Ankita Jadhav / lab_human_detection Public
Target: Espressif ESP-EYE (ESP32 240MHz) 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

test3

Espressif ESP-EYE (ESP32 240MHz)

100 ms

4096 kB

4096 kB

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General

F1-score

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Run #17 - tuner (Apr 09 2024, 13:44:50, finished) Run #16 - test6 (Apr 07 2024, 13:20:36, finished) Run #15 - test5 (Mar 31 2024, 16:06:50, running) Run #14 - test5 (Mar 22 2024, 16:43:18, finished) Run #13 - test5 (Mar 22 2024, 09:47:12, finished) Run #12 - test5 (Mar 22 2024, 09:25:33, cancelled) Run #11 - test4 (Mar 21 2024, 20:56:09, finished) Run #10 - test4 (Mar 19 2024, 17:15:35, finished) Run #9 - test4 (Mar 19 2024, 16:07:32, finished) Run #8 - test4 (Mar 18 2024, 12:59:55, cancelled) Run #7 - test4 (Mar 18 2024, 12:34:19, cancelled) Run #6 - test3 (Mar 18 2024, 12:03:21, cancelled) Run #5 - test3 (Mar 17 2024, 21:26:12, finished) Run #4 - test2 (Mar 15 2024, 12:46:49, finished) Run #3 - test1 (Mar 14 2024, 18:26:52, finished) Run #2 - test1 (Mar 14 2024, 18:21:03, finished) Run #1 - testing (Mar 14 2024, 13:05:13, finished)
83%
grayscale-fomo-d61
PERFORMANCE
LATENCY
1011 ms of 100 ms
Exceeds target by 911 ms
RAM
240 kB of 4096 kB
ROM
64 kB of 4096 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 30 | 83%

FOMO (MobileNetV2 0.1) | int8

3/18/2024, 12:22:49 PM

82%
rgb-fomo-5f3
PERFORMANCE
LATENCY
1066 ms of 100 ms
Exceeds target by 966 ms
RAM
240 kB of 4096 kB
ROM
64 kB of 4096 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 60 | 82%

FOMO (MobileNetV2 0.1) | int8

3/18/2024, 12:24:19 PM

73%
grayscale-fomo-313
PERFORMANCE
LATENCY
1010 ms of 100 ms
Exceeds target by 910 ms
RAM
240 kB of 4096 kB
ROM
64 kB of 4096 kB
DSP NN Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 30 | 73%

FOMO (MobileNetV2 0.1) | int8

3/18/2024, 12:26:07 PM

grayscale-fomo-0b9
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.1) | int8

rgb-fomo-0dc
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.1) | int8

rgb-fomo-4f0
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

rgb-fomo-709
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.35) | int8

rgb-fomo-13c
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.1) | int8

rgb-fomo-80f
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.35) | int8

rgb-fomo-bd4
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

RGB

OBJECT DETECTION (IMAGES)

0.1 | 60

FOMO (MobileNetV2 0.1) | int8

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