Detecting traffic using OpenCV and YOLO and tracking the vehicles for counting using Sort
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Updated
Dec 5, 2020 - Python
Detecting traffic using OpenCV and YOLO and tracking the vehicles for counting using Sort
Discover the future of urban mobility with the City Sense which is a UIT Data Science Traffic Application for Smart Cities. Our cutting-edge solution revolutionizes the way cities manage traffic, enhancing the quality of life for residents and fostering sustainable urban development.
Successfully developed an object detection model using Faster R-CNN to detect vehicles and traffic-related objects in real-time road scenes, supporting smart traffic monitoring and surveillance applications.
This project demonstrates a simple yet powerful application of the YOLOv8 (You Only Look Once) object detection model for identifying various traffic-related objects.
Training detection models (RetinaNet and SSD) to detect road objects, then applying a model to real world traffic video from Moscow.
Deteção de veiculos, tracking de veículo e estimador de velocidade
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