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
Sony Spresense (Cortex-M4F 156MHz)
100 ms
1536 kB
8192 kB
Filters
Status
DSP type
Network type
View
Data set
Precision
Sort
General
F1-score
Precision
Recall
PERFORMANCE
LATENCY
271 ms of
100 ms
Exceeds target by 171 ms
RAM
20 kB of
1536 kB
ROM
60 kB of
8192 kB
DSP
NN
Unused
INPUT
32 | 32
IMAGE
Grayscale
ACCURACY
CLASSIFICATION (KERAS)
0.0005 | 10
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 8 | 3 | - |
| conv2d | 16 | 3 | - |
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| dropout | - | - | 0.25 |
7/19/2022, 1:04:46 PM
Training output
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Click 'Run EON Tuner' to begin
