Object Detection with YOLOv9

This project implements real-time object detection using a YOLOv9 model and a live webcam feed.


Github Link!

Overview

It detects objects only within a defined Region of Interest (ROI) instead of the entire frame, improving efficiency and allowing focused detection in specific areas of the scene. The system uses OpenCV for video capture and display and Ultralytics YOLOv9 for deep learning–based object detection.

Technologies

• Python

• OpenCV

• Ultralytics YOLOv9

• Pre-trained YOLOv9 model (yolov9c.pt)

Features

• Real-time detection

• ROI-based processing

• Confidence thresholding

• Live visual feedback