Edge Impulse Experts / Surgery Inventory Synthetic Public
Target: Arduino Nicla Vision (Cortex-M7 480MHz) Clone this project
Experiments EON Tuner
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

No name set

Arduino Nicla Vision (Cortex-M7 480MHz)

100 ms

1024 kB

2048 kB

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General

F1-score

Precision

Recall

97%
rgb-fomo-63e
PERFORMANCE
LATENCY
166 ms of 100 ms
Exceeds target by 66 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 60 | 97%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 2:28:22 PM

96%
rgb-fomo-dcf
PERFORMANCE
LATENCY
251 ms of 100 ms
Exceeds target by 151 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 60 | 96%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:29:04 PM

94%
grayscale-fomo-4ba
PERFORMANCE
LATENCY
314 ms of 100 ms
Exceeds target by 214 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 60 | 94%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 2:31:09 PM

93%
grayscale-fomo-69b
PERFORMANCE
LATENCY
287 ms of 100 ms
Exceeds target by 187 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 60 | 93%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 3:00:21 PM

85%
grayscale-fomo-4b6
PERFORMANCE
LATENCY
276 ms of 100 ms
Exceeds target by 176 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 30 | 85%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:45:19 PM

30%
grayscale-fomo-a32
PERFORMANCE
LATENCY
219 ms of 100 ms
Exceeds target by 119 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 60 | 30%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:28:33 PM

20%
grayscale-fomo-18e
PERFORMANCE
LATENCY
218 ms of 100 ms
Exceeds target by 118 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 30 | 20%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:15:39 PM

1%
rgb-fomo-42e
PERFORMANCE
LATENCY
263 ms of 100 ms
Exceeds target by 163 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 30 | 1%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:16:16 PM

1%
rgb-fomo-06f
PERFORMANCE
LATENCY
285 ms of 100 ms
Exceeds target by 185 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 60 | 1%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 1:58:34 PM

rgb-fomo-e40
PERFORMANCE
LATENCY
271 ms of 100 ms
Exceeds target by 171 ms
RAM
630 kB of 1024 kB
ROM
78 kB of 2048 kB
DSP NN Unused
IMAGE INPUT

160 |
160

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 60 | 0%

FOMO (MobileNetV2 0.35) | int8

12/21/2023, 3:28:26 PM

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