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

test5

Espressif ESP-EYE (ESP32 240MHz)

100 ms

4096 kB

4096 kB

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General

F1-score

Precision

Recall

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)
86%
rgb-fomo-a51
PERFORMANCE
LATENCY
1076 ms of 100 ms
Exceeds target by 976 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 | 30 | 86%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:33:26 PM

83%
rgb-fomo-923
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 | 83%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:27:46 PM

82%
rgb-fomo-cad
PERFORMANCE
LATENCY
940 ms of 100 ms
Exceeds target by 840 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 | 30 | 82%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:19:36 PM

77%
rgb-fomo-2b8
PERFORMANCE
LATENCY
1154 ms of 100 ms
Exceeds target by 1054 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)

0.1 | 60 | 77%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:44:55 PM

73%
rgb-fomo-b24
PERFORMANCE
LATENCY
1058 ms of 100 ms
Exceeds target by 958 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)

0.1 | 60 | 73%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:16:57 PM

68%
rgb-fomo-f2d
PERFORMANCE
LATENCY
1050 ms of 100 ms
Exceeds target by 950 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)

0.1 | 30 | 68%

FOMO (MobileNetV2 0.1) | int8

3/31/2024, 4:25:17 PM

grayscale-fomo-ab7
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 60

FOMO (MobileNetV2 0.1) | int8

grayscale-fomo-1c4
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

grayscale-fomo-75b
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.1 | 30

FOMO (MobileNetV2 0.1) | int8

grayscale-fomo-ad4
PERFORMANCE
LATENCY
100 ms
RAM
4096 kB
ROM
4096 kB
Unused
IMAGE INPUT

96 |
96

IMAGE

Grayscale

OBJECT DETECTION (IMAGES)

0.01 | 30

FOMO (MobileNetV2 0.1) | int8

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