A simple object detection script using OpenCV and YOLOv8 nano.

Clasificación de imágenes y reconocimiento de objetos mediante la red neuronal convolucional CNN DenseNet y EfficientNet con el modelo frozen model y el framework Coffe. Posteriomente, mediante la red neuronal convolucional CNN MobileNet-SSD y YOLO con el framework TensorFlow

Realtime car traffic tracking using yolov8 model

Tensorflow.js object detection yolov8n coco-Ssd

Identifies 5 native plant species in Alberta using YOLOv8 for object detection, trained on a custom dataset. Features a Gradio demo for real-time plant recognition. Completed as part of my ML diploma.

MESOS: An AI Powered Emergency Notification System Integrated with ERP 2.0

A car counter application that detects, tracks and counts cars crossing a "red" line.

Person detection and movment tracking using YOLOv8

Create a machine-learning algorithm that counts the number of grass-thatch, tin and other roofed houses in aerial (drone) imagery.

The Verifier DApp is an application that generates and trades verified carbon credits, using blockchain technology, IoT, and AI to process images of trees and analyze environmental data, aiding in the quantification of forest biomass and the generation of carbon credits.

Проект для обучения модели по определению рамки автомобильного номера

An interactive app powered by YOLOv8 for object detection on uploaded images, displaying annotated results with prominently highlighted bounding boxes and labels.

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.

This project is part of my master's thesis at the IU International University of Applied Sciences

YOLOv8 implementation to run in a JetsonNano and send detected object bounding boxes through serial port

ML Model to detect License plate of vehicle ( ANPR + EasyOCR + Flask )

Библиотека C# WPF .NET Core 8 для распознавания движения автомобилей на парковке

The project is a Dockerized microservice utilizing YOLO for object detection, managed with Docker Compose. It exposes a REST API for detection tasks, ensuring scalability and ease of deployment. Developed with FastAPI, it accurately detects and reports objects within images, prioritizing code quality, containerization efficiency, and clear document

This repository contains a Python script for object counting using the YOLO (You Only Look Once) object detection model implemented in the ultralytics library along with OpenCV.