mirror of
https://github.com/TaterTotterson/microWakeWord-Trainer-Nvidia-Docker.git
synced 2026-06-12 20:10:19 -06:00
74b36885b5
Since this is a pure Python environment, the CUDA toolkit isn't really necessary. The various Python packages that can use CUDA will download and install the CUDA dependencies they need. This shaves off at least 8gb from the final image. The Python package install order needed to be tweaked to ensure onnxruntime, tensorflow and torch are installed in that order. Any other order results in dependent cuda package clashes. Resolves: #12
29 lines
684 B
Plaintext
29 lines
684 B
Plaintext
# --- Core training (Microwakeword) ---
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numpy==1.26.4
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scipy==1.12.0
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librosa==0.10.2.post1
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soundfile==0.12.1
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soxr==0.5.0.post1
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audiomentations==0.38.0
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webrtcvad==2.0.10
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tqdm==4.67.1
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scikit-learn==1.6.0
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numba==0.60.0
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joblib==1.4.2
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pandas==2.2.3
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pymicro_features @ git+https://github.com/puddly/pymicro-features@e1d3f88183e12bb8af2df9e399ea157af7393762
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audio-metadata @ git+https://github.com/whatsnowplaying/audio-metadata@d4ebb238e6a401bb1a5aaaac60c9e2b3cb30929f
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bitstruct==8.19.0
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# --- Piper sample generation ---
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piper-tts>=1.2.0
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piper-phonemize-cross==1.2.1
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# --- Notebook / tooling ---
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ipykernel==6.29.5
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jupyterlab==4.3.4
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ipywidgets==8.1.5
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matplotlib-inline==0.1.7
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rich==13.9.4
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