🚘 "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.

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

Real-time multi-camera multi-object tracker using (YOLOv5, YOLOv7,YOLOv8) and StrongSORT with OSNet

The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm

OpenCV implementation of lane and vehicle tracking

This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.

OpenCV 3 & Keras implementation of vehicle tracking with video data.

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

Bus Timetable app React Native

According to YOLOv3 and SORT algorithms, counting multi-type vehicles. Implemented by Pytorch.

A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM).

Collection of papers, code, notebooks, datasets and other resources for Multi Object Tracking (Vehicle tracking, Pedestrian tracking) | Google colab

Realtime transit tracker of Pittsburgh's Port Authority buses using the realtime PAT API using Google Maps to Display the Maps

Real-time Traffic and Pedestrian Counting (YOLOV3 in tensorflow2)

Detect and track vehicles in video

Automatic detection and tracking of moving vehicles in a video from a surveillance camera