Models
YOLOv3 PyTorch vs. MobileNet V2 Classification

YOLOv3 PyTorch vs. MobileNet V2 Classification

Both YOLOv3 PyTorch and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOv3 PyTorch and MobileNet V2 Classification.

Models

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YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
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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
YOLO
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Frameworks
PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.2k+
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License
GPL-3.0
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Training Notebook

Compare YOLOv3 PyTorch and MobileNet V2 Classification with Autodistill

Compare YOLOv3 PyTorch 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.