Ask questions and find answers on how to deploy, debug, and optimize AI models on ST microcontrollers, microprocessors, and smart sensors.
As stated, I have problem analyzing the ONNX model ported from a pytorch model. The code of the model is simple as follows: class LSTM(nn.Module): def __init__(self, input_size, hidden_size, num_layers, num_output=1): super(LSTM, self)._...
Hi ,I go into the hardfault handler when trying to run the ai_network_run which I call inside my run_inference function which is inside my ADC ISR , then it calls ai_platform_network_process , that is where we get thrown into the HardFault Handler . ...
I built a simple FCNN model based on onnx(regression, 4 input and 4 output), including three hidden layers with 64, 32, 16 nodes, and successfully "validate on target" in STM32 through X-CUBE-AI.Now I want to send(receive) data directly to(from) the...
When I used V4.3.1 before, there was a "5 Emulator" step, but it doesn't exist in V4.6.0.Is Emulator no longer available?
Dear community members,Here’s your chance to win some prizes from ST until the end of 2024! You can join the challenge by sharing your ISPU neural network implementation. We’ll provide instructions and hints during the ISPU webinar held on October 29...
I am trying to use MEMS Studio to configure the Machine Learning Core (MLC) of the ISM330DHCX sensor on both the B-U585I-IOT02A and a custom board, but after installing MEMS Studio and connecting the board, I realized that it is not recognized by the...
I was able to run the Serial emulator in NANOEDGE AI STUDIO Validation, so as the next step, I run [COMPILE LIBRARY] in Deployment and don't know where to put the libneai.a file generated in Project Explore.Also, please let me know if any other setti...
Hi everyone,I am working on implementing an image classification model on an STM32 board using the X-CUBE-AI extension. I am relatively new to embedded software development; my background is primarily in AI and deep learning. While I have managed to ...
The STM32N6 has been officially launched yesterday at the STM32 Summit! The STM32N6 is based on the Arm® Cortex®-M55 running at 800 MHz. It is the first STM32 MCU to embed the ST Neural-ART accelerator™, an in-house developed neural processing ...
Hi,We are trying a very simple deep neural network model with 20 inputs and 3 outputs and want to generate inferences in real-time. We are following the instructions from the document "Getting started with X-CUBE-AI Expansion Package for Artificial I...