This project aims to detect vehicles and read license plates from video footage. It leverages YOLOv8 for object detection and the SORT algorithm for tracking vehicles across frames. The detected license plates are then processed using EasyOCR to extract the text, with a focus on Indian license plate formats.

Multiple Computer Vision Project using OpenCV

This repository contains an object detection tutorial to detect swimming pools and cars using YOLOv4-tiny with satellite imagery. The project includes training scripts, dataset configurations, and instructions for running the model on Google Colab.

In this project, we compared different YOLO models by training them on drone images from the Unifesp parking lot to detect cars. Our objective was to assess their performance and identify the most effective model for improving traffic flow and optimizing parking space utilization.

This project utilizes the custom object detection model to monitor parking spaces in a video feed. It identifies vehicles in the video and overlays polygons representing parking spaces on the frames. The program then calculates the number of occupied and free parking spaces based on the detected vehicles and the predefined parking space polygons.

🚙 This project merges YOLOv8l for precise car detection with SORT for streamlined car tracking, offering a comprehensive tool for real-time vehicle counting in designated areas.

Detect empty parking spaces using a custom YOLOv8 model trained on a specialized dataset, with image manipulation handled by OpenCV.

This repository contains a car detection and tracking software implemented using YOLOv8 for object recognition and classification, along with DeepSORT for tracking. The model is capable of detecting cars, buses, trucks, and trains in real-time video streams. This model combines state-of-the-art object detection and tracking techniques.

Training and evaluating YOLOv8 models on a car-object detection dataset. The project is built using the Ultralytics YOLOv8 library and integrates with WandB for experiment tracking.

Car Detection with YoloV5 for Computer Vision Course

detecting model and the name of the cars with deep neural networks like VGG-16 , YOLOv5 and YOLOv8

AI-Driven car announcement helper

CNN-based real-time car parking lot classification

Car Detection using Haar's Cascade Classifier

YOLOPv2のPythonでのONNX推論サンプル

This application is designed using Flutter and Dart. This application will ask the user i.e., traffic police to choose any one out of these given options. It will represent information regarding vehicles which either have crossed the zebra crossing or not, at the traffic signal.

detecting license plates and cars in a video using YOLO NAS and YOLOv5

This is one of the best vehicle recognition applications. It can determine the car's license plate number, color, model, brand and year.

使用OpenCV部署HybridNets，同时处理车辆检测、可驾驶区域分割、车道线分割，三项视觉感知任务，包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行， 彻底摆脱对任何深度学习框架的依赖。

LiDAR를 활용한 객체 탐지 프로젝트