NanoEdge AI Operation Overview

Preface

ST has launched two highly integrated software solutions for AI applications, namely NanoEdge AI and CubeAI, to help users quickly adopt the technology. Today, we will mainly introduce NanoEdge AI, from operation to generating files and porting them into the MCU. The advantage of NanoEdge AI is its simple interface and the fact that it puts the most tedious training on the computer, with the MCU only using the final generated files.。

Obtain License

For NanoEdge AI, there are several months of free trial available. You can apply through the website or purchase directly. The steps are as follows:

  1. Apply for or purchase the license.
  2. Enter the obtained license in the NanoEdge AI software.
Your license key

If you don’t know your license key, log in to the Cryptlex licensing platform to retrieve it.
If you have lost your login credentials, reset your password using the email address used to download NanoEdge AI Studio.

Licensing API:Cartesiam API for library compilation:
54.147.158.22240.113.111.93
54.147.163.93
54.144.124.187
54.144.46.201
or via URL: https://api.cryptlex.com:443or via URL: https://apidev.cartesiam.net

Operation Method

  • Project Settings and MCU Selection (select the category project)
    • This mainly selects the flash size used on the control board in step 3.The corresponding data will be automatically generated based on the selected project.
  • As this step plans to classify objects into 4 categories, 4 different category data will be fed in.
  • This step allows the computer to simulate the training process to confirm the classification effect (in other words, to wait for the simulation to complete).
  • At this step, the file can be generated and the file can be pulled into your own environment. There are two pages here: one is to connect to your own system for more applications, and the other is to view the effect using Doma. Download based on the needs.
  • After the .a and .h files are generated, they can be connected to your own program for application.

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