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MetaOMR

A fast, reliable sheet music informatics system

Example

python show_layout.py samples/sonata.png

This detects layout-related information from the score (staves, measures, and staff systems) and overlays the result with the image using matplotlib.

Features

  • Robust layout (staves, systems, and measures) detection
  • Random forest glyph classification

Goals

  • Identifying multiple scans and editions of the same piece, and automatically selecting higher-quality scans
  • Creating a high-level OMR accuracy benchmark

Requirements

  • Python 2.7+
  • NumPy
  • Reikna
  • PyOpenCL or PyCUDA
  • PyFFT
  • Pillow, PyPDF, pylibtiff (PDF loading)
  • Pylab (for displaying data only)
  • SciPy (for Kanungo noise parameter estimation)
  • Music21 (for classified note export)

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Optical music recognition

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  • Python 77.0%
  • C 22.9%
  • Shell 0.1%