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| File Name: | YOLO and computer vision for traffic management.CNN & OpenCV |
| Content Source: | N/A |
| Genre / Category: | Programming |
| File Size : | 1.2 GB |
| Publisher: | N/A |
| Updated and Published: | April 23, 2024 |
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
DOWNLOAD LINK: YOLO and computer vision for traffic management.CNN & OpenCV
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