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1aubio
2=====
3
4aubio is a collection of tools for music and audio analysis.
5
6This package integrates the aubio library with [NumPy] to provide a set of
7efficient tools to process and analyse audio signals, including:
8
9- read audio from any media file, including videos and remote streams
10- high quality phase vocoder, spectral filterbanks, and linear filters
11- Mel-Frequency Cepstrum Coefficients and standard spectral descriptors
12- detection of note attacks (onset)
13- pitch tracking (fundamental frequency estimation)
14- beat detection and tempo tracking
15
16aubio works with both Python 2 and Python 3.
17
18Built with
19----------
20
21The core of aubio is written in C for portability and speed. In addition to
22[NumPy], aubio can be optionally built to use one or more of the following
23libraries:
24
25- media file reading:
26
27    - [ffmpeg](https://ffmpeg.org) / [avcodec](https://libav.org) to decode and
28      read audio from almost any format,
29    - [libsndfile](http://www.mega-nerd.com/libsndfile/) to read audio from
30      uncompressed sound files,
31    - [libsamplerate](http://www.mega-nerd.com/SRC/) to re-sample audio signals
32    - [CoreAudio](https://developer.apple.com/reference/coreaudio) to read all
33      media files supported natively on macOS, iOS, and tvOS.
34
35- hardware acceleration:
36
37    - [Atlas](http://math-atlas.sourceforge.net/) and
38      [Blas](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms),
39      for accelerated vector and matrix computations,
40    - [fftw3](http://fftw.org), to compute fast Fourier Transforms of any size.
41    - [Accelerate](https://developer.apple.com/reference/accelerate) for
42      hardware accelerated FFT and matrix computations on macOs and iOS,
43    - [Intel IPP](https://software.intel.com/en-us/intel-ipp), accelerated
44      vector computation and FFT implementation,
45
46Documentation
47-------------
48
49- [module documentation][doc_python]
50- [installation][doc_python_install]
51- [aubio manual][manual]
52- [aubio homepage][homepage]
53
54[manual]: https://aubio.org/manual/latest/
55[doc_python]: https://aubio.org/manual/latest/python.html
56[doc_python_install]: https://aubio.org/manual/latest/python_module.html
57[homepage]: https://aubio.org
58[NumPy]: https://www.numpy.org
59
60Demos scripts
61-------------
62
63Some examples are available in the [`python/demos`][demos_dir] folder. These
64scripts are small programs written in python and using python-aubio.
65
66**Notes**: installing additional modules is required to run some of the demos.
67
68### Analysis
69
70- `demo_source.py` uses aubio to read audio samples from media files
71- `demo_onset_plot.py` detects attacks in a sound file and plots the results
72  using [matplotlib]
73- `demo_pitch.py` looks for fundamental frequency in a sound file and plots the
74  results using [matplotlib]
75- `demo_spectrogram.py`, `demo_specdesc.py`, `demo_mfcc.py` for spectral
76  analysis.
77
78### Real-time
79
80- `demo_pyaudio.py` and `demo_tapthebeat.py` use [pyaudio]
81- `demo_pysoundcard_play.py`, `demo_pysoundcard.py` use [PySoundCard]
82- `demo_alsa.py` uses [pyalsaaudio]
83
84### Others
85
86- `demo_timestretch.py` can change the duration of an input file and write the
87  new sound to disk,
88- `demo_wav2midi.py` detects the notes in a file and uses [mido] to write the
89  results into a MIDI file
90
91### Example
92
93Use `demo_timestretch_online.py` to slow down `loop.wav`, write the results in
94`stretched_loop.wav`:
95
96    $ python demo_timestretch_online.py loop.wav stretched_loop.wav 0.92
97
98[demos_dir]:https://github.com/aubio/aubio/tree/master/python/demos
99[pyaudio]:https://people.csail.mit.edu/hubert/pyaudio/
100[PySoundCard]:https://github.com/bastibe/PySoundCard
101[pyalsaaudio]:https://larsimmisch.github.io/pyalsaaudio/
102[mido]:https://mido.readthedocs.io
103[matplotlib]:https://matplotlib.org/
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