source: python/README.md @ 0850e54

aubio
=====

aubio is a collection of tools for music and audio analysis.

This package integrates the aubio library with [NumPy] to provide a set of
efficient tools to process and analyse audio signals, including:

- read audio from any media file, including videos and remote streams
- high quality phase vocoder, spectral filterbanks, and linear filters
- Mel-Frequency Cepstrum Coefficients and standard spectral descriptors
- detection of note attacks (onset)
- pitch tracking (fundamental frequency estimation)
- beat detection and tempo tracking

aubio works with both Python 2 and Python 3.

Links
-----

- [module documentation][doc_python]
- [installation instructions][doc_python_install]
- [aubio manual][manual]
- [aubio homepage][homepage]
- [issue tracker][bugtracker]

Demos
-----

Some examples are available in the [`python/demos`][demos_dir] folder. Each
script is a command line program which accepts one ore more argument.

**Notes**: installing additional modules is required to run some of the demos.

### Analysis

- `demo_source.py` uses aubio to read audio samples from media files
- `demo_onset_plot.py` detects attacks in a sound file and plots the results
  using [matplotlib]
- `demo_pitch.py` looks for fundamental frequency in a sound file and plots the
  results using [matplotlib]
- `demo_spectrogram.py`, `demo_specdesc.py`, `demo_mfcc.py` for spectral
  analysis.

### Real-time

- `demo_pyaudio.py` and `demo_tapthebeat.py` use [pyaudio]
- `demo_pysoundcard_play.py`, `demo_pysoundcard.py` use [PySoundCard]
- `demo_alsa.py` uses [pyalsaaudio]

### Others

- `demo_timestretch.py` can change the duration of an input file and write the
  new sound to disk,
- `demo_wav2midi.py` detects the notes in a file and uses [mido] to write the
  results into a MIDI file

### Example

Use `demo_timestretch_online.py` to slow down `loop.wav`, write the results in
`stretched_loop.wav`:

    $ python demo_timestretch_online.py loop.wav stretched_loop.wav 0.92

Built with
----------

The core of aubio is written in C for portability and speed. In addition to
[NumPy], aubio can be optionally built to use one or more of the following
libraries:

- media file reading:

    - [ffmpeg] / [avcodec] to decode and read audio from almost any format,
    - [libsndfile] to read audio from uncompressed sound files,
    - [libsamplerate] to re-sample audio signals,
    - [CoreAudio] to read all media formats supported by macOS, iOS, and tvOS.

- hardware acceleration:

    - [Atlas] and [Blas], for accelerated vector and matrix computations,
    - [fftw3], to compute fast Fourier Transforms of any size,
    - [Accelerate] for accelerated FFT and matrix computations (macOS/iOS),
    - [Intel IPP], accelerated vector computation and FFT implementation.

[ffmpeg]: https://ffmpeg.org
[avcodec]: https://libav.org
[libsndfile]: http://www.mega-nerd.com/libsndfile/
[libsamplerate]: http://www.mega-nerd.com/SRC/
[CoreAudio]: https://developer.apple.com/reference/coreaudio
[Atlas]: http://math-atlas.sourceforge.net/
[Blas]: https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
[fftw3]: http://fftw.org
[Accelerate]: https://developer.apple.com/reference/accelerate
[Intel IPP]: https://software.intel.com/en-us/intel-ipp

[demos_dir]:https://github.com/aubio/aubio/tree/master/python/demos
[pyaudio]:https://people.csail.mit.edu/hubert/pyaudio/
[PySoundCard]:https://github.com/bastibe/PySoundCard
[pyalsaaudio]:https://larsimmisch.github.io/pyalsaaudio/
[mido]:https://mido.readthedocs.io

[manual]: https://aubio.org/manual/latest/
[doc_python]: https://aubio.org/manual/latest/python.html
[doc_python_install]: https://aubio.org/manual/latest/python_module.html
[homepage]: https://aubio.org
[NumPy]: https://www.numpy.org
[bugtracker]: https://github.com/aubio/aubio/issues
[matplotlib]:https://matplotlib.org/