NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Run zero-shot prediction models on your data

ROS compatible package for object tracking based on SAM, Cutie, GroundingDINO, YOLO-World, VLPart and DEVA

YOLO-World-v2 のGradioデモをColaboratoryで実行するノートブック

EfficientSAM + YOLO World base model for use with Autodistill.

YOLO World base module for use with Autodistill.

System designed to provide real-time assistance to visually impaired individuals by detecting obstacles in their path and helping them locate objects in their environment.

ODLabel is a powerful tool for zero-shot object detection, labeling and visualization. It provides an intuitive graphical user interface for labeling objects in images using the YOLO-World model and supports various output formats such as YOLO, COCO, CSV, and XML.

This repository contains code for detecting Personal Protective Equipment (PPE) using YOLOv8 and YOLO-World's Custom Model with Custom Classes. The goal of this project is to identify whether individuals in images are wearing appropriate PPE such as helmets, safety vests, goggles, etc.

Description of YOLO-World along with it's application

Repository containing implemetation and documentation of diploma thesis Object detection and segmentation in historical encrypted manuscripts at at Faculty of Electrical Engineering and Information Technology of Slovak University of Technology in Bratislava (FEI STU).