Awesome OCR toolkits based on PaddlePaddle(8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embedded and IoT devices)
Project description
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简介
PaddleOCR 旨在打造一套丰富、领先、且实用的 OCR 工具库,助力开发者训练出更好的模型,并应用落地。
🚀 社区
PaddleOCR 由 PMC 监督。Issues 和 PRs 将在尽力的基础上进行审查。欲了解 PaddlePaddle 社区的完整概况,请访问 community。
⚠️注意:Issues模块仅用来报告程序🐞Bug,其余提问请移步Discussions模块提问。如所提Issue不是Bug,会被移到Discussions模块,敬请谅解。
📣 近期更新(more)
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🔥🔥《PaddleOCR 2.9 发布,正式开源文本图像智能分析利器》,文本图像版面解析实现高精度实时预测,低代码全流程开发加速产业应用。集成文本图像矫正、版面区域检测、常规文本检测、印章文本检测、文本识别、表格识别等多功能。6条模型产线一键调用,显著降低开发成本。支持高性能推理、服务化部署和端侧部署等多种部署方式。10月24日(周四)19:00直播为您深度解析最新升级亮点。 报名链接
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🔥2024.10.1 添加OCR领域低代码全流程开发能力:
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飞桨低代码开发工具PaddleX,依托于PaddleOCR的先进技术,支持了OCR领域的低代码全流程开发能力:
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支持文档场景信息抽取v3PP-ChatOCRv3-doc、基于RT-DETR的高精度版面区域检测模型和PicoDet的高效率版面区域检测模型、高精度表格结构识别模型SLANet_Plus、文本图像矫正模型UVDoc、公式识别模型LatexOCR、基于PP-LCNet的文档图像方向分类模型
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🔥2024.7 添加 PaddleOCR 算法模型挑战赛冠军方案:
- 赛题一:OCR 端到端识别任务冠军方案——场景文本识别算法-SVTRv2;
- 赛题二:通用表格识别任务冠军方案——表格识别算法-SLANet-LCNetV2。
🌟 特性
支持多种 OCR 相关前沿算法,在此基础上打造产业级特色模型PP-OCR、PP-Structure和PP-ChatOCR,并打通数据生产、模型训练、压缩、预测部署全流程。
⚡ 快速开始
🔥 低代码全流程开发
📝 文档
完整文档请移步:docs
📚《动手学 OCR》电子书
🎖 贡献者
⭐️ Star
许可证书
本项目的发布受 Apache License Version 2.0 许可认证。
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