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YOLO and computer vision for traffic management.CNN & OpenCV https://hhmaps.vn/forum/viewtopic.php?f=9&t=10889 |
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Người gửi: | lovewarez [ Thứ 3 23/04/24 10:26 ] |
Tiêu đề bài viết: | YOLO and computer vision for traffic management.CNN & OpenCV |
[center] 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[/center] 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 Mã: https://www.udemy.com/course/yolo-and-computer-vision-for-traffic-managementcnn-opecv/ Mã: https://rapidgator.net/folder/7590733/YOLOandcomputervision.html
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