree_en.md)
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- Algorithm introduction
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- Algorithm Introduction
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- [Text Detection Algorithm](./doc/doc_en/algorithm_overview_en.md)
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- [Text Recognition Algorithm](./doc/doc_en/algorithm_overview_en.md)
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- [PP-OCR Pipline](#PP-OCR-Pipline)
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- Model training/evaluation
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- [PP-OCR Pipeline](#PP-OCR-Pipeline)
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- Model Training/Evaluation
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- [Text Detection](./doc/doc_en/detection_en.md)
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- [Text Recognition](./doc/doc_en/recognition_en.md)
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- [Direction Classification](./doc/doc_en/angle_class_en.md)
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- [Yml Configuration](./doc/doc_en/config_en.md)
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- Inference and Deployment
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- [Quick inference based on pip](./doc/doc_en/whl_en.md)
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- [Quick Inference Based on PIP](./doc/doc_en/whl_en.md)
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- [Python Inference](./doc/doc_en/inference_en.md)
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- [C++ Inference](./deploy/cpp_infer/readme_en.md)
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- [Serving](./deploy/hubserving/readme_en.md)
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- [Mobile](./deploy/lite/readme_en.md)
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- [Model Quantization](./deploy/slim/quantization/README_en.md)
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- [Model Compression](./deploy/slim/prune/README_en.md)
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- [Mobile](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme_en.md)
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- [Model Quantization](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/slim/quantization/README_en.md)
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- [Model Compression](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/slim/prune/README_en.md)
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- [Benchmark](./doc/doc_en/benchmark_en.md)
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- Data Annotation and Synthesis
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- [Semi-automatic Annotation Tool](./PPOCRLabel/README_en.md)
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- [Data Annotation Tools](./doc/doc_en/data_annotation_en.md)
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- [Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md)
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- Datasets
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- [General OCR Datasets(Chinese/English)](./doc/doc_en/datasets_en.md)
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- [HandWritten_OCR_Datasets(Chinese)](./doc/doc_en/handwritten_datasets_en.md)
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- [Various OCR Datasets(multilingual)](./doc/doc_en/vertical_and_multilingual_datasets_en.md)
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- [Data Annotation Tools](./doc/doc_en/data_annotation_en.md)
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- [Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md)
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- [Visualization](#Visualization)
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- [New language requests](#language_requests)
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- [FAQ](./doc/doc_en/FAQ_en.md)
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- [Community](#Community)
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- [References](./doc/doc_en/reference_en.md)
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- [License](#LICENSE)
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- [Contribution](#CONTRIBUTION)
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<a name="PP-OCR-Pipline"></a>
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***Note: The dynamic graphs branch is still under development.
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Currently, only dynamic graph training, python-end prediction, and C++ prediction are supported.
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If you need mobile-end deployment cases or quantitative demo,
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please use the static graph branch.***
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## PP-OCR Pipline
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<a name="PP-OCR-Pipeline"></a>
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## PP-OCR Pipeline
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<div align="center">
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<img src="./doc/ppocr_framework.png" width="800">
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@ -126,13 +146,24 @@ PP-OCR is a practical ultra-lightweight OCR system. It is mainly composed of thr
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<img src="./doc/imgs_results/1112.jpg" width="800">
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</div>
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<a name="Community"></a>
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## Community
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Scan the QR code below with your Wechat and completing the questionnaire, you can access to official technical exchange group.
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<div align="center">
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<img src="./doc/joinus.PNG" width = "200" height = "200" />
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</div>
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<a name="language_requests"></a>
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## Guideline for new language requests
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If you want to request a new language support, a PR with 2 following files are needed：
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1. In folder [ppocr/utils/dict](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/ppocr/utils/dict),
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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.
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2. In folder [ppocr/utils/corpus](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/ppocr/utils/corpus),
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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.
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Maybe, 50000 words per language is necessary at least.
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Of course, the more, the better.
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If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on.
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More details, please refer to [Multilingual OCR Development Plan](https://github.com/PaddlePaddle/PaddleOCR/issues/1048).
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<a name="LICENSE"></a>
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## License
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@ -149,3 +180,7 @@ We welcome all the contributions to PaddleOCR and appreciate for your feedback v
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- Thanks [authorfu](https://github.com/authorfu) for contributing Android demo and [xiadeye](https://github.com/xiadeye) contributing iOS demo, respectively.
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- Thanks [BeyondYourself](https://github.com/BeyondYourself) for contributing many great suggestions and simplifying part of the code style.
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- Thanks [tangmq](https://gitee.com/tangmq) for contributing Dockerized deployment services to PaddleOCR and supporting the rapid release of callable Restful API services.
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- Thanks [lijinhan](https://github.com/lijinhan) for contributing a new way, i.e., java SpringBoot, to achieve the request for the Hubserving deployment.
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- Thanks [Mejans](https://github.com/Mejans) for contributing the Occitan corpus and character set.
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- Thanks [LKKlein](https://github.com/LKKlein) for contributing a new deploying package with the Golang program language.
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- Thanks [Evezerest](https://github.com/Evezerest), [ninetailskim](https://github.com/ninetailskim), [edencfc](https://github.com/edencfc), [BeyondYourself](https://github.com/BeyondYourself) and [1084667371](https://github.com/1084667371) for contributing a new data annotation tool, i.e., PPOCRLabel。
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186
README_en.md
186
README_en.md
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@ -1,186 +0,0 @@
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English | [简体中文](README_ch.md)
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## Introduction
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PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.
|
||||
|
||||
**Recent updates**
|
||||
- 2020.11.25 Update a new data annotation tool, i.e., [PPOCRLabel](./PPOCRLabel/README_en.md), which is helpful to improve the labeling efficiency. Moreover, the labeling results can be used in training of the PP-OCR system directly.
|
||||
- 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), `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)
|
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|
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## Features
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- PPOCR series of high-quality pre-trained models, comparable to commercial effects
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- Ultra lightweight ppocr_mobile series models: detection (2.6M) + direction classifier (0.9M) + recognition (4.6M) = 8.1M
|
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- General ppocr_server series models: detection (47.2M) + direction classifier (0.9M) + recognition (107M) = 155.1M
|
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- Ultra lightweight compression ppocr_mobile_slim series models: detection (1.4M) + direction classifier (0.5M) + recognition (1.6M) = 3.5M
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- Support Chinese, English, and digit recognition, vertical text recognition, and long text recognition
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- Support multi-language recognition: Korean, Japanese, German, French
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- Support user-defined training, provides rich predictive inference deployment solutions
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- Support PIP installation, easy to use
|
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- Support Linux, Windows, MacOS and other systems
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|
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## Visualization
|
||||
|
||||
<div align="center">
|
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<img src="doc/imgs_results/1101.jpg" width="800">
|
||||
<img src="doc/imgs_results/1103.jpg" width="800">
|
||||
</div>
|
||||
|
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The above pictures are the visualizations of the general ppocr_server model. For more effect pictures, please see [More visualizations](./doc/doc_en/visualization_en.md).
|
||||
|
||||
<a name="Community"></a>
|
||||
## Community
|
||||
- Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
|
||||
|
||||
<div align="center">
|
||||
<img src="./doc/joinus.PNG" width = "200" height = "200" />
|
||||
</div>
|
||||
|
||||
|
||||
## Quick Experience
|
||||
|
||||
You can also quickly experience the ultra-lightweight OCR : [Online Experience](https://www.paddlepaddle.org.cn/hub/scene/ocr)
|
||||
|
||||
Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Android systems): [Sign in to the website to obtain the QR code for installing the App](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)
|
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|
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Also, you can scan the QR code below to install the App (**Android support only**)
|
||||
|
||||
<div align="center">
|
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<img src="./doc/ocr-android-easyedge.png" width = "200" height = "200" />
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</div>
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- [**OCR Quick Start**](./doc/doc_en/quickstart_en.md)
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|
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<a name="Supported-Chinese-model-list"></a>
|
||||
|
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## PP-OCR 2.0 series model list（Update on Sep 17）
|
||||
|
||||
| Model introduction | Model name | Recommended scene | Detection model | Direction classifier | Recognition model |
|
||||
| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
|
||||
| Chinese and English ultra-lightweight OCR model (8.1M) | ch_ppocr_mobile_v2.0_xx | Mobile & server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) |
|
||||
| Chinese and English general OCR model (143M) | ch_ppocr_server_v2.0_xx | Server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_traingit.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) |
|
||||
|
||||
|
||||
For more model downloads (including multiple languages), please refer to [PP-OCR v2.0 series model downloads](./doc/doc_en/models_list_en.md).
|
||||
|
||||
For a new language request, please refer to [Guideline for new language_requests](#language_requests).
|
||||
|
||||
## Tutorials
|
||||
- [Installation](./doc/doc_en/installation_en.md)
|
||||
- [Quick Start](./doc/doc_en/quickstart_en.md)
|
||||
- [Code Structure](./doc/doc_en/tree_en.md)
|
||||
- Algorithm Introduction
|
||||
- [Text Detection Algorithm](./doc/doc_en/algorithm_overview_en.md)
|
||||
- [Text Recognition Algorithm](./doc/doc_en/algorithm_overview_en.md)
|
||||
- [PP-OCR Pipeline](#PP-OCR-Pipeline)
|
||||
- Model Training/Evaluation
|
||||
- [Text Detection](./doc/doc_en/detection_en.md)
|
||||
- [Text Recognition](./doc/doc_en/recognition_en.md)
|
||||
- [Direction Classification](./doc/doc_en/angle_class_en.md)
|
||||
- [Yml Configuration](./doc/doc_en/config_en.md)
|
||||
- Inference and Deployment
|
||||
- [Quick Inference Based on PIP](./doc/doc_en/whl_en.md)
|
||||
- [Python Inference](./doc/doc_en/inference_en.md)
|
||||
- [C++ Inference](./deploy/cpp_infer/readme_en.md)
|
||||
- [Serving](./deploy/hubserving/readme_en.md)
|
||||
- [Mobile](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme_en.md)
|
||||
- [Model Quantization](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/slim/quantization/README_en.md)
|
||||
- [Model Compression](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/slim/prune/README_en.md)
|
||||
- [Benchmark](./doc/doc_en/benchmark_en.md)
|
||||
- Data Annotation and Synthesis
|
||||
- [Semi-automatic Annotation Tool](./PPOCRLabel/README_en.md)
|
||||
- [Data Annotation Tools](./doc/doc_en/data_annotation_en.md)
|
||||
- [Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md)
|
||||
- Datasets
|
||||
- [General OCR Datasets(Chinese/English)](./doc/doc_en/datasets_en.md)
|
||||
- [HandWritten_OCR_Datasets(Chinese)](./doc/doc_en/handwritten_datasets_en.md)
|
||||
- [Various OCR Datasets(multilingual)](./doc/doc_en/vertical_and_multilingual_datasets_en.md)
|
||||
- [Visualization](#Visualization)
|
||||
- [New language requests](#language_requests)
|
||||
- [FAQ](./doc/doc_en/FAQ_en.md)
|
||||
- [Community](#Community)
|
||||
- [References](./doc/doc_en/reference_en.md)
|
||||
- [License](#LICENSE)
|
||||
- [Contribution](#CONTRIBUTION)
|
||||
|
||||
***Note: The dynamic graphs branch is still under development.
|
||||
Currently, only dynamic graph training, python-end prediction, and C++ prediction are supported.
|
||||
If you need mobile-end deployment cases or quantitative demo,
|
||||
please use the static graph branch.***
|
||||
|
||||
|
||||
<a name="PP-OCR-Pipeline"></a>
|
||||
|
||||
## PP-OCR Pipeline
|
||||
|
||||
<div align="center">
|
||||
<img src="./doc/ppocr_framework.png" width="800">
|
||||
</div>
|
||||
|
||||
PP-OCR is a practical ultra-lightweight OCR system. It is mainly composed of three parts: DB text detection, detection frame correction and CRNN text recognition. The system adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module. The final results are an ultra-lightweight Chinese and English OCR model with an overall size of 3.5M and a 2.8M English digital OCR model. For more details, please refer to the PP-OCR technical article (https://arxiv.org/abs/2009.09941). Besides, The implementation of the FPGM Pruner and PACT quantization is based on [PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim).
|
||||
|
||||
|
||||
|
||||
## Visualization [more](./doc/doc_en/visualization_en.md)
|
||||
- Chinese OCR model
|
||||
<div align="center">
|
||||
<img src="./doc/imgs_results/1102.jpg" width="800">
|
||||
<img src="./doc/imgs_results/1104.jpg" width="800">
|
||||
<img src="./doc/imgs_results/1106.jpg" width="800">
|
||||
<img src="./doc/imgs_results/1105.jpg" width="800">
|
||||
</div>
|
||||
|
||||
- English OCR model
|
||||
<div align="center">
|
||||
<img src="./doc/imgs_results/img_12.jpg" width="800">
|
||||
</div>
|
||||
|
||||
- Multilingual OCR model
|
||||
<div align="center">
|
||||
<img src="./doc/imgs_results/1110.jpg" width="800">
|
||||
<img src="./doc/imgs_results/1112.jpg" width="800">
|
||||
</div>
|
||||
|
||||
|
||||
<a name="language_requests"></a>
|
||||
## Guideline for new language requests
|
||||
|
||||
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, please refer to [Multilingual OCR Development Plan](https://github.com/PaddlePaddle/PaddleOCR/issues/1048).
|
||||
|
||||
|
||||
<a name="LICENSE"></a>
|
||||
## License
|
||||
This project is released under <a href="https://github.com/PaddlePaddle/PaddleOCR/blob/master/LICENSE">Apache 2.0 license</a>
|
||||
|
||||
<a name="CONTRIBUTION"></a>
|
||||
## Contribution
|
||||
We welcome all the contributions to PaddleOCR and appreciate for your feedback very much.
|
||||
|
||||
- Many thanks to [Khanh Tran](https://github.com/xxxpsyduck) and [Karl Horky](https://github.com/karlhorky) for contributing and revising the English documentation.
|
||||
- Many thanks to [zhangxin](https://github.com/ZhangXinNan) for contributing the new visualize function、add .gitgnore and discard set PYTHONPATH manually.
|
||||
- Many thanks to [lyl120117](https://github.com/lyl120117) for contributing the code for printing the network structure.
|
||||
- Thanks [xiangyubo](https://github.com/xiangyubo) for contributing the handwritten Chinese OCR datasets.
|
||||
- Thanks [authorfu](https://github.com/authorfu) for contributing Android demo and [xiadeye](https://github.com/xiadeye) contributing iOS demo, respectively.
|
||||
- Thanks [BeyondYourself](https://github.com/BeyondYourself) for contributing many great suggestions and simplifying part of the code style.
|
||||
- Thanks [tangmq](https://gitee.com/tangmq) for contributing Dockerized deployment services to PaddleOCR and supporting the rapid release of callable Restful API services.
|
||||
- Thanks [lijinhan](https://github.com/lijinhan) for contributing a new way, i.e., java SpringBoot, to achieve the request for the Hubserving deployment.
|
||||
- Thanks [Mejans](https://github.com/Mejans) for contributing the Occitan corpus and character set.
|
||||
- Thanks [LKKlein](https://github.com/LKKlein) for contributing a new deploying package with the Golang program language.
|
||||
- Thanks [Evezerest](https://github.com/Evezerest), [ninetailskim](https://github.com/ninetailskim), [edencfc](https://github.com/edencfc), [BeyondYourself](https://github.com/BeyondYourself) and [1084667371](https://github.com/1084667371) for contributing a new data annotation tool, i.e., PPOCRLabel。
|
||||
|
|
@ -68,7 +68,6 @@ PaddleOCR提供的可下载模型包括`推理模型`、`训练模型`、`预训
|
|||
|ch_ppocr_mobile_v2.0_cls|原始模型|[cls_mv3.yml](../../configs/cls/cls_mv3.yml)|1.38M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |
|
||||
|
||||
|
||||
## OCR模型列表（V1.1，2020年9月22日更新）
|
||||
|
||||
[1.1系列模型地址](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/models_list.md)
|
||||
## OCR模型列表（V2.0，2020年12月15日更新）
|
||||
|
||||
[2.0系列模型地址](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/models_list.md)
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
# 效果展示
|
||||
|
||||
<a name="通用ppocr_server_1.1效果展示"></a>
|
||||
## 通用ppocr_server_1.1效果展示
|
||||
<a name="通用ppocr_server_2.0效果展示"></a>
|
||||
## 通用ppocr_server_2.0效果展示
|
||||
|
||||
<div align="center">
|
||||
<img src="../imgs_results/1101.jpg" width="800">
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
<a name="Algorithm_introduction"></a>
|
||||
## Algorithm introduction
|
||||
|
||||
This tutorial lists the text detection algorithms and text recognition algorithms supported by PaddleOCR, as well as the models and metrics of each algorithm on **English public datasets**. It is mainly used for algorithm introduction and algorithm performance comparison. For more models on other datasets including Chinese, please refer to [PP-OCR v1.1 models list](./models_list_en.md).
|
||||
This tutorial lists the text detection algorithms and text recognition algorithms supported by PaddleOCR, as well as the models and metrics of each algorithm on **English public datasets**. It is mainly used for algorithm introduction and algorithm performance comparison. For more models on other datasets including Chinese, please refer to [PP-OCR v2.0 models list](./models_list_en.md).
|
||||
|
||||
|
||||
- [1. Text Detection Algorithm](#TEXTDETECTIONALGORITHM)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
## OCR model list（V1.1, updated on 2020.12.12）
|
||||
## OCR model list（V2.0, updated on 2020.12.12）
|
||||
|
||||
- [1. Text Detection Model](#Detection)
|
||||
- [2. Text Recognition Model](#Recognition)
|
||||
|
|
@ -66,6 +66,6 @@ The downloadable models provided by PaddleOCR include `inference model`, `traine
|
|||
|ch_ppocr_mobile_v2.0_cls|Original model|[cls_mv3.yml](../../configs/cls/cls_mv3.yml)|1.38M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |
|
||||
|
||||
|
||||
## OCR model list (V1.1，updated on 2020.9.22)
|
||||
## OCR model list (V2.0，updated on 2020.12.15)
|
||||
|
||||
[1.1 series model address](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/models_list.md)
|
||||
[2.0 series model address](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/models_list.md)
|
||||
|
|
|
|||
Loading…
Reference in New Issue