YOLOv8 vs. Resnet-32

Both YOLOv8 and ResNet 32 are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 and ResNet 32.

Models

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

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

YOLO, CNN

Frameworks

PyTorch

Fast.ai v2

Annotation Format

Instance Segmentation

GitHub

GitHub Stars

21.1k+

32+

License

AGPL-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.