Models
YOLOv8 vs. YOLOv3 PyTorch

YOLOv8 vs. YOLOv3 PyTorch

Both YOLOv8 and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 and YOLOv3 PyTorch.

Models

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YOLOv8

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5.
Learn more about YOLOv8
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YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
Learn more about YOLOv3 PyTorch
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO, CNN
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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
21.1k+
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7.2k+
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License
AGPL-3.0
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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 YOLOv8 and YOLOv3 PyTorch with Autodistill

Compare YOLOv8 vs. YOLOv3 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.