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
Arduino Portenta H7 (Cortex-M7 480MHz)
300 ms
512 kB
2048 kB
Filters
Status
DSP type
Network type
View
Data set
Precision
Sort
General
F1-score
Precision
Recall
PERFORMANCE
LATENCY
432 ms of
300 ms
Exceeds target by 132 ms
RAM
98 kB of
512 kB
ROM
81 kB of
2048 kB
DSP
NN
Unused
INPUT
96 | 96
IMAGE
Grayscale
ACCURACY
CLASSIFICATION (KERAS)
0.0005 | 20
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 8 | 3 | - |
| conv2d | 5 | 3 | - |
| dropout | - | - | 0.25 |
| dense | 8 | - | - |
9/28/2022, 8:00:22 AM
PERFORMANCE
LATENCY
322 ms of
300 ms
Exceeds target by 22 ms
RAM
75 kB of
512 kB
ROM
68 kB of
2048 kB
DSP
NN
Unused
INPUT
96 | 96
IMAGE
Grayscale
ACCURACY
CLASSIFICATION (KERAS)
0.0005 | 20
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 6 | 3 | - |
| conv2d | 3 | 3 | - |
| dropout | - | - | 0.25 |
| dense | 6 | - | - |
9/28/2022, 8:00:34 AM
Training output
Hide
Click 'Run EON Tuner' to begin
