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EON Tuner

Run #1 (, finished)
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 Portenta H7 (Cortex-M7 480MHz)

100 ms

512 kB

2048 kB

Filters

Status

DSP type

Network type

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Data set

Precision

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General

F1-score

Precision

Recall

90%
grayscale-fomo-3a9
Show logs
PERFORMANCE
LATENCY
123 ms of 100 ms
Exceeds target by 23 ms
RAM
627 kB of 512 kB
Exceeds target by 115 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

4/6/2024, 10:37:40 PM

90%
grayscale-fomo-df3
Show logs
PERFORMANCE
LATENCY
168 ms of 100 ms
Exceeds target by 68 ms
RAM
630 kB of 512 kB
Exceeds target by 118 kB
ROM
78 kB of 2048 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

4/7/2024, 2:22:48 AM

88%
rgb-fomo-7fa
Show logs
PERFORMANCE
LATENCY
111 ms of 100 ms
Exceeds target by 11 ms
RAM
627 kB of 512 kB
Exceeds target by 115 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 2:41:11 AM

86%
grayscale-fomo-92e
Show logs
PERFORMANCE
LATENCY
64 ms of 100 ms
RAM
243 kB of 512 kB
ROM
78 kB of 2048 kB
DSP NN Unused
INPUT

96 | 96

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.35) | int8

4/7/2024, 6:54:32 AM

86%
rgb-fomo-591
Show logs
PERFORMANCE
LATENCY
54 ms of 100 ms
RAM
243 kB of 512 kB
ROM
78 kB of 2048 kB
DSP NN Unused
INPUT

96 | 96

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.35) | int8

4/7/2024, 6:57:40 AM

85%
grayscale-fomo-506
Show logs
PERFORMANCE
LATENCY
76 ms of 100 ms
RAM
409 kB of 512 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

128 | 128

IMAGE

Grayscale

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

4/6/2024, 9:26:10 PM

85%
rgb-fomo-43c
Show logs
PERFORMANCE
LATENCY
45 ms of 100 ms
RAM
240 kB of 512 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

96 | 96

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:08:32 AM

84%
rgb-fomo-9db
Show logs
PERFORMANCE
LATENCY
80 ms of 100 ms
RAM
409 kB of 512 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

128 | 128

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 7:05:57 AM

84%
rgb-fomo-954
Show logs
PERFORMANCE
LATENCY
126 ms of 100 ms
Exceeds target by 26 ms
RAM
627 kB of 512 kB
Exceeds target by 115 kB
ROM
64 kB of 2048 kB
DSP NN Unused
INPUT

160 | 160

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 7:57:32 AM

81%
rgb-fomo-0c0
Show logs
PERFORMANCE
LATENCY
67 ms of 100 ms
RAM
243 kB of 512 kB
ROM
78 kB of 2048 kB
DSP NN Unused
INPUT

96 | 96

IMAGE

RGB

ACCURACY
OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.35) | int8

4/7/2024, 7:00:42 AM

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