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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> |
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README.md | [Example] YOLOv8-ONNXRuntime (#2992) | 2 years ago |
main.py | `ultralytics 8.0.136` refactor and simplify package (#3748) | 1 year ago |
README.md
YOLOv8 - ONNX Runtime
This project implements YOLOv8 using ONNX Runtime.
Installation
To run this project, you need to install the required dependencies. The following instructions will guide you through the installation process.
Installing Required Dependencies
You can install the required dependencies by running the following command:
pip install -r requirements.txt
Installing onnxruntime-gpu
If you have an NVIDIA GPU and want to leverage GPU acceleration, you can install the onnxruntime-gpu package using the following command:
pip install onnxruntime-gpu
Note: Make sure you have the appropriate GPU drivers installed on your system.
Installing onnxruntime
(CPU version)
If you don't have an NVIDIA GPU or prefer to use the CPU version of onnxruntime, you can install the onnxruntime package using the following command:
pip install onnxruntime
Usage
After successfully installing the required packages, you can run the YOLOv8 implementation using the following command:
python main.py --model yolov8n.onnx --img image.jpg --conf-thres 0.5 --iou-thres 0.5
Make sure to replace yolov8n.onnx with the path to your YOLOv8 ONNX model file, image.jpg with the path to your input image, and adjust the confidence threshold (conf-thres) and IoU threshold (iou-thres) values as needed.