YOLOv8 Instance Segmentation vs. YOLOv4 Tiny

Both YOLOv8 Instance Segmentation and YOLOv4 Tiny are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 Instance Segmentation and YOLOv4 Tiny.

Models

YOLOv8 Instance Segmentation

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.

Learn more about YOLOv8 Instance Segmentation

YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset

Learn more about YOLOv4 Tiny

Model Type

Instance Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

ResNet-D, YOLO

Annotation Format

Instance Segmentation

Framework

PyTorch

Darknet

GitHub

View Repo

GitHub Stars

21.1k+

License

AGPL-3.0

YOLO

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLOv8 Instance Segmentation vs. YOLOv4 Tiny

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.

YOLOv8 Instance Segmentation vs. YOLOv4 Tiny

Models