Automotive Maintenance / Spark Plugs - FOMO-AD Public
The EON Tuner helps you quickly run hyper-parameter sweeps that explore different pre-processing + model architectures optimized for your defined objectives. Clone this project to use the EON Tuner.

Target

Run #1

Raspberry Pi 5

100 ms

8388608 kB

33554432 kB

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General

Anomaly accuracy

F1-score

Precision

Recall

100%
grayscale-fomo-ad-661
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
517 kB of 8388608 kB
ROM
125 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

128 |
128

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 1.7

100% | 100% | 100% | 100%

1 9/15/2025, 12:26:32 PM

86%
rgb-fomo-ad-3cb
PERFORMANCE
LATENCY
5 ms of 100 ms
RAM
714 kB of 8388608 kB
ROM
125 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 1.7

86% | 92% | 83% | 100%

2 9/15/2025, 12:37:36 PM

86%
grayscale-fomo-ad-5a9
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
793 kB of 8388608 kB
ROM
138 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 1.7

86% | 92% | 83% | 100%

2 9/15/2025, 12:37:47 PM

86%
grayscale-fomo-ad-ab2
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
1377 kB of 8388608 kB
ROM
159 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

224 |
224

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 1.3

86% | 92% | 83% | 100%

1 9/15/2025, 12:26:47 PM

86%
rgb-fomo-ad-8ec
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
517 kB of 8388608 kB
ROM
126 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

128 |
128

IMAGE

RGB

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 0.6

86% | 50% | 100% | -

0 9/15/2025, 12:13:53 PM

86%
grayscale-fomo-ad-fdd
PERFORMANCE
LATENCY
27 ms of 100 ms
RAM
3514 kB of 8388608 kB
ROM
329 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

224 |
224

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Patchcore | mobilenet_v2_a1 | 3 | 9 | 3 | 0.005 | 0.6

86% | 92% | 83% | 100%

0 9/15/2025, 12:12:06 PM

86%
grayscale-fomo-ad-c3f
PERFORMANCE
LATENCY
2 ms of 100 ms
RAM
302 kB of 8388608 kB
ROM
116 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 2

86% | 92% | 83% | 100%

0 9/15/2025, 12:12:48 PM

71%
grayscale-fomo-ad-1ea
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
1516 kB of 8388608 kB
ROM
126 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

224 |
224

IMAGE

Grayscale

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | low | 1.5

71% | 83% | 67% | 100%

1 9/15/2025, 12:26:34 PM

57%
rgb-fomo-ad-cf7
PERFORMANCE
LATENCY
15 ms of 100 ms
RAM
1891 kB of 8388608 kB
ROM
412 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

VISUAL ANOMALY DETECTION - FOMO-AD
Patchcore | mobilenet_v2_a1 | 3 | 9 | 3 | 0.005 | 0.6

57% | 75% | 50% | 100%

0 9/15/2025, 12:19:34 PM

43%
rgb-fomo-ad-a6a
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
597 kB of 8388608 kB
ROM
167 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

128 |
128

IMAGE

RGB

VISUAL ANOMALY DETECTION - FOMO-AD
Patchcore | mobilenet_v2_a1 | 3 | 9 | 3 | 0.005 | 0.6

43% | 67% | 33% | 100%

0 9/15/2025, 12:19:19 PM

14%
rgb-fomo-ad-a3e
PERFORMANCE
LATENCY
10 ms of 100 ms
RAM
1528 kB of 8388608 kB
ROM
172 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

224 |
224

IMAGE

RGB

VISUAL ANOMALY DETECTION - FOMO-AD
Gaussian Mixture Model (GMM) | mobilenet_v2_a35 | medium | 0.6

14% | 50% | - | 100%

2 9/15/2025, 12:37:34 PM