Models
Scaled-YOLOv4 vs. YOLOR

Scaled-YOLOv4 vs. YOLOR

Both Scaled YOLOv4 and YOLOR are commonly used in computer vision projects. Below, we compare and contrast Scaled YOLOv4 and YOLOR.

Models

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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
Learn more about Scaled YOLOv4
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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
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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CNN, YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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PyTorch
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PyTorch
GitHub
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View Repo
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View Repo
GitHub Stars
2k+
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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 Scaled YOLOv4 and YOLOR with Autodistill

Compare Scaled-YOLOv4 vs. YOLOR

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.