Computer Vision Models for Edge Deployment

Models with smaller weight sizes and a good FPS are more suitable for edge deployment than larger models that require more compute and storage resources. Below, we have curated computer vision models that are well suited for deployment to the edge.

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Instance Segmentation
Instance Segmentation
Instance Segmentation
Instance Segmentation

Model Size:

MB

Parameters:

Top FPS:

Architecture:

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks. Learn more »
Object Detection
Object Detection
Object Detection
Object Detection

Model Size:

MB

Parameters:

Top FPS:

Architecture:

YOLO, CNN

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5. Learn more »
Instance Segmentation
Instance Segmentation
Instance Segmentation
Instance Segmentation

Model Size:

MB

Parameters:

219 million

Top FPS:

Architecture:

Transformers

OneFormer is a state-of-the-art multi-task image segmentation framework that is implemented using transformers. Learn more »
Classification
Classification
Classification
Classification

Model Size:

MB

Parameters:

Top FPS:

Architecture:

The Vision Transformer leverages powerful natural language processing embeddings (BERT) and applies them to images. Learn more »
Semantic Segmentation
Semantic Segmentation
Semantic Segmentation
Semantic Segmentation

Model Size:

MB

Parameters:

Top FPS:

51

Architecture:

Transformers

SegFormer is a computer vision framework used in semantic segmentation tasks, implemented with transformers. Learn more »
Object Detection
Object Detection
Object Detection
Object Detection

Model Size:

75.6

MB

Parameters:

Top FPS:

161

Architecture:

YOLO, CNN

YOLOv7 is a state of the art object detection model. Learn more »
Object Detection
Object Detection
Object Detection
Object Detection

Model Size:

14.1

MB

Parameters:

7.2 million

Top FPS:

140

Architecture:

CNN, YOLO

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

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