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Error training object_detection using model-zoo-services
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2024-12-31 06:25 AM
Im doing a proof-of-concept on trying to run a model on the STM32N6 that does object-detection.
For this, Im following this guide: https://github.com/STMicroelectronics/stm32ai-modelzoo-services/blob/main/object_detection/src/training/README.md
1. `!git clone https://github.com/STMicroelectronics/stm32ai-modelzoo-services.git`
2. `!pip install -r stm32ai-modelzoo-services/requirements.txt`
3. Im using a Pascal VOC XML dataset which Im converting using the provided scripts with the different config files as attachment in a zip-file
4. `!python converter.py --config-name dataset_config_train.yaml`
5. `!python converter.py --config-name dataset_config_validation.yaml`
6. `!python dataset_create_tfs.py --config-name dataset_config_tfs.yaml`
7. `!python stm32ai_main.py`
This gives the following error (full stacktrace as attachment): `ValueError: Can't convert Python sequence with mixed types to Tensor.`.
As I believe Im following the steps correctly, Im unsure what Im missing to correctly train this model?
Labels:
- Labels:
-
Model Zoo
-
ST Edge AI Core
-
STM32N6
2 REPLIES 2
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2025-01-03 01:07 AM
Hello,
Could you please share your installed python packages using :
!pip list
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2025-01-03 03:43 AM
Package Version
---------------------------- ------------
absl-py 2.1.0
alembic 1.14.0
antlr4-python3-runtime 4.9.3
appdirs 1.4.4
archspec 0.2.2
astunparse 1.6.3
audioread 3.0.1
blinker 1.9.0
boltons 23.1.1
Brotli 1.1.0
cachetools 5.5.0
certifi 2024.12.14
cffi 1.16.0
charset-normalizer 3.3.2
click 8.1.8
cloudpickle 2.2.1
cmaes 0.11.1
colorama 0.4.5
coloredlogs 15.0.1
colorlog 6.9.0
conda 23.11.0
conda-libmamba-solver 23.12.0
conda-package-handling 2.2.0
conda_package_streaming 0.9.0
contourpy 1.3.1
cycler 0.12.1
databricks-cli 0.18.0
decorator 5.1.1
distro 1.8.0
docker 6.1.3
entrypoints 0.4
Flask 2.3.3
flatbuffers 2.0.7
fonttools 4.55.3
gast 0.6.0
gitdb 4.0.12
GitPython 3.1.44
google-auth 2.37.0
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
greenlet 3.1.1
grpcio 1.68.1
gunicorn 20.1.0
h5py 3.12.1
humanfriendly 10.0
hydra-core 1.3.2
idna 3.6
imageio 2.36.1
imgaug 0.4.0
importlib-metadata 6.11.0
itsdangerous 2.2.0
Jinja2 3.1.5
joblib 1.2.0
jsonpatch 1.33
jsonpointer 2.4
keras 2.8.0
Keras-Preprocessing 1.1.2
kiwisolver 1.4.8
larq 0.13.3
lazy_loader 0.4
libclang 18.1.1
libmambapy 1.5.5
librosa 0.10.0.post2
llvmlite 0.43.0
Mako 1.2.4
mamba 1.5.5
Markdown 3.7
MarkupSafe 3.0.2
marshmallow 3.20.1
matplotlib 3.6.2
menuinst 2.0.1
mlflow 2.3.0
mpmath 1.3.0
msgpack 1.1.0
munch 2.5.0
networkx 3.4.2
numba 0.60.0
numpy 1.23.4
nvidia-cublas-cu11 11.11.3.6
nvidia-cudnn-cu11 8.6.0.163
oauthlib 3.2.2
omegaconf 2.3.0
onnx 1.12.0
onnxconverter-common 1.13.0
onnxruntime 1.15.1
opencv-python 4.6.0.66
opt_einsum 3.4.0
optuna 3.1.1
packaging 23.2
pandas 1.5.3
pillow 11.1.0
pip 23.3.2
platformdirs 4.1.0
pluggy 1.3.0
pooch 1.6.0
protobuf 3.19.6
pyarrow 11.0.0
pyasn1 0.6.1
pyasn1_modules 0.4.1
pycosat 0.6.6
pycparser 2.21
PyJWT 2.10.1
pyparsing 3.2.1
pyserial 3.5
PySocks 1.7.1
python-dateutil 2.9.0.post0
pytz 2023.4
PyYAML 6.0.2
querystring-parser 1.2.4
requests 2.28.2
requests-oauthlib 2.0.0
rsa 4.9
ruamel.yaml 0.18.5
ruamel.yaml.clib 0.2.7
scikit-image 0.24.0
scikit-learn 1.2.2
scipy 1.13.1
seaborn 0.12.2
setuptools 68.2.2
shapely 2.0.6
six 1.17.0
skl2onnx 1.14.0
smmap 5.0.2
soundfile 0.13.0
soxr 0.5.0.post1
SQLAlchemy 2.0.36
sqlparse 0.5.3
sympy 1.13.3
tabulate 0.9.0
tensorboard 2.8.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow 2.8.3
tensorflow-estimator 2.8.0
tensorflow-io-gcs-filesystem 0.37.1
termcolor 2.5.0
terminaltables 3.1.10
tf2onnx 1.14.0
threadpoolctl 3.5.0
tifffile 2024.12.12
tqdm 4.65.0
truststore 0.8.0
typing_extensions 4.12.2
urllib3 1.26.13
websocket-client 1.8.0
Werkzeug 3.1.3
wget 3.2
wheel 0.42.0
wrapt 1.17.0
xmlrunner 1.7.7
zipp 3.21.0
zstandard 0.22.0