There are 10 repositories under vehicle-counting topic.
🚀 The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
YOLOv8 Object Tracking using PyTorch, OpenCV and DeepSORT
Vehicle Detection, Tracking and Counting
This project imlements the following tasks in the project: 1. Vehicle counting, 2. Lane detection. 3.Lane change detection and 4.speed estimation
Vehicle Detection Using Deep Learning and YOLO Algorithm
This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.
Vehicle detection, tracking and counting by blob detection with OpenCV on c++.
Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
Vehicle counting using Pytorch
According to YOLOv3 and SORT algorithms, counting multi-type vehicles. Implemented by Pytorch.
A project for counting vehicles using YOLOv4 + DeepSORT + Flask + Ngrok + TF2
detect the no of people every second entering building gate. #person-detection
实时车辆行人交通流计数Real-time Vehicle and Pedestrian Counting (CenterNet)
Vehicle counting in a conjusted traffic road where background subtraction gives lower performance.
YOLOv8 Object Tracking and Counting using PyTorch, OpenCV and DeepSORT, deployed on Streamlit.
Zero-VIRUS: Zero-shot VehIcle Route Understanding System for Intelligent Transportation (CVPR 2020 AI City Challenge Track 1)
A computer vision and artificial intelligence project to detect and counting vehicles. This project is using YOLOV5 and Deep Sort Algorithm to perform object recognition and tracking realtime.
Project on Vehicle Detection, Classification, and Counting. Done in python using OpenCV.
Vehicle detection, tracking, counting and speed prediction on videos with OpenCV.
YoLo is a CNN architecture which specialize in object detection. I am using tutorial from https://www.pyimagesearch.com/2018/11/12/yolo-object-detection-with-opencv/ to develop my own modification. This project aims to count every vehicle(motorcycle, bus, car, cycle, truck) detected in the input image/video.
Building a small demo system to detect and count vehicle using Streamlit framework
Traffic analysis using YOLOv4 and OpenCV
Video/Image processing project using Blob Detection.
Vehicle counter using python opencv and dlib
The goal of the project is to classify the vehicles, count their frequency, track them using unique ID and provide safety measures to the users by flagging the suspicious ones.
Proyecto de control de trafico e intercepción de semáforos inteligentes.
OpenCv based live vechicle counting system written in C.
Advanced Vehicle Tracking and Detection System using ByteTrack, Supervision, and YOLO Algorithms
This repository contains the code for an IoT Traffic Surveillance System using a fog-computing architecture. The system uses an adaptive video encoding algorithm that switches the video encoding at specific intervals to reduce the required network bandwidth.
Vehicle Tracking and Counting using Yolo and ByteTrack
EC463 Senior Design Miniproject: Raspberry Pi video processing
Vehicle counting by density map regression