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
Raspberry Pi 4
100 ms
8388608 kB
33554432 kB
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General
F1-score
Precision
Recall
83%
rgb-mobilenetv2-212
PERFORMANCE
LATENCY
14 ms of 100 ms
RAM
738 kB of 8388608 kB
ROM
586 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 83%
MobileNetV2 160x160 0.35
16 | 0.5
6/3/2022, 5:16:11 AM
82%
rgb-mobilenetv2-cc6
PERFORMANCE
LATENCY
12 ms of 100 ms
RAM
738 kB of 8388608 kB
ROM
649 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 82%
MobileNetV2 0.35
64 | 0.1
6/3/2022, 5:16:39 AM
82%
rgb-mobilenetv2-949
PERFORMANCE
LATENCY
11 ms of 100 ms
RAM
738 kB of 8388608 kB
ROM
586 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 82%
MobileNetV2 0.35
16 | 0.1 |
6/3/2022, 5:18:12 AM
82%
rgb-mobilenetv1-3f0
PERFORMANCE
LATENCY
5 ms of 100 ms
RAM
264 kB of 8388608 kB
ROM
324 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 82%
MobileNetV1 0.25
64 | 0.1 |
6/3/2022, 5:24:54 AM
81%
rgb-mobilenetv1-399
PERFORMANCE
LATENCY
6 ms of 100 ms
RAM
264 kB of 8388608 kB
ROM
324 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 81%
MobileNetV1 0.25
64 | 0.5
6/3/2022, 5:27:27 AM
79%
rgb-mobilenetv2-fd8
PERFORMANCE
LATENCY
12 ms of 100 ms
RAM
670 kB of 8388608 kB
ROM
1633 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
96 |
96
IMAGE
RGB
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 79%
MobileNetV2 160x160 0.75
16 | 0.5
6/3/2022, 5:23:23 AM
70%
grayscale-mobilenetv1-962
PERFORMANCE
LATENCY
6 ms of 100 ms
RAM
264 kB of 8388608 kB
ROM
312 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
Grayscale
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 70%
MobileNetV1 0.25
16 | 0.5
6/3/2022, 5:20:42 AM
69%
grayscale-mobilenetv1-b34
PERFORMANCE
LATENCY
6 ms of 100 ms
RAM
264 kB of 8388608 kB
ROM
312 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
160 |
160
IMAGE
Grayscale
ACCURACY (KERAS-TRANSFER-IMAGE)
TRANSFER LEARNING (IMAGES)
0.0005 | 20 | 69%
MobileNetV1 0.25
16 | 0.1 |
6/3/2022, 5:22:27 AM
67%
rgb-conv2d-085
PERFORMANCE
LATENCY
2 ms of 100 ms
RAM
51 kB of 8388608 kB
ROM
42 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
64 |
64
IMAGE
RGB
ACCURACY (KERAS)
CLASSIFICATION (KERAS)
0.0005 | 10 | 67%
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 8 | 3 | - |
| conv2d | 16 | 3 | - |
| dropout | - | - | 0.25 |
6/3/2022, 5:16:52 AM
62%
grayscale-conv2d-8b1
PERFORMANCE
LATENCY
44 ms of 100 ms
RAM
30 kB of 8388608 kB
ROM
59 kB of 33554432 kB
DSP NN Unused
IMAGE INPUT
32 |
32
IMAGE
Grayscale
ACCURACY (KERAS)
CLASSIFICATION (KERAS)
0.0005 | 10 | 62%
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 16 | 3 | - |
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| dropout | - | - | 0.25 |
6/3/2022, 5:23:06 AM
Training output
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