mir-eval
Common metrics for common audio/music processing tasks.
Decision gist · record as of 2026-08-14
Yes. mir_eval is actively maintained, has no known vulnerabilities, installs with low friction, and provides standard reference implementations for music information retrieval metrics. Install it if you are evaluating audio or music processing algorithms and need reproducible metric computation.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction installation with three stable dependencies (numpy, scipy, decorator).
- Active maintenance with recent commits and a 710-star repository; last release was 2025-02-25.
License · maintenance · safety
MIT (permissive) — MIT license is permissive, allowing use in commercial and proprietary projects with minimal restrictions beyond attribution.
last release 2025-02-25 (535 days) · last repo commit 2026-02-19 · 710 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 229,671 downloads/mo, #9,127 on PyPI
Alternatives
Verify before relying
pip install mir-eval
import mir_eval
# Call mir_eval functions to compute metrics for your audio processing task- Whether the library supports specific MIR tasks like beat tracking, chord recognition, and source separation evaluation.
- Whether mir_eval provides F-measure, precision, recall, or other specific metric types.
What it is and what it does
mir_eval is a Python library that implements standard evaluation metrics used in music and audio information retrieval research. It provides reference implementations of common accuracy measures for audio signal processing problems. The library depends on numpy, scipy, and decorator, making it straightforward to integrate into research workflows and evaluation pipelines.
The package is designed for researchers and practitioners who need to benchmark audio processing algorithms against established metrics. Rather than reimplementing evaluation logic, users can call mir_eval's functions to compute metrics consistently and reproducibly, which is especially valuable when comparing results across papers or validating new methods against published baselines.
Use it for
- Evaluate audio processing algorithms by computing standard metrics against ground truth annotations.
- Benchmark music processing systems using standardized accuracy measures from the mir_eval library.
- Validate audio analysis results by computing evaluation metrics across research projects.
- Compare results across papers using transparent, reference implementations of common MIR metrics.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
mir_eval is actively maintained, has no known vulnerabilities, installs with low friction, and provides standard reference implementations for music information retrieval metrics. Install it if you are evaluating audio or music processing algorithms and need reproducible metric computation.
Install
mir-eval on PyPI
Before you install
Low friction installation with three stable dependencies (numpy, scipy, decorator). Active maintenance with recent commits and a 710-star repository; last release was 2025-02-25.
License in practice
MIT license is permissive, allowing use in commercial and proprietary projects with minimal restrictions beyond attribution.
Quickstart
pip install mir-eval
import mir_eval
# Call mir_eval functions to compute metrics for your audio processing taskVerify before relying
- Whether the library supports specific MIR tasks like beat tracking, chord recognition, and source separation evaluation.
- Whether mir_eval provides F-measure, precision, recall, or other specific metric types.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesnumpyscipydecorator |
| Maintenance | Actively maintained 535 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 229,671 / month, #9,127 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Multimedia :: Sound/Audio :: Analysis |
Evidence: mir_eval-0.8.2-py3-none-any.whl
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