Question/Issue: Hello World, I have some problem for my Edge Impulse project in Spresense. The firmware what Edge Impulse build have 921600 (baud rate), but my device, Spresense have 115200 (baud rate). So, I want to change this boud rate in firmware to 115200, is this OK? If not, what can I do to fix it? Because, I think that is reason for my problem (image 2).
Thanks

Project ID: 229697
Context/Use case:
Hi @nntruyen ,
the initial connection with the deamon is always done at 115200.
The baud in the Device info is the maximum one which is used during streaming of the camera or when sending data to studio during ingestion, and for the Spresense is 921600.
As I said in the other topic, your problem is probably related to the model which is too big. I will try to have a look at it.
regards,
fv
I understand. But, What should I do to fix it? How to reduce the model?
If you make your EI project public I can clone it and try it on my Spresense.
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I have make my project public, you can clone it now
I am getting the same results as you using the EI ready-to-go binary
…investigating now…
I hope you find the cause and solution soon. it takes a lot of my time and I can’t continue my project.
@mmajchrzycki the Spresense firmware SDK release 09 May 2023 seems to have broken the ready-to-go binary.
- I duplicated @nntruyen deployed version has the issue he described.
- I get the same error when deploying a known good EI Impulse that previously worked on the Spresense, aka re-built the Model in the Studio and deployed via
flash_windows.bat
. I also tried in Ubuntu using ./flash_linux.sh
- I did a
make flash
using an older version of the EI Spresense SDK and the edge-impulse-run-impulse
worked as desired. I have no idea what version of the EI Spresense SDK I have in that project folder but it works. Is there a way to tell what version it is? Then, I could do a code diff to try and find the issue.
- I tried a different Impulse that is an image classification, 160x160, RGB and get the same error nntruyen described.
Please advise.
@Rocksetta or @louis when either of you get time could you take a known-good working image Impulse and re-deploy it using the latest version of the Studio to a Sony Spresense. I would like to get verification that the Edge Impulse Sony Spresense ready-to-go binary has a bug in it causing the Failed to allocate snapshot buffer
error.
@nntruyen I am still trying to figure this out…
Hi @MMarcial
I’ll give a look at Sony, thx for reporting.
fv
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Hi @MMarcial
I tested the Beers vs Can project Beer vs. cans FOMO - Dashboard - Edge Impulse and it works - input image size is 96x96.
The error regarding the snapshot buffer is due that there is not enough RAM to allocate memory for the image - with an input image size of 160x160 the RAM required by the model is doubled and there is not enough free.
When you say
I get the same error when deploying a known good EI Impulse that previously worked on the Spresense
do you refer to an object detection model ? 96x96 or 160x160?
@nntruyen can you try to set the input image to 96x96 ?
fv
Hi @ei_francesco. I tried with 96x96 before, but the result is still the same.
Did you try to change model architecture ?
You can try different architecture with lower RAM requirement but with less accuracy.