Models
YOLOv5 vs. MobileNet SSD v2

YOLOv5 vs. MobileNet SSD v2

Both YOLOv5 and MobileNet SSD v2 are commonly used in computer vision projects. Below, we compare and contrast YOLOv5 and MobileNet SSD v2.

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.
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MobileNet SSD v2

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
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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Frameworks
PyTorch
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TensorFlow 1.5
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
46k+
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81+
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License
AGPL-3.0
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MIT
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Training Notebook

Compare YOLOv5 and MobileNet SSD v2 with Autodistill

Compare YOLOv5 vs. MobileNet SSD v2

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.