emptysoal/TensorRT-YOLOv8
Based on tensorrt v8.0+, deploy detect, pose, segment, tracking of YOLOv8 with C++ and python api.
This project helps developers integrate high-performance computer vision tasks like object detection, pose estimation, instance segmentation, and object tracking into their applications. It takes pre-trained YOLOv8 models and optimizes them for faster execution using TensorRT, providing a C++ API for maximum speed and a Python API for ease of use. This is ideal for developers building vision-powered systems on edge devices like Jetson or Linux servers.
141 stars.
Use this if you are a software developer needing to deploy YOLOv8 models for real-time object detection, pose estimation, instance segmentation, or tracking with high inference speed on NVIDIA GPUs.
Not ideal if you are an end-user without programming experience or if you need to train YOLOv8 models, as this project focuses on deployment rather than training.
Stars
141
Forks
27
Language
C++
License
MIT
Category
Last pushed
Oct 24, 2025
Commits (30d)
0
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