Models
YOLOR vs. YOLOv5

YOLOR vs. YOLOv5

Both YOLOR and YOLOv5 are commonly used in computer vision projects. Below, we compare and contrast YOLOR and YOLOv5.

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.
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YOLOv5

A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.
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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CNN, YOLO
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
2k+
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46k+
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License
GPL-3.0
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AGPL-3.0
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Training Notebook

Compare YOLOR and YOLOv5 with Autodistill

Compare YOLOR vs. YOLOv5

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.