Animal Detection and Classification using YOLO

An online examination monitoring system employing YOLOv8, along with various other deep learning and machine learning approaches, centered around computer vision.

SnapnCook is an AI-powered web app that helps you cook smarter, not harder. Simply upload a photo of your fridge or ingredients, and the app instantly suggests delicious recipes based on what it sees, no typing required!

Implementation of YOLOv8 for detection of Baybayin characters, an ancient script from the Philippines.

Apple Detection (Fresh / Stale) With YOLOv8 and Flask

Object Detection Web App using YOLOv11 and Flask. Supports RTSP Streams and Video Uploads. A study case for a Fall Detection System for the Elderly.

The Online Exam Proctor System is a computer vision-based project designed to ensure the integrity and fairness of online exams. As the popularity of remote learning and online education grows, the need for a robust proctoring system becomes crucial to prevent cheating and maintain the credibility of the examination process.

A tool that scans the background of images and videos and points out potential private information leaks such as house numbers, phone screens and logos, ensuring safety for social media users

Safety Equipment Wearing Detection System Using YOLOv8 and Fastapi

GARUDA is a high-precision surveillance system that leverages the YOLOv8 AI model to detect people in real-time video from drones or other cameras. The system includes a web control panel and instantly sends alerts with images to Telegram.

The Valorant Object Detection project is a Flask-based web application that allows users to upload images from the game Valorant and detect various in-game objects using a YOLOv8 model. The application provides a simple interface for uploading images and displays the detection results in an intuitive format.

Pothole Detection application that uses AI to analyse video and images

Data Farm est une application web développée dans le cadre du projet universitaire **Esprit School of Engineering**, visant à digitaliser la gestion agricole intelligente et durable.

This project uses a local YOLOv8 custom PPE model to detect the presence of PPE with a Meraki MV Camera. PPE Zones are defined to specify what a full 'PPE Kit' looks like per camera. If one or more PPE violations are detected, a Microsoft Teams message is sent to a notification space with an attached snapshot.