<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/d9ba9e61f13944d794c0ee060379e7ee&quot; frameborder=&quot;0&quot; width=&quot;1280&quot; height=&quot;960&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>960</height><width>1280</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>960</thumbnail_height><thumbnail_width>1280</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/d9ba9e61f13944d794c0ee060379e7ee-00001.gif</thumbnail_url><duration>27.186</duration><title>Vehicle Detection and Traffic Monitoring System</title><description>In this video, I demonstrate a Python program that uses computer vision techniques to detect vehicles in video streams and monitor traffic volume. I also show how we utilized OpenCV for video processing. The program is able to detect vehicles in real-time and includes an alert for high traffic congestion. Watch the video to learn more about this vehicle detection and traffic monitoring system.</description></oembed>