Models
YOLOv8 Instance Segmentation vs. MobileNet SSD v2

YOLOv8 Instance Segmentation vs. MobileNet SSD v2

Both YOLOv8 Instance Segmentation and MobileNet SSD v2 are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 Instance Segmentation and MobileNet SSD v2.

Models

icon-model

YOLOv8 Instance Segmentation

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.
Learn more about YOLOv8 Instance Segmentation
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.
Learn more about MobileNet SSD v2
Model Type
Instance Segmentation
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
--
--
Annotation Format
Instance Segmentation
Instance Segmentation
Framework
--
PyTorch
--
TensorFlow 1.5
GitHub
--
View Repo
--
View Repo
GitHub Stars
21.1k+
--
81+
--
License
AGPL-3.0
--
MIT
--
Paper
--
View Paper
--
View Paper
Training Notebook
Train on Colab
--
Train on Colab
--
Deploy Model
--
rocket icon
Deploy with Roboflow
--
rocket icon
Deploy with Roboflow
Compare Alternatives
--
Compare with...
--
Compare with...

Compare YOLOv8 Instance Segmentation and MobileNet SSD v2 with Autodistill

Compare YOLOv8 Instance Segmentation vs. MobileNet SSD v2

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.