YOLOR vs. Scaled-YOLOv4

Both YOLOR and Scaled YOLOv4 are commonly used in computer vision projects. Below, we compare and contrast YOLOR and Scaled YOLOv4.

Models

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

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN, YOLO

YOLO

Annotation Format

Instance Segmentation

Framework

PyTorch

GitHub

GitHub Stars

2k+

License

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.