Models
OneFormer vs. YOLOv4 PyTorch

OneFormer vs. YOLOv4 PyTorch

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

Models

icon-model

OneFormer

OneFormer is a state-of-the-art multi-task image segmentation framework that is implemented using transformers.
Learn more about OneFormer
icon-model

YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
Learn more about YOLOv4 PyTorch
Model Type
Instance Segmentation
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
Transformers
--
YOLO
--
Annotation Format
Instance Segmentation
Instance Segmentation
Framework
--
PyTorch
--
PyTorch
GitHub
--
View Repo
--
View Repo
GitHub Stars
1.3k+
--
4.4k+
--
License
MIT
--
Apache-2.0
--
Paper
--
View Paper
--
View Paper
Training Notebook
Train on Colab
--
Train on Colab
--
Deploy Model
--
rocket icon
Deploy with Roboflow
--
rocket icon
Deploy with Roboflow
Compare Alternatives
--
Compare with...
--
Compare with...

Compare OneFormer and YOLOv4 PyTorch with Autodistill

Compare OneFormer vs. YOLOv4 PyTorch

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.