AFCI offline kit - Part 5: Python environment for ST model zoo arc-fault scripts
Offline development kit for an arc-fault detection / electrical-fire prevention system (current sensor -> STM32F407 ADC+DMA -> FFT/STFT features -> quantized DNN -> trip). Target offline PC: Windows 10/11 x64, CPU-only Python training.
Contents: Python environment for ST's model zoo services (arc_fault_detection)
ST's stm32ai-modelzoo-services (Part 4) pins its own versions (TensorFlow 2.18, Keras 3.8, PyTorch 2.7.1, ONNX 1.16, ONNX Runtime 1.20, Hydra 1.3.2, MLflow 2.20, neural-compressor 3.4.1, ...), which conflict with the general environment in Part 3. So it gets its own virtual environment.
wheels_stm32ai_modelzoo_py312/: 176 wheels for CPython 3.12 / win_amd64 (ST recommends Python 3.12.9; the 3.12.10 installer in Part 2 works).requirements_original_from_ST.txt: ST'srequirements.txtas published.requirements_stm32ai_modelzoo_windows_lock.txt: exact pinned set used here. It was checked by resolving it from these local wheels only (no internet) for Windows/Python 3.12.install_offline.bat: rebuilds split wheels, creates%USERPROFILE%\stzoo-venv, installs everything with--no-index.
Differences from ST's list (Windows/offline only):
pesq==0.0.4left out: no Windows wheel, needs a C compiler, and it's only used by ST's speech_enhancement use case.pycocotools2.0.11 instead of 2.0.7: 2.0.7 has no Windows wheel for Python 3.12; it's only pulled in by neural-compressor and used by the vision use cases.antlr4-python3-runtime 4.9.3andwget 3.2only exist as source on PyPI; they were built here into pure-Pythonpy3-none-anywheels.
Note: the ST Edge AI Core / STM32Cube AI Studio executables needed for the benchmarking modes are not included (see Part 7 checklist). Training, evaluation, quantization and prediction run fully offline with this environment.
Rebuilding split files
Files over 100 MB were split into *.part001, *.part002, ... pieces. After downloading the whole repo:
- Windows:
powershell -ExecutionPolicy Bypass -File .\join_parts.ps1 - Linux/macOS:
bash join_parts.sh
Both scripts rebuild the files and check them against SHA256SUMS.txt.
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wheels_stm32ai_modelzoo_py312/threadpoolctl-3.7.0-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/tifffile-2026.3.3-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/timm-1.0.19-py3-none-any.whl |
2.4 MB | - |
wheels_stm32ai_modelzoo_py312/torch-2.7.1-cp312-cp312-win_amd64.whl |
206.0 MB | 3 |
wheels_stm32ai_modelzoo_py312/torchaudio-2.7.1-cp312-cp312-win_amd64.whl |
2.4 MB | - |
wheels_stm32ai_modelzoo_py312/torchvision-0.22.1-cp312-cp312-win_amd64.whl |
1.6 MB | - |
wheels_stm32ai_modelzoo_py312/tqdm-4.67.1-py3-none-any.whl |
76.7 KB | - |
wheels_stm32ai_modelzoo_py312/truststore-0.10.5-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/typing_extensions-4.16.0-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/typing_inspection-0.4.4-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/tzdata-2026.6-py2.py3-none-any.whl |
340.0 KB | - |
wheels_stm32ai_modelzoo_py312/urllib3-1.26.13-py2.py3-none-any.whl |
137.3 KB | - |
wheels_stm32ai_modelzoo_py312/waitress-3.0.2-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/wcwidth-0.9.4-cp310-abi3-win_amd64.whl |
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wheels_stm32ai_modelzoo_py312/werkzeug-3.1.9-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/wget-3.2-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/wheel-0.48.0-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/win32_setctime-1.2.1-py3-none-any.whl |
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wheels_stm32ai_modelzoo_py312/wrapt-2.5.2-cp312-cp312-win_amd64.whl |
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wheels_stm32ai_modelzoo_py312/zipp-4.1.2-py3-none-any.whl |
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Each file keeps the license of its original publisher (see the notes above).
Master index
This is one of 19 repos (AFCI_part1 … AFCI_part19). Overview of all parts: AFCI_part6 / 00_START_HERE_MASTER_INDEX.md · Installation: AFCI_part6 / 00_INSTALLATION_GUIDE.md
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