## 简介 PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力使用者训练出更好的模型，并应用落地。 ## 特性 - 超轻量级中文OCR，总模型仅8.6M - 单模型支持中英文数字组合识别、竖排文本识别、长文本识别 - 检测模型DB（4.1M）+识别模型CRNN（4.5M） - 多种文本检测训练算法，EAST、DB - 多种文本识别训练算法，Rosetta、CRNN、STAR-Net、RARE ## **超轻量级中文OCR体验** ![](./doc/imgs_draw/11.jpg) 上图是超轻量级中文OCR模型效果展示，更多效果图请见文末。 #### 1.运行环境配置 前请先参考[快速安装](./doc/installation.md)配置PaddleOCR运行环境。 #### 2.模型下载 ``` # 创建模型保存目录 mkdir inference && cd inference && mkdir det && mkdir rec # 下载inference模型文件包 wget -P ./inference https://paddleocr.bj.bcebos.com/inference.tar # inference模型文件包解压 tar -xf ./inference/inference.tar ``` #### 3.单张图像或者图像集合预测 实现文本检测、识别串联推理，在执行预测时，需要通过参数image_dir指定单张图像或者图像集合的路径、参数det_model_dir指定检测inference模型的路径和参数rec_model_dir指定识别inference模型的路径。 ``` # 设置PYTHONPATH环境变量 export PYTHONPATH=. # 预测image_dir指定的单张图像 python tools/infer/predict_system.py --image_dir="/Demo.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/" # 预测image_dir指定的图像集合 python tools/infer/predict_system.py --image_dir="/test_imgs/" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/" ``` 更多的文本检测、识别串联推理使用方式请参考文档教程中[基于推理引擎预测](./doc/inference.md)。 ## 文档教程 - [快速安装](./doc/installation.md) - [文本检测模型训练/评估/预测](./doc/detection.md) - [文本识别模型训练/评估/预测](./doc/recognition.md) - [基于推理引擎预测](./doc/inference.md) ## 文本检测算法 PaddleOCR开源的文本检测算法列表： - [x] [EAST](https://arxiv.org/abs/1704.03155) - [x] [DB](https://arxiv.org/abs/1911.08947) - [ ] [SAST](https://arxiv.org/abs/1908.05498)(百度自研, comming soon) 在ICDAR2015文本检测公开数据集上，算法效果如下： |模型|骨干网络|Hmean| |-|-|-| |[EAST](https://paddleocr.bj.bcebos.com/det_r50_vd_east.tar)|ResNet50_vd|85.85%| |[EAST](https://paddleocr.bj.bcebos.com/det_mv3_east.tar)|MobileNetV3|79.08%| |[DB](https://paddleocr.bj.bcebos.com/det_r50_vd_db.tar)|ResNet50_vd|83.30%| |[DB](https://paddleocr.bj.bcebos.com/det_mv3_db.tar)|MobileNetV3|73.00%| PaddleOCR文本检测算法的训练和使用请参考文档教程中[文本检测模型训练/评估/预测](./doc/detection.md)。 ## 文本识别算法 PaddleOCR开源的文本识别算法列表： - [x] [CRNN](https://arxiv.org/abs/1507.05717) - [x] [Rosetta](https://arxiv.org/abs/1910.05085) - [x] [STAR-Net](http://www.bmva.org/bmvc/2016/papers/paper043/index.html) - [x] [RARE](https://arxiv.org/abs/1603.03915v1) - [ ] [SRN]((https://arxiv.org/abs/2003.12294))(百度自研, comming soon) 参考[DTRB](https://arxiv.org/abs/1904.01906)文字识别训练和评估流程，使用MJSynth和SynthText两个文字识别合成数据集训练，在IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE数据集上进行效果评估，算法效果如下： |模型|骨干网络|ACC| |-|-|-| |[Rosetta](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_none_ctc.tar)|Resnet34_vd|80.24%| |[Rosetta](https://paddleocr.bj.bcebos.com/rec_mv3_none_none_ctc.tar)|MobileNetV3|78.16%| |[CRNN](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_bilstm_ctc.tar)|Resnet34_vd|82.20%| |[CRNN](https://paddleocr.bj.bcebos.com/rec_mv3_none_bilstm_ctc.tar)|MobileNetV3|79.37%| |[STAR-Net](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_ctc.tar)|Resnet34_vd|83.93%| |[STAR-Net](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_ctc.tar)|MobileNetV3|81.56%| |[RARE](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_attn.tar)|Resnet34_vd|84.90%| |[RARE](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_attn.tar)|MobileNetV3|83.32%| PaddleOCR文本识别算法的训练和使用请参考文档教程中[文本识别模型训练/评估/预测](./doc/recognition.md)。 ## 端到端OCR算法 - [ ] [End2End-PSL](https://arxiv.org/abs/1909.07808)(百度自研, comming soon) ## 效果展示 ![](./doc/imgs_draw/1.jpg) ![](./doc/imgs_draw/4.jpg) ![](./doc/imgs_draw/6.jpg) ![](./doc/imgs_draw/7.jpg) ![](./doc/imgs_draw/9.jpg) ![](./doc/imgs_draw/12.jpg) ![](./doc/imgs_draw/16.jpg) ![](./doc/imgs_draw/22.jpg) ## 参考文献 ``` 1. EAST: @inproceedings{zhou2017east, title={EAST: an efficient and accurate scene text detector}, author={Zhou, Xinyu and Yao, Cong and Wen, He and Wang, Yuzhi and Zhou, Shuchang and He, Weiran and Liang, Jiajun}, booktitle={Proceedings of the IEEE conference on Computer Vision and Pattern Recognition}, pages={5551--5560}, year={2017} } 2. DB: @article{liao2019real, title={Real-time Scene Text Detection with Differentiable Binarization}, author={Liao, Minghui and Wan, Zhaoyi and Yao, Cong and Chen, Kai and Bai, Xiang}, journal={arXiv preprint arXiv:1911.08947}, year={2019} } 3. DTRB: @inproceedings{baek2019wrong, title={What is wrong with scene text recognition model comparisons? dataset and model analysis}, author={Baek, Jeonghun and Kim, Geewook and Lee, Junyeop and Park, Sungrae and Han, Dongyoon and Yun, Sangdoo and Oh, Seong Joon and Lee, Hwalsuk}, booktitle={Proceedings of the IEEE International Conference on Computer Vision}, pages={4715--4723}, year={2019} } 4. SAST: @inproceedings{wang2019single, title={A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning}, author={Wang, Pengfei and Zhang, Chengquan and Qi, Fei and Huang, Zuming and En, Mengyi and Han, Junyu and Liu, Jingtuo and Ding, Errui and Shi, Guangming}, booktitle={Proceedings of the 27th ACM International Conference on Multimedia}, pages={1277--1285}, year={2019} } 5. SRN: @article{yu2020towards, title={Towards Accurate Scene Text Recognition with Semantic Reasoning Networks}, author={Yu, Deli and Li, Xuan and Zhang, Chengquan and Han, Junyu and Liu, Jingtuo and Ding, Errui}, journal={arXiv preprint arXiv:2003.12294}, year={2020} } 6. end2end-psl: @inproceedings{sun2019chinese, title={Chinese Street View Text: Large-scale Chinese Text Reading with Partially Supervised Learning}, author={Sun, Yipeng and Liu, Jiaming and Liu, Wei and Han, Junyu and Ding, Errui and Liu, Jingtuo}, booktitle={Proceedings of the IEEE International Conference on Computer Vision}, pages={9086--9095}, year={2019} } ``` ## 许可证书 本项目的发布受Apache 2.0 license许可认证。 ## 版本更新 ## 如何贡献代码 我们非常欢迎你为PaddleOCR贡献代码，也十分感谢你的反馈。