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Muhammad Rizwan Munawar 51026a9a4a
`ultralytics 8.3.54` New Streamlit inference Solution (#18316)
8 months ago
..
5b76bed7d0
[Example] RTDETR-ONNXRuntime-Python (#18369)
8 months ago
51026a9a4a
`ultralytics 8.3.54` New Streamlit inference Solution (#18316)
8 months ago

README.md

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RTDETR - ONNX Runtime

This project implements RTDETR 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 RTDETR implementation using the following command:

python main.py --model rtdetr-l.onnx --img image.jpg --conf-thres 0.5 --iou-thres 0.5

Make sure to replace rtdetr-l.onnx with the path to your RTDETR 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.

Tip!

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