π "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
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Updated
Sep 11, 2021 - Python
π "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
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
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 counting using Pytorch
According to YOLOv3 and SORT algorithms, counting multi-type vehicles. Implemented by Pytorch.
Real-time Traffic and Pedestrian Counting (YOLOV3 in tensorflow2)
Car tracking and car counter implemented with YOLOX, ByteTrack and Pytorch.
π Pandora Car Alarm (and Telemetry) System / ΠΠ²ΡΠΎΡΠΈΠ³Π½Π°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈ ΡΠ΅Π»Π΅ΠΌΠ΅ΡΡΠΈΡ Pandora (ΡΠ°ΠΊΠΆΠ΅ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΈΠ²Π°Π΅ΡΡΡ BENISH Guard)
Implementation of the Automatic Emergency Braking System using deep learning.
Modified TensorFlow Object Detection Model for vehicle detection and tracking
Vehicle MTMC Tracking
Implementation of a few prevelant computer vision techniques using Python
Vehicle detection and tracking and speed estimation using opencv
Vehicle detection, tracking, counting and speed prediction on videos with OpenCV.
π VehicleDetectionTracker: Real-time vehicle detection and tracking powered by YOLO. ππ Enhance your computer vision projects with speed, precision, and adaptability.
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.
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