Object Detection Project with YOLO11 and OpenCV

This project demonstrates object detection using the YOLO11 model, with the OpenCV library for processing and handling images and videos in real-time.

Requirements

• YOLO11 Model: This project utilizes the YOLO11x model for enhanced accuracy.
• OpenCV Library: The OpenCV library is required for image processing.

Converting YOLO11x.pt to ONNX

To use the YOLO11x model in this project, you need to convert it to ONNX format. This requires Python 3.9.13 and the `ultralytics` library. Use the following script to perform the conversion:

from ultralytics import YOLO
model = YOLO("yolo11x.pt")
model.export(format="onnx")

Licenses

This project uses the following software under the licenses mentioned:

YOLO11

The YOLO11 model is used under the AGPL-3.0 License. The code and pretrained models are provided by Ultralytics. You can find the full license details here.

OpenCV

OpenCV is used under the Apache License 2.0. You can find the full license details here. The official OpenCV repository can be found here.