---

name: evaluation description: "Evaluate Spleeter models on MUSDB-style datasets, dependency gates, output metrics, fixtures, and evaluation troubleshooting." metadata: disco-role: operating disable-model-invocation: true license: MIT

Spleeter evaluation router

Use this sub-skill when the task mentions spleeter evaluate, MUSDB or MUSDB-like test sets, musdb/museval, SDR/SAR/SIR/ISR, evaluation output directories, fake evaluation fixtures, or evaluation failures related to model downloads and caches.

Do not use this sub-skill for generic source separation recipes; route those to separation. Do not use it for training CSV/config construction except for a tiny evaluation fixture; route training work to training.

Fast route

User intent	Go to
Install or check evaluation prerequisites	Evaluation workflow and root installation/runtime
Run spleeter evaluate on a MUSDB-style dataset	Evaluation workflow
Understand mus_dir layout or distinguish ground truth from estimates	MUSDB format and metrics
Interpret SDR/SAR/SIR/ISR metrics or compiled medians	Metric compilation behavior
Make a tiny deterministic fixture for smoke/layout checks	scripts/create_eval_fixture.py and fixture notes
Debug exit code 10, missing stems, cache/network, JSON metrics, or slow runs	Evaluation troubleshooting
Compare evaluation CLI flags with the global CLI catalog	Root CLI reference
Select model descriptors, local configs, or cache/network policy	Root models/configuration

Core command shape

spleeter evaluate \
  --mus_dir MUSDB_ROOT \
  --output_path OUTPUT \
  --params_filename spleeter:4stems \
  --adapter spleeter.audio.ffmpeg.FFMPEGProcessAudioAdapter \
  --mwf \
  --verbose

python -m spleeter evaluate ... is equivalent when the console entry point is unavailable. Short forms supported by the CLI include -o/--output_path, -p/--params_filename, and -a/--adapter. --mus_dir, --mwf, and --verbose are long-form options.

Keep these boundaries clear

• MUSDB_ROOT/test/<song>/mixture.wav is the mixture input that Spleeter separates.
• MUSDB_ROOT/test/<song>/{vocals,drums,bass,other}.wav are ground-truth source files required by museval; they are not Spleeter outputs.
• Evaluation writes Spleeter estimates under OUTPUT/audio/test/<song>/ and metric JSON files under OUTPUT/metrics/test/.
• Base Spleeter installs may not include evaluation dependencies. If musdb or museval cannot import, Spleeter logs the missing extras and exits with status 10.
• GPU use is optional acceleration only; the verified runtime path is TensorFlow CPU.

Evidence basis: spleeter/__main__.py, spleeter/options.py, tests/test_eval.py, pyproject.toml, README.md, and configs/musdb_config.json.