EON Tuner
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
Vision
Raspberry Pi 4
100 ms
585 kB
585 kB
Filters
Status
DSP type
Network type
View
Data set
Precision
Sort
General
F1-score
Precision
Recall
PERFORMANCE
LATENCY
8 ms of
100 ms
RAM
369 kB of
4194304 kB
ROM
2358 kB of
33554432 kB
DSP
NN
Unused
INPUT
96 | 96
IMAGE
RGB
ACCURACY
NEURAL NETWORK (KERAS)
0.0005 | 10
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| dropout | - | - | 0.25 |
| dense | 64 | - | - |
| dropout | - | - | 0.25 |
1/20/2022, 2:24:27 PM
PERFORMANCE
LATENCY
10 ms of
100 ms
RAM
372 kB of
4194304 kB
ROM
163 kB of
33554432 kB
DSP
NN
Unused
INPUT
96 | 96
IMAGE
Grayscale
ACCURACY
NEURAL NETWORK (KERAS)
0.0005 | 10
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| conv2d | 128 | 3 | - |
| dropout | - | - | 0.5 |
1/20/2022, 2:46:41 PM
Training output
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Click 'Run EON Tuner' to begin
