YOLOR vs. Resnet-32: Compared and Contrasted

Models

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

A fast, simple convolutional neural network that gets the job done for many tasks, including classification.

Model Type

Object Detection

Classification

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN, YOLO

Frameworks

PyTorch

Fast.ai v2

Annotation Format

Instance Segmentation

GitHub

GitHub Stars

2k+

32+

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.