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FeiYull/TensorRT-Alpha

C++

🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎

yolov8yolov7cudalibfacedetectiontensorrtu2netyoloryolov3yolov4yolov5yolov6yolox
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README

TensorRT-Alpha

Cuda

English | 简体中文


可视化



介绍

本仓库提供深度学习CV领域模型加速部署案例，仓库实现的cuda c支持多batch图像预处理、推理、decode、NMS。大部分模型转换流程为：torch->onnx->tensorrt。 获取onnx文件以下有两种方式：

pth -> trt coming soon.
pth -> onnx -> trt:
  • [i]. 本仓库提供的网盘直接下载onnx。weiyun or google driver
  • [ii]. 按照本仓库提供的指令，手动从相关源代码框架导出onnx。

更新

  • 2023.01.01 🔥 更新 yolov3, yolov4, yolov5, yolov6
  • 2023.01.04 🍅 更新 yolov7, yolox, yolor
  • 2023.01.05 🎉 更新 u2net, libfacedetection
  • 2023.01.08 🚀 全网最快支持yolov8的tensorrt部署
  • 2023.01.20 🍏 更新 efficientdet, pphunmanseg
  • 2023.12.09 🍁 更新 yolov8-pose
  • 2023.12.19 🍉 更新 yolov8-seg
  • 2023.12.27 💖 更新 yolonas

安装

兼容平台: Windows and Linux. 以下环境已被测过：

Ubuntu18.04
  • cuda11.3
  • cudnn8.2.0
  • gcc7.5.0
  • tensorrt8.4.2.4
  • opencv3.x or 4.x
  • cmake3.10.2
Windows10
  • cuda11.3
  • cudnn8.2.0
  • visual studio 2017 or 2019 or 2022
  • tensorrt8.4.2.4
  • opencv3.x or 4.x
创建Python环境(可选）
# install miniconda first
conda create -n tensorrt-alpha python==3.8 -y
conda activate tensorrt-alpha
git clone https://github.com/FeiYull/tensorrt-alpha
cd tensorrt-alpha
pip install -r requirements.txt

安装教程：

快速开始

Ubuntu18.04

设置TensorRT根目录（安装目录）路径:

git clone https://github.com/FeiYull/tensorrt-alpha
cd tensorrt-alpha/cmake
vim common.cmake
# 把common.cmake文件第20行中的TensorRT_ROOT修改成您的TensorRT安装目录, 例如改成如下:
# set(TensorRT_ROOT /home/feiyull/TensorRT-8.4.2.4)

开始编译、运行工程，例如:yolov8

模型

目前已实现30多个主流模型，部分整理好的onnx文件如下列表：

🍉稍后在tesla v100 和 A100上测量时间开销!现在看看yolov8n在移动端RTX2070m(8G)的性能表现：

模型 视频分辨率 模型输入尺寸 显存占用 GPU利用率
yolov8n 1920x1080 8x3x640x640 1093MiB/7982MiB 14%
无法显示图片时显示的文字
一个batch内，平均每一帧的时间开销

严格的精度对齐，官方效果 vs TensorRT-Alpha:


无法显示图片时显示的文字
yolov8n : Offical( left ) vs Ours( right )

无法显示图片时显示的文字
yolov7-tiny : Offical( left ) vs Ours( right )

无法显示图片时显示的文字
yolov6s : Offical( left ) vs Ours( right )

无法显示图片时显示的文字
yolov5s : Offical( left ) vs Ours( right )

无法显示图片时显示的文字
yolov5s : Offical( left ) vs Ours( right )

无法显示图片时显示的文字
libfacedetection : Offical( left ) vs Ours( right topK:2000)

Citation

@misc{FeiYull_TensorRT-Alpha,  
  author = {FeiYull},  
  title = {TensorRT-Alpha},  
  year = {2023},  
  publisher = {GitHub},  
  journal = {GitHub repository},  
  howpublished = {https://github.com/FeiYull/tensorrt-alpha}
}
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