Vehicle counting in a conjusted traffic road where background subtraction gives lower performance.
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Updated
Jul 12, 2019 - Python
Vehicle counting in a conjusted traffic road where background subtraction gives lower performance.
Detecting and counting cars on the video
Real-time Traffic and Pedestrian Counting (YOLOV3 in tensorflow2)
实时车辆行人交通流计数Real-time Vehicle and Pedestrian Counting (CenterNet)
This project imlements the following tasks in the project: 1. Vehicle counting, 2. Lane detection. 3.Lane change detection and 4.speed estimation
This project utilizes PyQt5, YOLOv8, and TensorFlow for vehicle detection and identification, including speed monitoring and fine issuance. It features a user-friendly interface and contributes to traffic discipline through automated enforcement.
Vehicle Detection Using Deep Learning and YOLO Algorithm
Here is a source code for car counting using YOLOv8n model. It is a basic example of computer vision and object detection task.
A car-counting system using background subtraction on a video feed. It makes use of OpenCV API.
The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
This app detects types of cars and counts cars using YOLOv3
Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.
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