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YOLO and computer vision for traffic management.CNN & OpenCV

Author: warezcrackfull on 25-04-2024, 02:42, Views: 0

Free Download YOLO and computer vision for traffic management.CNN & OpenCV
Published 4/2024
Created by Sunny Kumar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 12 Lectures ( 1h 53m ) | Size: 1.23 GB

Revolutionising traffic management with YOLO and DeepSort. Detect and track object using YOLOV8. Region based counting.
What you'll learn:
you will explore various tracking algorithms and methodologies integrated with YOLO to enable robust and reliable tracking of objects across frames.
Understand basics of opencv to combine
You will learn about techniques such as Kalman filtering, and deep association learning for tracking objects through occlusions and cluttered environments.
combine deep sort and yolo for object tracking and counting.
count number of vehicle moving on a highway.
Count number of vehicles moving in and out in a multilane highway environment
Use OpenCV to work with Image and Video Files.
Understand the fundamentals of Object Detection and learn how to use YOLO Algorithm to do Object Detection with YOLOv8
Understand concepts of deepsort and yolov8 to distinctly identify vehicles in cluttered environment.
Estimate the movement of Vehicles through generation of heatmap using yolo
Understand how to generate heatmap using yolo and deepsort
Revolutionise traffic management using object tracking and object counting
Understand how to do video analytics using computer vision algorithm.
Understand how openCV can be used to do frame extraction from video
basics steps of how to apply yolo on image and video
region based object counting
Requirements:
Python basics
Description:
Embark on an exhilarating journey into the world of computer vision with our cutting-edge course content featuring YOLO (You Only Look Once) for Object Detection, Vehicle Counting, and Traffic Management. Delve into the heart of real-time detection and classification as you master YOLO, the revolutionary deep learning model renowned for its speed and accuracy in identifying objects within images and video streams.But that's just the beginning. Elevate your skills as you explore the intricate realm of vehicle counting, gaining insights into how advanced algorithms can precisely track and analyze vehicle movements in complex scenarios. Learn how to harness the power of YOLO to not only detect vehicles but also accurately count them, paving the way for enhanced traffic monitoring and management solutions.And that's not all—dive deeper into the realm of traffic management and discover how YOLO can be leveraged to optimize traffic flow, enhance safety measures, and streamline urban mobility. From understanding traffic patterns to implementing intelligent control systems, this course equips you with the knowledge and tools needed to revolutionize transportation infrastructure.Whether you're a seasoned developer looking to expand your expertise or a newcomer eager to dive into the exciting field of computer vision, our course content promises an immersive learning experience that will empower you to unlock the full potential of YOLO for object detection, vehicle counting, and traffic management. Get ready to revolutionize the way we perceive and interact with the world around us
Who this course is for:
students and professionals who are looking to implement realtime object tracking and counting. Implement YOLO for realtime video analytics.
Homepage

https://www.udemy.com/course/yolo-and-computer-vision-for-traffic-managementcnn-opecv/

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