Hi STM Community,
I'm currently leveraging an STM32H745I-DISCO to run our custom DNN model, which is designed for a 4-class classification task and accepts multivariate time-series data of the shape (3, 2048). While I've successfully analyzed and validated the model with random input data on the target platform, I'm finding it challenging to upload and run inference using our own custom data (over 100 instances).
Considering my limited experience in embedded engineering, I'm in need of detailed guidance on how to accomplish the following:
Data Uploading: What are the steps and the preferred format to upload our custom data onto the STM32 platform?
Data Implementation: How can I integrate this data into the main script for the model to run inference?
Data Reshaping: The first reference below seems to illustrate the use of 1-dimensional data, while our model uses 2-dimensional data. Could you provide advice on reshaping the data appropriately for our model?
Here are a few resources I have already consulted:
STM32 MCU AI: How to perform motion sensing on STM32L4 IoT node - https://wiki.st.com/stm32mcu/wiki/AI:How_to_perform_motion_sensing_on_STM32L4_IoTnode#Include_headers_for_STM32Cube-AI
STM32 Machine Learning AI MCU Community Post: How do I send my input data to a neural network on an STM32F4 to get a prediction? - https://community.st.com/t5/stm32-machine-learning-ai-mcu/how-do-i-send-my-input-data-to-a-neural-network-on-an-stm32f4-to/m-p/263197
Unfortunately, these resources haven't provided the specific information I need for uploading and using our custom data on the STM32. I would really appreciate any advice, references, or detailed guides that you might have to share.
Thank you for your time and assistance!
