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When running the command: python stm32ai_main.py --config-path--config-name，error:the same file

llcc
Associate III

‎2025-05-15 8:42 PM

D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src>python stm32ai_main.py --config-path ./config_file_examples/ --config-name my_deployment_n6_ssd_mobilenet_v2_fpnlite_config.yaml
2025-05-16 11:30:17.018496: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2025-05-16 11:30:17.018747: 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] : ClearML config check
[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="D:/stm32aibushu/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: D:/stm32aibushu/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: "D:\stm32edgeai\stedgeai\2.1\Utilities\windows\stedgeai.exe".
[INFO] : Offline CubeAI used; Selected tools: 10.1.0 (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 : ['D:/stm32aibushu/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 : 10.1.0 (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
[returned code = 4294967295 - FAILED]
$ cwd: None
$ args: D:\stm32edgeai\stedgeai\2.1\Utilities\windows\stedgeai.exe generate --target stm32n6 -m D:/stm32aibushu/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 --output D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\experiments_outputs\2025_05_16_11_30_18 --workspace D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\experiments_outputs\2025_05_16_11_30_18 --st-neural-art default@../../application_code/object_detection/STM32N6/Model/user_neuralart.json --input-data-type uint8 --inputs-ch-position chlast
ST Edge AI Core v2.1.0-20194 329b0e98d

PASS: 0%| | 0/92 [00:00<?, ?it/s]
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PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

>>>> EXECUTING NEURAL ART COMPILER

PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

D:/stm32edgeai/stedgeai/2.1/Utilities/windows/atonn.exe -i "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/ssd_mobilenet_v2_fpnlite_035_192_int8_OE_3_2_0.onnx" --json-quant-file "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/ssd_mobilenet_v2_fpnlite_035_192_int8_OE_3_2_0_Q.json" -g "network.c" --load-mdesc "D:/stm32edgeai/stedgeai/2.1/Utilities/configs/stm32n6.mdesc" --load-mpool "D:/stm32aibushu/stm32ai-modelzoo-services/application_code/object_detection/STM32N6/Model/my_mpools/stm32n6-app2.mpool" --save-mpool-file "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/neural_art__network/stm32n6-app2.mpool" --out-dir-prefix "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/neural_art__network/" --all-buffers-info --no-hw-sw-parallelism --cache-maintenance --enable-virtual-mem-pools --native-float --optimization 3 --Os --Omax-ca-pipe 4 --Ocache-opt --enable-epoch-controller --output-info-file "c_info.json"

PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

<<<< DONE EXECUTING NEURAL ART COMPILER

PASS: 91%|█████████▏| 84/92 [00:37<00:15, 1.92s/it]
PASS: 92%|█████████▏| 85/92 [00:38<00:17, 2.55s/it]


LOAD ERROR: WindowsPath('D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/network.h') and WindowsPath('D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/network.h') are the same file
$ cwd: None
$ args: D:\stm32edgeai\stedgeai\2.1\Utilities\windows\stedgeai.exe generate --target stm32n6 -m D:/stm32aibushu/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 --output D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\experiments_outputs\2025_05_16_11_30_18 --workspace D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\experiments_outputs\2025_05_16_11_30_18 --st-neural-art default@../../application_code/object_detection/STM32N6/Model/user_neuralart.json --input-data-type uint8 --inputs-ch-position chlast
ST Edge AI Core v2.1.0-20194 329b0e98d

PASS: 0%| | 0/92 [00:00<?, ?it/s]
PASS: 12%|█▏ | 11/92 [00:16<01:59, 1.48s/it]
PASS: 13%|█▎ | 12/92 [00:17<01:56, 1.46s/it]
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PASS: 80%|████████ | 74/92 [00:27<00:02, 6.09it/s]
PASS: 82%|████████▏ | 75/92 [00:27<00:02, 5.93it/s]
PASS: 84%|████████▎ | 77/92 [00:27<00:02, 7.07it/s]
PASS: 85%|████████▍ | 78/92 [00:27<00:02, 6.52it/s]
PASS: 86%|████████▌ | 79/92 [00:27<00:02, 5.91it/s]
PASS: 87%|████████▋ | 80/92 [00:28<00:02, 5.71it/s]
PASS: 88%|████████▊ | 81/92 [00:28<00:01, 5.53it/s]
PASS: 89%|████████▉ | 82/92 [00:28<00:01, 5.46it/s]
PASS: 90%|█████████ | 83/92 [00:28<00:01, 5.36it/s]
PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

>>>> EXECUTING NEURAL ART COMPILER

PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

D:/stm32edgeai/stedgeai/2.1/Utilities/windows/atonn.exe -i "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/ssd_mobilenet_v2_fpnlite_035_192_int8_OE_3_2_0.onnx" --json-quant-file "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/ssd_mobilenet_v2_fpnlite_035_192_int8_OE_3_2_0_Q.json" -g "network.c" --load-mdesc "D:/stm32edgeai/stedgeai/2.1/Utilities/configs/stm32n6.mdesc" --load-mpool "D:/stm32aibushu/stm32ai-modelzoo-services/application_code/object_detection/STM32N6/Model/my_mpools/stm32n6-app2.mpool" --save-mpool-file "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/neural_art__network/stm32n6-app2.mpool" --out-dir-prefix "D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/neural_art__network/" --all-buffers-info --no-hw-sw-parallelism --cache-maintenance --enable-virtual-mem-pools --native-float --optimization 3 --Os --Omax-ca-pipe 4 --Ocache-opt --enable-epoch-controller --output-info-file "c_info.json"

PASS: 91%|█████████▏| 84/92 [00:34<00:15, 1.92s/it]

<<<< DONE EXECUTING NEURAL ART COMPILER

PASS: 91%|█████████▏| 84/92 [00:37<00:15, 1.92s/it]
PASS: 92%|█████████▏| 85/92 [00:38<00:17, 2.55s/it]


LOAD ERROR: WindowsPath('D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/network.h') and WindowsPath('D:/stm32aibushu/stm32ai-modelzoo-services/object_detection/src/experiments_outputs/2025_05_16_11_30_18/network.h') are the same file
Error executing job with overrides: []
Traceback (most recent call last):
File "D:\anaconda\lib\site-packages\clearml\binding\hydra_bind.py", line 230, in _patched_task_function
return task_function(a_config, *a_args, **a_kwargs)
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\stm32ai_main.py", line 228, in main
process_mode(cfg)
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\stm32ai_main.py", line 102, in process_mode
deploy(cfg)
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\../deployment\deploy.py", line 111, in deploy
stm32ai_deploy_stm32n6(target=board, stlink_serial_number=stlink_serial_number, stm32ai_version=stm32ai_version, c_project_path=c_project_path,
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\../../common/deployment\common_deploy.py", line 469, in stm32ai_deploy_stm32n6
stmaic_local_call(session)
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\../../common/deployment\common_deploy.py", line 443, in stmaic_local_call
stmaic.compile(session=session, options=opt, target=session._board_config)
File "D:\stm32aibushu\stm32ai-modelzoo-services\object_detection\src\../../common\stm32ai_local\compile.py", line 208, in cmd_compile
raise Exception('Error during compilation')
Exception: Error during compilation

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

0 Kudos
29 REPLIES 29
LQC_
Associate III
In response to llcc

‎2025-05-21 1:10 AM - last edited on ‎2025-06-30 12:07 AM by Community manager

Not yet, I use food classification and image classification.

 

*This post has been translated from Chinese to comply with the ST Community guidelines.

0 Kudos
llcc
Associate III
In response to LQC_

‎2025-05-21 1:14 AM - last edited on ‎2025-06-30 12:08 AM by Community manager

Ok ok, please for version 3.1.0 do you still follow that tutorial to configure the file and run the process, I see that there is no stm32ai_main.py file in the src folder of that tutorial but in the previous folder of src there is this .py file, thank you for your help!

 

*This post has been translated from Chinese to comply with the ST Community guidelines

0 Kudos
LQC_
Associate III
In response to llcc

‎2025-05-21 1:17 AM - last edited on ‎2025-06-30 12:09 AM by Community manager

No, the stm32ai_main.py that is executed at the upper src level, I have a question about what to do next after executing the script. I followed other people's tutorials to burn the boot file, the model file, and the bin file in that order, to no avail. Thanks for sharing if you know!

 

*This post has been translated from Chinese to comply with the ST Community guidelines

0 Kudos
llcc
Associate III
In response to LQC_

‎2025-05-21 1:23 AM - last edited on ‎2025-06-30 12:09 AM by Community manager

Sorry, I haven't run that far yet, I'm still stuck on this screen

 

*This post has been translated from Chinese to comply with the ST Community guidelines

0 Kudos
LQC_
Associate III
In response to llcc

‎2025-05-21 1:30 AM - last edited on ‎2025-06-30 12:11 AM by Community manager

Well, I didn't use object_detection instead, you can try a different example like image_classification and see if you still have this error.

By:【新提醒】【STM32N6570-DK测评】3.快速实现AI目标检测应用 - 边缘AI - 电子工程世界-论坛

*This post has been translated from Chinese to comply with the ST Community guidelines

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LQC_
Associate III
In response to llcc

‎2025-05-21 2:29 AM - last edited on ‎2025-06-30 12:10 AM by Community manager

I just tried object_detection and didn't get the error you just did.

Here is my user_config.yaml file

*This post has been translated from Chinese to comply with the ST Community guidelines

general:
  model_type: ssd_mobilenet_v2_fpnlite # 'st_ssd_mobilenet_v1', 'ssd_mobilenet_v2_fpnlite', 'tiny_yolo_v2', 'st_yolo_lc_v1', 'st_yolo_x', 'yolo_v8'
  # path to a `.tflite` or `.onnx` file.
  model_path: ../../stm32ai-modelzoo/object_detection/ssd_mobilenet_v2_fpnlite/ST_pretrainedmodel_public_dataset/coco_2017_80_classes/ssd_mobilenet_v2_fpnlite_100_256/ssd_mobilenet_v2_fpnlite_100_256_int8.tflite

operation_mode: deployment

dataset:
  name: coco_2017_80_classes
  class_names: [person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush]

preprocessing:
  resizing:
    interpolation: bilinear
    aspect_ratio: crop
  color_mode: rgb # rgb, bgr

postprocessing:
  confidence_thresh: 0.6
  NMS_thresh: 0.5
  IoU_eval_thresh: 0.4
  yolo_anchors: # Only applicable for YoloV2
  max_detection_boxes: 10

tools:
  stedgeai:
    version: 10.1.0
    optimization: balanced
    on_cloud: False # Not Available For STM32N6
    path_to_stedgeai: D:/16_STEdgeAI/2.1/Utilities/windows/stedgeai.exe
  path_to_cubeIDE: D:/15_STM32CubeIDE_1.18.0/stm32cubeide1.17/STM32CubeIDE_1.17.0/STM32CubeIDE/stm32cubeide.exe

deployment:
  c_project_path: ../application_code/object_detection/STM32N6/
  IDE: GCC
  verbosity: 1
  hardware_setup:
    serie: STM32N6
    board: STM32N6570-DK

hydra:
  run:
    dir: ./src/experiments_outputs/${now:%Y_%m_%d_%H_%M_%S}

mlflow:
  uri: ./src/experiments_outputs/mlruns
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LQC_
Associate III
In response to llcc

‎2025-05-21 2:31 AM - last edited on ‎2025-06-30 12:00 AM by Community manager

Did you check your user_config.yaml file, is the name field missing?

LQC__0-1747819881630.png

*This post has been translated from Chinese to comply with the ST Community guidelines.

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llcc
Associate III
In response to LQC_

‎2025-05-21 2:37 AM - last edited on ‎2025-06-30 12:05 AM by Community manager 

general:
  model_type: ssd_mobilenet_v2_fpnlite # 'st_ssd_mobilenet_v1', 'ssd_mobilenet_v2_fpnlite', 'tiny_yolo_v2', 'st_yolo_lc_v1', 'st_yolo_x', 'yolo_v8'
  # path to a `.tflite` or `.onnx` file.
  model_path: D:/stm32aibushu/stm32ai-modelzoo/object_detection/ssd_mobilenet_v2_fpnlite/ST_pretrainedmodel_public_dataset/coco_2017_80_classes/ssd_mobilenet_v2_fpnlite_100_256/ssd_mobilenet_v2_fpnlite_100_256_int8.tflite



operation_mode: deployment

dataset:
  name: coco_2017_80_classes
  class_names: [person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush]

preprocessing:
  resizing:
    interpolation: bilinear
    aspect_ratio: crop
  color_mode: rgb # rgb, bgr

postprocessing:
  confidence_thresh: 0.6
  NMS_thresh: 0.5
  IoU_eval_thresh: 0.4
  yolo_anchors: # Only applicable for YoloV2
  max_detection_boxes: 10

tools:
  stedgeai:
    version: 10.1.0
    optimization: balanced
    on_cloud: False # Not Available For STM32N6
    path_to_stedgeai: D:/stm32edgeai/stedgeai/2.1/Utilities/windows/stedgeai.exe
  path_to_cubeIDE: D:/Stm32Cubbeide/STM32CubeIDE_1.16.0/STM32CubeIDE/stm32cubeide.exe

deployment:
  c_project_path: ../application_code/object_detection/STM32N6/
  IDE: GCC
  verbosity: 1
  hardware_setup:
    serie: STM32N6
    board: STM32N6570-DK

hydra:
  run:
    dir: ./src/experiments_outputs/${now:%Y_%m_%d_%H_%M_%S}

mlflow:
  uri: ./src/experiments_outputs/mlruns

There's no shortage of it. It's mine. "D:\stm32aibushu\stm32ai-modelzoo-services-3.1.0\object_detection\src\config_file_examples\my_deployment_n6_ssd_mobilenet_v2_fpnlite_config.yaml" file.

*This post has been translated from Chinese to comply with the ST Community guidelines.

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llcc
Associate III
In response to LQC_

‎2025-05-21 2:38 AM - last edited on ‎2025-06-30 12:10 AM by Community manager

It doesn't report an error either, it just stays at that step with no further output.

 

*This post has been translated from Chinese to comply with the ST Community guidelines

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llcc
Associate III
In response to LQC_

‎2025-05-21 2:39 AM - last edited on ‎2025-06-30 12:03 AM by Community manager

python stm32ai_main.py --config-path ./src/config_file_examples/ --config-name my_deployment_n6_ssd_mobilenet_v2_fpnlite_config.yam This is the command I ran.

 

*This post has been translated from Chinese to comply with the ST Community guidelines.

 

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