OneFormer vs. YOLOv4 Tiny

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

Models

OneFormer is a state-of-the-art multi-task image segmentation framework that is implemented using transformers.

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

Model Type

Instance Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

Transformers

ResNet-D, YOLO

Frameworks

PyTorch

Darknet

Annotation Format

Instance Segmentation

GitHub

GitHub Stars

1.3k+

License

MIT

YOLO

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.