[Example] YOLOv8-ONNXRuntime (#2992)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>

examples/YOLOv8-ONNXRuntime/README.md

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+# 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:
+
+```bash
+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:
+
+```bash
+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:
+
+```bash
+pip install onnxruntime
+```
+
+### Usage
+
+After successfully installing the required packages, you can run the YOLOv8 implementation using the following command:
+
+```bash
+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.