<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Yolov8 on Antonio Montemurro</title><link>https://antoniomontemurro.com/en/tags/yolov8/</link><description>Recent content in Yolov8 on Antonio Montemurro</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 26 Jul 2025 11:22:11 +0000</lastBuildDate><atom:link href="https://antoniomontemurro.com/en/tags/yolov8/index.xml" rel="self" type="application/rss+xml"/><item><title>Detecting and Counting People with YOLOv8</title><link>https://antoniomontemurro.com/en/posts/yolo-opencv-python-count-people/</link><pubDate>Sat, 26 Jul 2025 11:22:11 +0000</pubDate><guid>https://antoniomontemurro.com/en/posts/yolo-opencv-python-count-people/</guid><description>&lt;p&gt;In this article, you’ll discover what YOLO is and how to use it to analyze a video and detect and count people within it.&lt;br&gt;
We’ll walk through a simple Python script that lets you configure basic parameters and choose the most appropriate video source for your needs.&lt;/p&gt;
&lt;h3 id="what-is-yolo"&gt;What is YOLO?&lt;/h3&gt;
&lt;p&gt;YOLO (You Only Look Once) is a &lt;strong&gt;real-time object detection&lt;/strong&gt; algorithm based on neural networks.&lt;br&gt;
Put simply, YOLO analyzes each video frame (whether from a file or a webcam/IP stream) to identify objects such as people, vehicles, animals, and more.&lt;/p&gt;</description></item></channel></rss>