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STM32N6570-DK model zoo delpoyment error

wwnsok2
Associate II
I followed the steps in the link below and then ran main.py, but I encountered the following error. I don’t know how to resolve it. I also set the BOOT0 and BOOT1 switches on the board, but I still get the same result.
 
 
(st_zoo) C:\Users\wwnso\Desktop\STM\stm32ai-modelzoo-services\object_detection\src>python stm32ai_main.py --config-path ./config_file_examples/ --config-name deployment_n6_ssd_mobilenet_v2_fpnlite_config.yaml 2025-03-14 02:35:59.704524: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 2025-03-14 02:35:59.705273: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. [WARNING] The usable GPU memory is unlimited. Please consider setting the 'gpu_memory_limit' attribute in the 'general' section of your configuration file. [INFO] : Running deployment operation mode [INFO] : The random seed for this simulation is 123 INFO: Created TensorFlow Lite XNNPACK delegate for CPU. [INFO] : Generating C header file for Getting Started... [INFO] : This TFLITE model doesnt contain a post-processing layer loading model.. model_path="C:/Users/wwnso/Desktop/STM/stm32ai-modelzoo/object_detection/ssd_mobilenet_v2_fpnlite/ST_pretrainedmodel_public_dataset/coco_2017_person/ssd_mobilenet_v2_fpnlite_035_192/ssd_mobilenet_v2_fpnlite_035_192_int8.tflite" loading conf file.. "../../application_code/object_detection/STM32N6/stmaic_STM32N6570-DK.conf" config="None" "n6 release" configuration is used [INFO] : Selected board : "STM32N6570-DK Getting Started Object Detection (STM32CubeIDE)" (stm32_cube_ide/n6 release/stm32n6) [INFO] : Compiling the model and generating optimized C code + Lib/Inc files: C:/Users/wwnso/Desktop/STM/stm32ai-modelzoo/object_detection/ssd_mobilenet_v2_fpnlite/ST_pretrainedmodel_public_dataset/coco_2017_person/ssd_mobilenet_v2_fpnlite_035_192/ssd_mobilenet_v2_fpnlite_035_192_int8.tflite setting STM.AI tools.. root_dir="", req_version="" Cube AI Path: "C:\ST\STEdgeAI\2.0\Utilities\windows\stedgeai.exe". [INFO] : Offline CubeAI used; Selected tools: 10.0.0 (x-cube-ai pack) loading conf file.. "../../application_code/object_detection/STM32N6/stmaic_STM32N6570-DK.conf" config="None" "n6 release" configuration is used compiling... "ssd_mobilenet_v2_fpnlite_035_192_int8_tflite" session model_path : ['C:/Users/wwnso/Desktop/STM/stm32ai-modelzoo/object_detection/ssd_mobilenet_v2_fpnlite/ST_pretrainedmodel_public_dataset/coco_2017_person/ssd_mobilenet_v2_fpnlite_035_192/ssd_mobilenet_v2_fpnlite_035_192_int8.tflite'] tools : 10.0.0 (x-cube-ai pack) target : "STM32N6570-DK Getting Started Object Detection (STM32CubeIDE)" (stm32_cube_ide/n6 release/stm32n6) options : --st-neural-art default@../../application_code/object_detection/STM32N6/Model/user_neuralart.json --input-data-type uint8 --inputs-ch-position chlast "series" value is not coherent.. stm32n6 != stm32n6npu results -> RAM=621,048 IO=110,592:153,800 WEIGHTS=1,618,465 MACC=0 RT_RAM=1,773 RT_FLASH=632,615 LATENCY=0.000 [INFO] : Optimized C code + Lib/Inc files generation done. [INFO] : Building the STM32 c-project.. deploying the c-project.. "STM32N6570-DK Getting Started Object Detection (STM32CubeIDE)" (stm32_cube_ide/n6 release/stm32n6) updating.. n6 release -> s:copying file.. "network.c" to ....\application_code\object_detection\STM32N6\Model\network.c -> s:copying file.. "network_ecblobs.h" to ....\application_code\object_detection\STM32N6\Model\network_ecblobs.h -> s:copying file.. "network_atonbuf.xSPI2.raw" to ....\application_code\object_detection\STM32N6\Model\network_atonbuf.xSPI2.raw -> s:removing dir.. ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Lib\GCC\ARMCortexM55 -> s:copying dir.. "ARMCortexM55" to ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Lib\GCC\ARMCortexM55 -> s:removing dir.. ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Inc -> s:copying dir.. "Inc" to ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Inc -> s:removing dir.. ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Npu\ll_aton -> s:copying dir.. "ll_aton" to ....\application_code\object_detection\STM32N6\Middlewares\AI_Runtime\Npu\ll_aton -> u:copying file.. "app_config.h" to ....\application_code\object_detection\STM32N6\Inc\app_config.h -> updating cproject file "C:\Users\wwnso\Desktop\STM\stm32ai-modelzoo-services\application_code\object_detection\STM32N6\STM32CubeIDE" with "NetworkRuntime1000_CM55_GCC.a" building.. n6 release flashing.. n6 release STM32N6570-DK [returned code = 1 - FAILED] Board programming failed: "ST-LINK error (DEV_CONNECT_ERR)" [INFO] deployment complete [INFO] : Please on STM32N6570-DK toggle the boot switches to the left and power cycle the board.
1 ACCEPTED SOLUTION

Accepted Solutions

Hello @wwnsok2 ,

 

Can you go to your model zoo folder then /application_code. 

Next got to the folder of the use case you are working with (image classif, object detection etc)

Then /STM32N6/STM32CubeIDE and open .project 

 

Set the N6 boot pins to the right and connect it to the pc.

Click Build then run on stm32CubeIDE.

 

If everything works, set the pins to the left this time and unplug/plug the N6.

 

Let me know how it went.

Julian


In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.

View solution in original post

7 REPLIES 7
Julian E.
ST Employee

Hello @wwnsok2 ,

 

It seems to be a STM32CubeProgrammer Error.

What version of STM32CubeIDE and STM32CubeProgrammer are you using?

What is your OS?

Can you also please send me your user_config.yaml

 

Have a good day

Julian


In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.

i'm using on

STM32CubeIDE 1.18.0

STM32CubeProgrammer 2.19.0

Windows 11

 

Since attaching .yaml files is not supported, I have converted it to a .zip file and attached it.

Thanks for the information.

 

Can you try to open STM32CubeProgrammer, plug your board and click connect

Do you get an error?

 

Do you use a USB C cable to USB C? 

I have seen other people with other board having the same issue because of power supply. 

In the case of the N6, I've heard about issue if not using USB C to USB C.

 

Julian


In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.

Please use formatting in your original post.

No specific language (for instance terminal output):

unsigned_char_array_0-1741092281956.png

A programming specific language (such as C/C++):

unsigned_char_array_1-1741092366689.png

 

Kudo posts if you have the same problem and kudo replies if the solution works.
Click "Accept as Solution" if a reply solved your problem. If no solution was posted please answer with your own.

 

When I press the "Connect" button in STM32Cube Programmer, the connection is established. The model name is also detectable. I’ve updated the ST-Link driver firmware, but the same message still appears. Additionally, I’ve tried both a C-to-C cable and a C-to-A cable, but both produce the same result. 
Also, the boot switch is set according to the manual. thank you.

Hello @wwnsok2 ,

 

Can you go to your model zoo folder then /application_code. 

Next got to the folder of the use case you are working with (image classif, object detection etc)

Then /STM32N6/STM32CubeIDE and open .project 

 

Set the N6 boot pins to the right and connect it to the pc.

Click Build then run on stm32CubeIDE.

 

If everything works, set the pins to the left this time and unplug/plug the N6.

 

Let me know how it went.

Julian


In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.

thank you very much it works very well.