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

test6

Espressif ESP-EYE (ESP32 240MHz)

100 ms

4096 kB

4096 kB

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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)
88%
grayscale-fomo-874
PERFORMANCE
LATENCY
1074 ms of 100 ms
Exceeds target by 974 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 | 88%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:36:01 PM

88%
rgb-fomo-a9e
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 | 88%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:34:13 PM

81%
grayscale-fomo-251
PERFORMANCE
LATENCY
1038 ms of 100 ms
Exceeds target by 938 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 | 60 | 81%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:45:08 PM

80%
rgb-fomo-b92
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 | 80%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:49:22 PM

80%
rgb-fomo-127
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 | 80%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:43:19 PM

78%
rgb-fomo-e16
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 | 78%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 2:02:44 PM

78%
grayscale-fomo-e26
PERFORMANCE
LATENCY
1031 ms of 100 ms
Exceeds target by 931 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 | 60 | 78%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:33:01 PM

72%
grayscale-fomo-803
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 | 72%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:52:55 PM

71%
rgb-fomo-373
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 | 71%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:40:26 PM

71%
rgb-fomo-e61
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 | 71%

FOMO (MobileNetV2 0.1) | int8

4/7/2024, 1:31:26 PM

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