Models
YOLOv5 vs. YOLOv4

YOLOv5 vs. YOLOv4

Both YOLOv5 and YOLOv4 Darknet are commonly used in computer vision projects. Below, we compare and contrast YOLOv5 and YOLOv4 Darknet.

Models

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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.
Learn more about YOLOv5
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YOLOv4 Darknet

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 Darknet.
Learn more about YOLOv4 Darknet
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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Darknet
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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
46k+
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License
AGPL-3.0
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YOLO
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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 YOLOv5 and YOLOv4 Darknet with Autodistill

Compare YOLOv5 vs. YOLOv4

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.