Models
OneFormer vs. YOLOv7 Instance Segmentation

OneFormer vs. YOLOv7 Instance Segmentation

Both OneFormer and YOLOv7 Instance Segmentation are commonly used in computer vision projects. Below, we compare and contrast OneFormer and YOLOv7 Instance Segmentation.

Models

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OneFormer

OneFormer is a state-of-the-art multi-task image segmentation framework that is implemented using transformers.
Learn more about OneFormer
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YOLOv7 Instance Segmentation

YOLOv7 Instance Segmentation lets you perform segmentation tasks with the YOLOv7 model.
Learn more about YOLOv7 Instance Segmentation
Model Type
Instance Segmentation
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Instance Segmentation
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Model Features
Item 1 Info
Item 2 Info
Architecture
Transformers
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YOLO
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
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View Repo
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View Repo
GitHub Stars
1.3k+
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12.5k+
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License
MIT
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GPL-3.0
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
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Compare OneFormer and YOLOv7 Instance Segmentation with Autodistill

Compare OneFormer vs. YOLOv7 Instance Segmentation

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.