Models
MobileNet SSD v2 vs. YOLOv5

MobileNet SSD v2 vs. YOLOv5

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

Models

icon-model

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.
icon-model

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
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
--
CNN, YOLO
--
Frameworks
TensorFlow 1.5
--
PyTorch
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
81+
--
46k+
--
License
MIT
--
AGPL-3.0
--
Training Notebook

Compare MobileNet SSD v2 and YOLOv5 with Autodistill

Models

MobileNet SSD v2 vs. YOLOv5

.

Both

MobileNet SSD v2

and

YOLOv5

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

MobileNet SSD v2

and

YOLOv5
  MobileNet SSD v2 YOLOv5
Date of Release Jan 13, 2018 Jan 06, 2020
Model Type Object Detection Object Detection
Architecture CNN, YOLO
GitHub Stars 81 33200

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 AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

YOLOv5

A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

Deploy a computer vision model today

Join 250,000 developers curating high quality datasets and deploying better models with Roboflow.

Get started