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🚀 TensorRT-YOLO: Support YOLOv3, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, PP-YOLOE using TensorRT acceleration with EfficientNMS!

Home Page: https://github.com/laugh12321/TensorRT-YOLO

License: GNU General Public License v3.0

C++ 32.33% Python 57.21% Lua 1.33% Cuda 4.31% CMake 3.30% Dockerfile 1.52%

tensorrt-yolo's Introduction

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🚀 TensorRT YOLO

GitHub License GitHub Release GitHub commit activity GitHub Repo stars GitHub forks

TensorRT-YOLO 是一个支持 YOLOv3、YOLOv5、YOLOv6、YOLOv7、YOLOv8、YOLOv9、YOLOv10、PP-YOLOE 和 PP-YOLOE+ 的推理加速项目,使用 NVIDIA TensorRT 进行优化。项目不仅集成了 EfficientNMS TensorRT 插件以增强后处理效果,还使用了 CUDA 核函数来加速前处理过程。TensorRT-YOLO 提供了 C++ 和 Python 推理的支持,旨在提供快速而优化的目标检测解决方案。

✨ 主要特性

  • 支持 YOLOv3、YOLOv5、YOLOv6、YOLOv7、YOLOv8、YOLOv9、YOLOv10、PP-YOLOE 和 PP-YOLOE+
  • 支持 ONNX 静态、动态导出以及 TensorRT 推理
  • 集成 EfficientNMS TensorRT 插件加速后处理
  • 利用 CUDA 核函数加速前处理
  • 支持 C++ 和 Python 推理
  • CLI 快速导出与推理
  • Docker 一键部署

🛠️ 环境要求

  • 推荐 CUDA 版本 >= 11.6
  • 推荐 TensorRT 版本 >= 8.6

📦 使用教程

📺 BiliBili

📄 许可证

TensorRT-YOLO采用 GPL-3.0许可证,这个OSI 批准的开源许可证非常适合学生和爱好者,可以推动开放的协作和知识分享。请查看LICENSE 文件以了解更多细节。

感谢您选择使用 TensorRT-YOLO,我们鼓励开放的协作和知识分享,同时也希望您遵守开源许可的相关规定。

📞 联系方式

对于 TensorRT-YOLO 的错误报告和功能请求,请访问 GitHub Issues

tensorrt-yolo's People

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