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
Nvidia Jetson Nano
100 ms
4194304 kB
16777216 kB
Filters
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DSP type
Model type
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General
F1-score
Precision
Recall
PERFORMANCE
LATENCY
6 ms of
100 ms
RAM
89 kB of
4194304 kB
ROM
405 kB of
16777216 kB
DSP
NN
Unused
IMAGE INPUT
32
|
32
IMAGE
RGB
ACCURACY (KERAS)
CLASSIFICATION
0.0005 | 10 | 65%
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 16 | 3 | - |
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| conv2d | 128 | 3 | - |
| dropout | - | - | 0.25 |
12/22/2022, 4:06:24 PM
PERFORMANCE
LATENCY
8 ms of
100 ms
RAM
184 kB of
4194304 kB
ROM
126 kB of
16777216 kB
DSP
NN
Unused
IMAGE INPUT
64
|
64
IMAGE
RGB
ACCURACY (KERAS)
CLASSIFICATION
0.0005 | 10 | 53%
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 8 | 3 | - |
| conv2d | 16 | 3 | - |
| conv2d | 32 | 3 | - |
| conv2d | 64 | 3 | - |
| dropout | - | - | 0.25 |
12/22/2022, 4:01:06 PM
Training output
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