jefferson.sarmiento / worm pick assistant 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 #3

Raspberry Pi 5

100 ms

8388608 kB

33554432 kB

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General

F1-score

Precision

Recall

33%
grayscale-fomo-c0a
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
409 kB of 8388608 kB
ROM
58 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

128 |
128

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 60 | 33%

FOMO (MobileNetV2 0.1) | int8

0 11/30/2025, 1:46:15 AM

0%
grayscale-fomo-3dd
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
240 kB of 8388608 kB
ROM
59 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 30 | 0%

FOMO (MobileNetV2 0.1) | int8

1 11/30/2025, 2:10:45 AM

0%
rgb-fomo-184
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
240 kB of 8388608 kB
ROM
59 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 60 | 0%

FOMO (MobileNetV2 0.1) | int8

0 11/30/2025, 1:52:38 AM

0%
rgb-fomo-ecf
PERFORMANCE
LATENCY
9 ms of 100 ms
RAM
631 kB of 8388608 kB
ROM
71 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 60 | 0%

FOMO (MobileNetV2 0.35) | int8

0 11/30/2025, 1:52:36 AM

0%
grayscale-fomo-91d
PERFORMANCE
LATENCY
3 ms of 100 ms
RAM
240 kB of 8388608 kB
ROM
58 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 30 | 0%

FOMO (MobileNetV2 0.1) | int8

0 11/30/2025, 1:44:12 AM

0%
grayscale-fomo-0df
PERFORMANCE
LATENCY
4 ms of 100 ms
RAM
409 kB of 8388608 kB
ROM
59 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT

128 |
128

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 60 | 0%

FOMO (MobileNetV2 0.1) | int8

0 11/30/2025, 1:45:24 AM