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STEVAL-STWINCSV1 data collection in Nano Edge studio

NShut.1
Associate

We are using the Nano Edge studio to run the STWIN DTMF Classifier on the STEVAL-STWINCSV1 on a Linux system.

We followed the instructions from: https://wiki.st.com/stm32mcu/wiki/AI   Entitled:  How to create a dual-tone multi-frequency classifier using NanoEdge AI Studio

When we run and capture 100 lines of samples, we move to the "Import Signal" and 99% of the data is misaligned and classed as corrupted. We have a space as our separator, but we need a new line to separate each line and this causes corruption. We also noted that on occasion we have, as an example, 0.0.000. We have tried modifying the code in the classifier example:

for( uint16_t class_cpt = 0; class_cpt < CLASS_NUMBER; class_cpt++ )
{
printf( " %.3f", output_class_buffer[ class_cpt ] );
}
printf( "\n" );

But no matter how we format the code the date is always classed as corrupt.

We are unable to use the button to "Open file location" as it does nothing.

1) Could you please tell us where we would find the output file so we can modify the csv file?

2) Would anyone know if we can modify the code to give us a better output format?

Thanks

Nevel

P.S. Not our signal is generated manually...by hitting the STWIN against the table or playing music!

1 REPLY 1
Julian E.
ST Employee

Hello @NShut.1 ,

 

You can find these files here: workspaceNanoEdgeAI/filesLogs

 

I will advise you to instead use the datalogger generator in NanoEdge AI Studio.

AI:NanoEdge AI Studio - stm32mcu

 

You can find all the source code here:

https://github.com/stm32-hotspot/stm32ai-nanoedge-datalogger

 

I don't really understand some part of your message but normally a project is divided in these steps:

  1. Create a project
  2. Create code data log
  3. Import data in the Studio
  4. Run a benchmark
  5. Compile the library after tests in validation
  6. Create a new code that log data similarly and use the function from the library to make inference

Here you talk about issue in logging and modifying the classifier code. There are no links, so it will not help you.

 

have a good day,

Julian


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