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

tuner

Espressif ESP-EYE (ESP32 240MHz)

100 ms

4096 kB

4096 kB

Filters

Status

DSP type

Model type

View

Data set

Variant

Sort

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)
88%
grayscale-fomo-a62
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

4/9/2024, 1:59:46 PM

88%
rgb-fomo-2d3
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

4/9/2024, 1:59:25 PM

81%
grayscale-fomo-773
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

4/9/2024, 2:13:48 PM

80%
rgb-fomo-0eb
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

4/9/2024, 2:15:22 PM

80%
rgb-fomo-fba
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

4/9/2024, 2:08:50 PM

78%
rgb-fomo-476
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

4/9/2024, 2:32:03 PM

78%
grayscale-fomo-3b1
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

4/9/2024, 2:04:09 PM

72%
grayscale-fomo-94a
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

4/9/2024, 2:17:18 PM

71%
rgb-fomo-093
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

4/9/2024, 2:06:22 PM

71%
rgb-fomo-71d
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

4/9/2024, 1:54:22 PM

Help & documentation Get help on the forum Send feedback Contact sales
Join us
Terms of Service Privacy policy