Models
YOLOv8 Instance Segmentation vs. YOLOv4 PyTorch

YOLOv8 Instance Segmentation vs. YOLOv4 PyTorch

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

Models

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YOLOv8 Instance Segmentation

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.
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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.
Model Type
Instance Segmentation
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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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 Stars
21.1k+
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4.4k+
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License
AGPL-3.0
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Apache-2.0
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Training Notebook

Compare YOLOv8 Instance Segmentation and YOLOv4 PyTorch with Autodistill

Compare YOLOv8 Instance Segmentation 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.