MobileNet SSD v2 vs. YOLOv3 PyTorch: Compared and Contrasted

Models

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.

Learn more about MobileNet SSD v2

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.

Learn more about YOLOv3 PyTorch

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

Frameworks

TensorFlow 1.5

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

81+

7.2k+

License

MIT

GPL-3.0

Paper

Training Notebook

Deploy Model

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MobileNet SSD v2 vs. YOLOv3 PyTorch

Both

MobileNet SSD v2

and

YOLOv3 PyTorch

are commonly used in computer vision projects. Below, we compare and contrast

MobileNet SSD v2

and

YOLOv3 PyTorch

	MobileNet SSD v2	YOLOv3 PyTorch
Date of Release	Jan 13, 2018	Apr 08, 2018
Model Type	Object Detection	Object Detection
Architecture		YOLO
GitHub Stars	81	7200

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.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

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.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

Learn more about MobileNet SSD v2

Learn more about YOLOv3 PyTorch