Models
YOLOv5 vs. MobileNet V2 Classification

YOLOv5 vs. MobileNet V2 Classification

Both YOLOv5 and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOv5 and MobileNet V2 Classification.

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 V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.
Model Type
Object Detection
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Classification
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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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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
46k+
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License
AGPL-3.0
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Training Notebook

Compare YOLOv5 and MobileNet V2 Classification with Autodistill

Compare YOLOv5 vs. MobileNet V2 Classification

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.