# TrackTrt **Repository Path**: segmentfault/track-trt ## Basic Information - **Project Name**: TrackTrt - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-04-04 - **Last Updated**: 2025-04-10 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Track-trt ![Language](https://img.shields.io/badge/language-c++-brightgreen) ![Language](https://img.shields.io/badge/CUDA-12.1-brightgreen) ![Language](https://img.shields.io/badge/TensorRT-8.6.1.6-brightgreen) ![Language](https://img.shields.io/badge/OpenCV-4.5.5-brightgreen) ![Language](https://img.shields.io/badge/ubuntu-20.04-brightorigin) ## Introduction 基于 TensorRT 的 C++ 高性能 单目标跟踪 推理,支持单目标跟踪算法 OSTrack、LightTrack。 其中 OSTrack 为ViT模型,适用于服务端计算设备,LightTrack 为NAS搜索出来的轻量CNN架构,适用于边缘端计算设备。请按需使用。 更多 TensorRT 部署模型,请移步仓库 [github](https://github.com/l-sf/Linfer) ## Project Build and Run 1. install cuda/tensorrt/opencv [reference](https://github.com/l-sf/Notes/blob/main/notes/Ubuntu20.04_install_tutorials.md#%E4%BA%94cuda--cudnn--tensorrt-install) 2. compile engine 1. 下载onnx模型 [google driver](https://drive.google.com/drive/folders/16ZqDaxlWm1aDXQsjsxLS7yFL0YqzHbxT?usp=sharing) 或者 跟踪教程自己导出 2. ```bash cd Track-trt/workspace bash compile_engine.sh ``` 3. build ```bash # 修改CMakeLists.txt中 cuda/tensorrt/opencv 为自己的路径 cd Track-trt mkdir build && cd build cmake .. && make -j4 ``` 4. run 视频文件输入: ```bash cd Track-trt/workspace ./pro 0 "bag.avi" ``` 摄像头输入: ```bash cd Track-trt/workspace ./pro 1 0 ``` 图片序列输入: ```bash cd Track-trt/workspace ./pro 2 "Woman/img/%04d.jpg" ``` ## Speed Test 在 Jetson Orin Nano 8G 上进行测试,包括整个流程(即预处理+推理+后处理) | Method | Precision | Resolution | Average Latency | | :--------: | :-------: | :--------: | :-------------: | | LightTrack | fp16 | 256x256 | 10ms | | OSTrack | fp16 | 256x256 | 30ms | ## onnx导出 [LightTrack](./lighttrack/README.md) [OSTrack](./ostrack/README.md) ## Reference [tensorRT_Pro](https://github.com/shouxieai/tensorRT_Pro.git)