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EON Tuner

The EON Tuner helps you find the most optimal architecture for your embedded machine-learning application. Clone this project to use the EON Tuner.

Target

No name set

Object detection with centroids

Arduino Nicla Vision (Cortex-M7 480MHz)

100 ms

128 kB

1024 kB

Filters

Status

DSP type

Network type

View

Data set

Precision

Sort

General

F1-score

Precision

Recall

96%
rgb-fomo-63e
Show logs
PERFORMANCE
LATENCY
166 ms of 100 ms
Exceeds target by 66 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

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

95%
grayscale-fomo-69b
Show logs
PERFORMANCE
LATENCY
287 ms of 100 ms
Exceeds target by 187 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

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

95%
rgb-fomo-dcf
Show logs
PERFORMANCE
LATENCY
251 ms of 100 ms
Exceeds target by 151 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

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

93%
grayscale-fomo-4ba
Show logs
PERFORMANCE
LATENCY
314 ms of 100 ms
Exceeds target by 214 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

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

93%
grayscale-fomo-4b6
Show logs
PERFORMANCE
LATENCY
276 ms of 100 ms
Exceeds target by 176 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.35) | int8

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

67%
grayscale-fomo-a32
Show logs
PERFORMANCE
LATENCY
219 ms of 100 ms
Exceeds target by 119 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.35) | int8

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

62%
grayscale-fomo-18e
Show logs
PERFORMANCE
LATENCY
218 ms of 100 ms
Exceeds target by 118 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.35) | int8

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

47%
rgb-fomo-42e
Show logs
PERFORMANCE
LATENCY
263 ms of 100 ms
Exceeds target by 163 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.35) | int8

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

47%
rgb-fomo-06f
Show logs
PERFORMANCE
LATENCY
285 ms of 100 ms
Exceeds target by 185 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.35) | int8

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

38%
rgb-fomo-e40
Show logs
PERFORMANCE
LATENCY
271 ms of 100 ms
Exceeds target by 171 ms
RAM
630 kB of 128 kB
Exceeds target by 502 kB
ROM
78 kB of 1024 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.35) | int8

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

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