detecting model and the name of the cars with deep neural networks like VGG-16 , YOLOv5 and YOLOv8 This project tries to detect a car name and its model in an image or a video. VGG-16 uses tensorflow object detection model to detect cars and from the detections in each frame each vehicle can be tracked across a video. YOLOV5s and YOLOv8s uses pythorch. the focus of this project is on YOLOv5s. this algorithm trained on a dataset contains of 2100 images of 5 classes. you can use the dataset provided for this project.It's availabel on roboflow platform.

The project created in python by using tensorflow so you must be familiar with tensorflow and basic object detection and you must also know basic maths for understanding the tracking algorithm. You must be also familiar with Deep neural networks and how it works.If you already know about these fields, you can go to the next phase ;).

Python packages to be installed: Tensorflow (Tensorflow-gpu if you have Nvidia GPU), openCV, imutils, Pillow, numpy, urllib, matplotlib

The results of trianed model:

YOLOv5s:

YOLOv5s vs VGG16 vs YOLOv8s:

hope you enjoy this project, also don't forget that give me a star, thanks in advance ;)