YOLOv8 vs. YOLOR: Compared and Contrasted

Models

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5.

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO, CNN

CNN, YOLO

Frameworks

PyTorch

Annotation Format

Instance Segmentation

GitHub

GitHub Stars

21.1k+

2k+

License

AGPL-3.0

GPL-3.0

Paper

Training Notebook

Deploy Model

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.