Edge Impulse Experts / Visual Anomaly Detection (FOMO_AD) Public

Target: Sony Spresense (Cortex-M4F 156MHz) Clone this project

Welcome to Edge Impulse, the largest community of edge AI developers!
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.

Visual Anomaly Detection (FOMO_AD)

Images

About this project

This public Edge Impulse project does not have a README yet. Clone this project to add new data or retrain this project, or to deploy this project to a device.

Data (139 items)

View all

non_anomaly26

ID: 1021437301

Label: no anomaly

non_anomaly21

ID: 1021437574

Label: no anomaly

non_anomaly66

ID: 1021436894

Label: no anomaly

non_anomaly42

ID: 1021437902

Label: no anomaly

non_anomaly60

ID: 1021436998

Label: no anomaly

non_anomaly71

ID: 1021436620

Label: no anomaly

non_anomaly73

ID: 1021436901

Label: no anomaly

non_anomaly96

ID: 1021438005

Label: no anomaly

Model accuracy (Unoptimized (float32))

Validation set

Test set

On-device performance (Sony Spresense (Cortex-M4F 156MHz), Quantized (int8))

Latency

197 ms.

Peak RAM usage

118.6K

Flash usage

81.7K

Run this model

On any device

Clone project

Dataset summary

Data collected

139 items

Labels

no anomaly, test1

Project info

Project ID	391673
License	Apache 2.0
No. of views	33,552
No. of clones	4