Edge Impulse Experts / Visual Anomaly Detection (FOMO_AD) Public
Target: Sony Spresense (Cortex-M4F 156MHz) Clone this project

Test data

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Model variants
Test 'Unoptimized (float32)' model Test 'Quantized (int8)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.

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Sample name Expected outcome Anomaly Accuracy Result
testing.50ccjp4s testing
Show classification Show in data acquisition Show in feature explorer
testing.50ccj168 testing
Show classification Show in data acquisition Show in feature explorer
testing.50ccid98 testing
Show classification Show in data acquisition Show in feature explorer
testing.50ccgs5m testing
Show classification Show in data acquisition Show in feature explorer
testing.50ccdtqc testing
Show classification Show in data acquisition Show in feature explorer
testing.50cccbae testing
Show classification Show in data acquisition Show in feature explorer
testing.50ccacv1 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cc97e8 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cc7vk5 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cc70dp testing
Show classification Show in data acquisition Show in feature explorer
testing.50cc5sn9 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cc508d testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbpps3 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbp6jo testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbo3tc testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbmgaa testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbm26h testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbjpbh testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbifif testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbhkhh testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbftui testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbev11 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbe3qm testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbbsif testing
Show classification Show in data acquisition Show in feature explorer
testing.50cbakcl testing
Show classification Show in data acquisition Show in feature explorer
testing.50cb4f3s testing
Show classification Show in data acquisition Show in feature explorer
testing.50cb3003 testing
Show classification Show in data acquisition Show in feature explorer
testing.50cb1snf testing
Show classification Show in data acquisition Show in feature explorer
testing.50cb06pl testing
Show classification Show in data acquisition Show in feature explorer
testing.4vssqvbb testing
Show classification Show in data acquisition Show in feature explorer
testing.4vssp91u testing
Show classification Show in data acquisition Show in feature explorer
non_anomaly18 no anomaly 12.52 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly36 no anomaly 11.66 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly70 no anomaly 6.02 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly16 no anomaly 15.88 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly32 no anomaly 10.84 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly7 no anomaly 14.92 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly91 no anomaly 4.80 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly55 no anomaly 8.51 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
non_anomaly3 no anomaly 12.81 100% no anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly1 anomaly 28.79 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly6 anomaly 14.25 0% no anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly9 anomaly 19.17 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly4 anomaly 25.12 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly7 anomaly 25.33 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly5 anomaly 28.18 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly3 anomaly 32.73 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly2 anomaly 35.95 100% anomaly
Show classification Show in data acquisition Show in feature explorer
anomaly8 anomaly 19.98 100% anomaly
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
Accuracy
94.44%

Confusion matrix

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Feature explorer

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