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README
Apache-2.0

简体中文 | English

🌈简介

PaddleDetection是一个基于PaddlePaddle的目标检测端到端开发套件,在提供丰富的模型组件和测试基准的同时,注重端到端的产业落地应用,通过打造产业级特色模型|工具、建设产业应用范例等手段,帮助开发者实现数据准备、模型选型、模型训练、模型部署的全流程打通,快速进行落地应用。

主要模型效果示例如下(点击标题可快速跳转):

通用目标检测 小目标检测 旋转框检测 3D目标物检测
人脸检测 2D关键点检测 多目标追踪 实例分割
车辆分析——车牌识别 车辆分析——车流统计 车辆分析——违章检测 车辆分析——属性分析
行人分析——闯入分析 行人分析——行为分析 行人分析——属性分析 行人分析——人流统计

同时,PaddleDetection提供了模型的在线体验功能,用户可以选择自己的数据进行在线推理。

说明:考虑到服务器负载压力,在线推理均为CPU推理,完整的模型开发实例以及产业部署实践代码示例请前往🎗️产业特色模型|产业工具

传送门模型在线体验

✨主要特性

🧩模块化设计

PaddleDetection将检测模型解耦成不同的模块组件,通过自定义模块组件组合,用户可以便捷高效地完成检测模型的搭建。传送门🧩模块组件

📱丰富的模型库

PaddleDetection支持大量的最新主流的算法基准以及预训练模型,涵盖2D/3D目标检测、实例分割、人脸检测、关键点检测、多目标跟踪、半监督学习等方向。传送门📱模型库⚖️模型性能对比

🎗️产业特色模型|产业工具

PaddleDetection打造产业级特色模型以及分析工具:PP-YOLOE+、PP-PicoDet、PP-TinyPose、PP-HumanV2、PP-Vehicle等,针对通用、高频垂类应用场景提供深度优化解决方案以及高度集成的分析工具,降低开发者的试错、选择成本,针对业务场景快速应用落地。传送门🎗️产业特色模型|产业工具

💡🏆产业级部署实践

PaddleDetection整理工业、农业、林业、交通、医疗、金融、能源电力等AI应用范例,打通数据标注-模型训练-模型调优-预测部署全流程,持续降低目标检测技术产业落地门槛。传送门💡产业实践范例🏆企业应用案例

📣最新进展

💎稳定版本

位于release/2.5分支,最新的v2.5版本已经在 2022.09.13 发布,版本发新详细内容请参考v2.5.0更新日志,重点更新:

  • 🎗️产业特色模型|产业工具
    • 发布PP-YOLOE+,最高精度提升2.4% mAP,达到54.9% mAP,模型训练收敛速度提升3.75倍,端到端预测速度最高提升2.3倍;多个下游任务泛化性提升
    • 发布PicoDet-NPU模型,支持模型全量化部署;新增PicoDet版面分析模型
    • 发布PP-TinyPose升级版增强版,在健身、舞蹈等场景精度提升9.1% AP,支持侧身、卧躺、跳跃、高抬腿等非常规动作
    • 发布行人分析工具PP-Human v2,新增打架、打电话、抽烟、闯入四大行为识别,底层算法性能升级,覆盖行人检测、跟踪、属性三类核心算法能力,提供保姆级全流程开发及模型优化策略,支持在线视频流输入
    • 首次发布PP-Vehicle,提供车牌识别、车辆属性分析(颜色、车型)、车流量统计以及违章检测四大功能,兼容图片、在线视频流、视频输入,提供完善的二次开发文档教程
  • 📱模型库
    • 全面覆盖的YOLO家族经典与最新算法模型的代码库PaddleYOLO: 包括YOLOv3,百度飞桨自研的实时高精度目标检测模型PP-YOLOE,以及前沿检测算法YOLOv4、YOLOv5、YOLOX,YOLOv6及YOLOv7
    • 新增基于ViT骨干网络高精度检测模型,COCO数据集精度达到55.7% mAP;新增OC-SORT多目标跟踪模型;新增ConvNeXt骨干网络
  • 💡产业实践范例

🧬预览版本

位于develop分支,体验最新功能请切换到该分支,最近更新:

  • 📱模型库
  • 🎗️产业特色模型|产业工具
    • 发布旋转框检测模型PP-YOLOE-R:Anchor-free旋转框检测SOTA模型,精度速度双高、云边一体,s/m/l/x四个模型适配不用算力硬件、部署友好,避免使用特殊算子,能够轻松使用TensorRT加速;
    • 发布小目标检测模型PP-YOLOE-SOD:基于切图的端到端检测方案、基于原图的检测模型,精度达VisDrone开源最优;

👫开源社区

  • 📑项目合作: 如果您是企业开发者且有明确的目标检测垂类应用需求,请扫描如下二维码入群,并联系群管理员AI后可免费与官方团队展开不同层次的合作。
  • 🏅️社区贡献: PaddleDetection非常欢迎你加入到飞桨社区的开源建设中,参与贡献方式可以参考开源项目开发指南
  • 💻直播教程: PaddleDetection会定期在飞桨直播间(B站:飞桨PaddlePaddle微信: 飞桨PaddlePaddle),针对发新内容、以及产业范例、使用教程等进行直播分享。
  • 🎁加入社区: 微信扫描二维码并填写问卷之后,加入交流群领取20G重磅目标检测学习大礼包,包括:
    • 往期直播录播&PPT
    • 30+行人车辆等垂类高性能预训练模型
    • 七大任务开源数据集下载链接汇总
    • 40+前沿检测领域顶会算法
    • 15+从零上手目标检测理论与实践视频课程
    • 10+工业安防交通全流程项目实操(含源码)

PaddleDetection官方交流群二维码

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简介

PaddleDetection的目的是为工业界和学术界提供丰富、易用的目标检测模型 展开 收起
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