Models
MobileNet V2 Classification vs. YOLOv5

MobileNet V2 Classification vs. YOLOv5

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

Models

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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.
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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
Classification
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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CNN, YOLO
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Frameworks
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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46k+
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License
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AGPL-3.0
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Training Notebook

Compare MobileNet V2 Classification and YOLOv5 with Autodistill

Compare MobileNet V2 Classification 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.