Edge AI

Hello Community, I've been stuck at this now for some time. I created a datalogger using the tool in NEAI studio, got a .zip file containing the Metadata.json and the neai_logger.bin. The .bin i flashed to the BOXPRO and i get a output using a STLink like the DL tool suggested. When i try then try (Anomaly Detection) Add Signal -> Log Signal from Serial USB and connect to the port that worked in Putty/TeraTerm, i get a warning "No data detected, please check COM-Port and try again"Is there something i missed?all the best

Hello,I'm doing my machelor thesis, and I found a very interesting phenomenon. I deployed a Yolov8n from model zoo inside the N6 Nucleo Board NPU(by modifying the template project from the DK board and Input from the UART with CRC code to make sure the picture is send correctly.) the inference seems to be right. However, when I input the same data (same picture with same crc code), the output can be different!!???? Is this phenomenon right? or its because I messed up sth. when I change the project???????Also even if I deploy this Yolov8n inside CPU without NPU, the outcome is still different when giving the same input. (the reference seems also working correctly.) Is this also correct??? any explanation or documentation for this? (the mAP can have a 20% different when giving 10 same pictures) Also when using a mobilenet v2 the same phenomenon is also found both in CPU and NPU,( top 5 class is same

Hello, I'm currently writing a bachelor thesis regarding the model deployment inside the NPU. I'm writing about the theorical part of the thesis. And I was reading the RM0486 Reference manual. But I found one thing unexpected, from the page 1023, this figure have a I-TCM and D-TCM above the CPU and seems to have a connection with the NPU and CPU. However, I never have any experience with these storage devices... I have the project to make right inference inside the NPU which is modified from the get started project of the DK Board, the CubeIDE project only activated t

  Hi, Im working with the ST EDGE AI Developer Cloud and since the last monday Im having some problems with the benchmark, they got stuck into this infinite loading...  Its still possible to download the final files, but the benchmark tools are really useful to know if the model is going to work "well" in the boards.     

Hi,I have an STM32N6570-DK evaluation kit that I'm using to build a small ML demo. NanoEdge AI studio has the possibility to record a dataset using the Data Logger functionality. However that currently does not support my evaluation kit, or at least I am not able to find such option. I was hoping to use the inbuilt microphone to record sample data for my demo. Will the STM32N6570-DK be supported in the near future, or can I somehow make this work myself without official support?

Hey,I'm using the STEVAL-STWINKT1B sensor to log data, and I was wondering if there's a way to do it without connecting via BLE (through the ST BLE Sensor app on iOS). I know it's possible to log data using NanoEdgeAI — which I’ve successfully done — but I was hoping there might be a simpler method.Specifically, is there a way to just power the sensor with a battery, insert the SD card, and start logging data by pressing a combination of buttons (like holding down the reset button for a few seconds, etc.) — without needing any app or external interface?Best,Anthony

I am Working with the board NUCLEO-N657X0-Q, I need to generate a c code of the Ai model Run in the Board, for that I generated a c code for the STM32N6570-DK to run in my board from St developer zone. Unfortunately i cant build the project file in CUBE IDE i cant figure out what is the problem. 

  Hi everyone, I'm currently working with the STM32N6570-DK and facing challenges in two areas that I’d really appreciate help with: 1. Custom AI Model Deployment (ONNX) We’re experimenting with deploying a small, simple object detection model converted from an ONNX file for testing purposes on the STM32N6570-DK. I’ve managed to get the model analyzed and validated through STM32 tools (X-CUBE-AI), which generated the typical files like network.c, network.h, and low-level AIfiles such as activation buffers, weights, etc. Here’s what I’d like guidance on: How to integrate the generated AI files into a full working project How to feed live camera data into the model How to display the model output (e.g., bounding boxes or classification results)

 Hello,I’m working on a project based on the x-cube-n6-ai-h264-usb-uvc-v1.0.0 example, which originally used the network.c file generated by STedgeAI 2.0. However, I can now only download STedgeAI 2.1, and the code generated by both versions is not compatible. I’ve tried updating the network.c generated by STedgeAI 2.1 into my project, but I’m encountering the following errors during compilation: Description Resource Path Location Type cannot find -lNetworkRuntime1000_CM55_GCC: No such file or directory x-cube-n6-ai-h264-usb-uvc C/C++ Problem Description Resource Path Location Type make: *** [makefile:

Hiiii!I installed NanoEdge AI Studio. try to upload some test data for training. As shown below, sanity check is not taking progress. I am not sure if is related to connection issue. I do encounter following issue as well My license is activated successfully.&

Hi, we found there an AED sample for stm32 n6 npu, but this example doesn't meet our needs. We want do streaming speech recognization on stm32n6 offline, do you have any advice or recommend model we can try on stm32n6. Thanks!

Hi,I'm trying to use the NPU of the STM32N6 to run a onnx model in attachment.The issue I try to fix is that stedgeai is not using the NPU for all operations. Some of them are run in SW instead of HW, like Conv and Gemm and I don't understand what is preventing the acceleration.Here is the stedgeai output:/home/doc/STM32Cube/Repository/Packs/STMicroelectronics/X-CUBE-AI/10.1.0/Utilities/linux/stedgeai generate --target stm32n6 --name network - m denoiser_LSTM_Valetini_nobatchsize_preprocess_simplified_q.onnx --st-neural-art "n6-noextmem@/home/doc/STM32Cube/Repository/Packs/STMicroelectronics/X-CUBE-AI/10.0.0/scripts/N6_scripts/user_neuralar t.json" --verbosity 1 ST Edge AI Core v2.1.0-20194 329b0e98d WARNING: Unsupported keys in the current profile n6-noextmem are ignored: memory_desc > memory_desc is not a valid key anymore, use machine_desc instead >>>> EXECUTING NEURAL ART COMPILER /home/d

Hello.This problem has bothered me a lot.I generated an nbg modle form my tflite model:adam@Ubuntu22:~/STM32MPU_workspace/stedgeai/2.0/Utilities/linux$ ./stedgeai generate --model test.tflite --target stm32mp25ST Edge AI Core v2.0.0-20049PASS: 0%| | 0/2 [00:00<?, ?it/s]Galcore warning: MMU is disabled!Model was successfully compiled to NBG: /home/adam/STM32MPU_workspace/stedgeai/2.0/Utilities/linux/stm32ai_output/test.nbPASS: 100%elapsed time (generate): 39.985sI am not sure if the waring "MMU is disabled" meaning my model will works in low efficiency or not. But I definitely monitored the gpu load while inferenceing and the maximum occupancy rate is 2% only. Then I tried to changed batch size to 32 to improve gpu load. But the result is:[ 9143.030372] [galcore]: GPU[0] core0 hang, automatic recovery.[ 9143.030732] [galcore]: recovery doneI changed the batch size to 6, it'

Hi everyone,I'm having trouble generating a project to run an AI model on the Nucleo-N657X0-Q board.I open STM32CubeMX version 6.14.1, select the board, choose "Secured Application", and then when I select the X-CUBE-AI package, it asks for the ZIP file available here:https://www.st.com/en/development-tools/stedgeai-core.html?ecmp=tt9470_gl_link_feb2019&rt=db&id=DB4255I download it, choose to use X-CUBE-AI in the Application domain, and when I try to select the ONNX model, it asks whether I want to optimize peripherals and clock. At this point, whether I click "Yes" or "No", CubeMX freezes indefinitely.I’ve already tried using CubeMX version 6.13 as well, but it didn’t help.My suspicion is that the problem might be relat

Hi,Here is a picture when I run my app on the STM32N6570-DK in developer mode:It works just fineWhen signing and flashing the bin file, this is when I run the app in Flash mode:

Hello everyone,I am encountering issues while using the X-Cube-AI tool to analyze two models that I recently resized and reduced. Despite thorough testing and troubleshooting, I cannot resolve the errors, and I hope someone here might provide insight.Issue Details:Model Behavior in Python:Both models run perfectly in Python.They work well when tested as .onnx models using other tools.Troubleshooting Steps Taken:Analyzed the .onnx models manually using Netron.app — no issues were identified.

Hello,I have a very similair problem as my last forum post, so here I go again. I tried the fix that worked last time (quantizing using ST AI Developer Cloud), but this didn't fix it this time. The problem:I have a large .onnx model which, untouched, I’m unable to analyze on the ST AI Developer Cloud. After quantizing this larger model using the online ST AI Developer Cloud tool, I now receive the following error when running the analyze command with X-CUBE-AI (I also get this when I try to "Optimize" this quantized model on the ST AI Dev Cloud):>> stedgeai analyze --model anchornet_PerChannel_quant_random_1.onnx --allocate-inputs --allocate-outputs --optimization balanced --target stm32f4 --name network --workspace workspace --output output ST Edge AI Core v1.0.0-19894TOOL ERROR: need more than 2 values to unpackStrangely, the original (unquantized) model can still be analyzed successfully, so it seems the quantization step int

Following are my configuration in detailed. I have analyzed and validated network on MX. However, after compileing code by MDK and flashing .hex on board, i reset the board and do not see any print on virtual tyy.following are the set on MX:RCCSYS

I have been using STM32N6 to conduct model training and deployment for the model zoo. Now, I want to transfer the generated code to my TouchGFX project for embedded use in the CubeIDE environment. However, when I am transferring several files, before the transfer, the original files did not have this error, but after the transfer, there is this error and it is particularly common, mostly for the official-generated code. As follows:  When these files are transferred： After the transplantation was completed, an error occurred：

Hi,I have migrated to STEdgeAI v2.1 and I can't analyze or compile an audio ONNX quantizaied model for STM32N6.Before this, the same model was being analized correctly with version 2.0 of stedgeai.This is the error:C:/ST/STEdgeAI/2.1/Utilities/windows/stedgeai.exe analyze -v3 --target STM32N6 -m "model.onnx"ST Edge AI Core v2.1.0-20194 329b0e98dINTERNAL ERROR: Unexpected conditionThe PASS progress is rising to 11%, but then it fails and stops. There isn't any other log information.Is there any bug with the STEdgeAI new version that explains this behaviour?Thank you,Gilen 

I am using a STM32U575ZIT6 MCU, on a custom board, and I wanted to know which option to choose on the data logger generator screen, I have a ISM330DHCX accelerometer on my board

Dear Community,I'm evaluating whether some of the STM32 ICs are suitable for future projects using simple CNNs (Convolutional Neural Networks).I'm running into problems when trying to analyze a simple CNN model in the ONNX format (converted to ONNX from pyTorch) in the STM32CubeMX AI IDE. I'm using ST Edge AI Core v2.0.0-20049 and once I click on 'analyze' in the network tab, the IDE gives me the error 'INTERNAL ERROR: 'kernel_shape''. Please see the model attached below.I could not find any hint in the docs a

Hello,I have a discovery kit STM32N6570-DK and I am trying to follow the instructions in ST Model Zoo Services so that I can train, evaluate and deploy an object detection model that can detect cars. So I downloaded the Pascal_VOC_2012 dataset, I made some custom data cleanup to keep only the images with the vehicles, (classes  [ bicycle,bus,car,motorbike ]) and on that I used the predefined scripts in ST model zoo to train st_ssd_mobilenet_v1. This went well and the evaluation gave good accuracy results. Then I used the scipts to make predictions on some images. The prediction options "host" and "stedgeai_host" also went well. When I try the option "stedgeai_n6", then the compilation and programming of the board works ok but then the inference freezes. After some debugging I found out that there is a software epoch that performs a Tile operation and this one freezes. In the network_generate_report.txt I noticed some question marks just before this Ti

Hi, When changing from a Tiny YOLOv2 model to ST SSD Mobilenet v1 I strangely got the following error:Bus interface interruptBUSIF0 ERR: 0x10BUSIF1 ERR: 0x0ATON_STD_IRQHandler()@763: irqs=0xlxassertion "0" failed: file "Y:/VM/stm-workspace/fall-guard-v2.0.0/Lib/AI_Runtime/Npu/ll_aton/ll_aton_runtime.c", line 767, function: __LL_ATON_RT_IrqErr I tried other models but only Mobilenet v1 always returns this error. Is there a specific config required? Thanks,Gino

1. X-CUBE_AI forces the use of the bypass clock source and enables both I-Cache and D-Cache.2. Following the advice in https://community.st.com/t5/edge-ai/x-cube-ai-integration-and-clock-errors/td-p/706076 allowed me to avoid the bypass clock source, but the caches remain enabled. Additionally, the SystemClock_Config function enters a hardfault at: RCC_OscInitStruct.HSI48State = RCC_HSI48_ON; RCC_OscInitStruct.PLL.PLLState = RCC_PLL_ON;3. When TouchGFX is not used, X-CUBE_AI can apply templates normally and generates an additional app_x-cube-ai.c file. The code in this file seems self-contained, so the clock initialization issue is likely not related to this. 4. Are there any solutions or workarounds to resolve the clock configuration conflict and disable the forc