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@docker-audio-tools

docker-audio-tools

README.md

Docker Audio Tools

Ready-to-run Dockerfiles for audio processing and ML/DSP workloads. Build once, run anywhere (local CPU/GPU or in a Cloud environment like AWS/GCP).

What you get

  • Batteries-included images for common audio/ML pipelines with pinned versions for reproducibility..
  • CPU/GPU support when available.
  • Exact stack per image (Python, CUDA/cuDNN, PyTorch, torchaudio/vision, librosa, NumPy, SciPy, FFmpeg) + OS base.
  • Cloud-ready: sample GCP job specs to deploy at scale.
  • CPU/GPU variants with matching CUDA toolkits.

Quick start (local)

# Build a tool/image
docker build -t audio-tools:latest .

Pinned Loading

  1. spleeter-docker-job spleeter-docker-job Public

    Builds docker image and deploys on GCP to avoid M1 chip problems

    Python

  2. drumsep-docker-job drumsep-docker-job Public

    Forked from inagoy/drumsep

    Hybrid Demucs model for drum separation

    Python

  3. all-in-one-docker-gpu-job all-in-one-docker-gpu-job Public

    Forked from JuanCruzC97/all-in-one

    All-In-One Music Structure Analyzer (demucs stems splitter + song structure). GPU job @ GCP

    Python 1

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