YOLO and computer vision for traffic management.CNN & OpenCV

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