Models
YOLOR vs. YOLOv3 PyTorch

YOLOR vs. YOLOv3 PyTorch

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

Models

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YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.
Learn more about YOLOR
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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
CNN, 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
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View Repo
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View Repo
GitHub Stars
2k+
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7.2k+
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License
GPL-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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rocket icon
Deploy with Roboflow
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Compare YOLOR and YOLOv3 PyTorch with Autodistill

Compare YOLOR 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.