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https://github.com/clementine-player/Clementine
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97 lines
3.2 KiB
Plaintext
97 lines
3.2 KiB
Plaintext
Chromaprint
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===========
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Dependencies
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------------
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The library itself only depends on a FFT library, which at the moment can
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be either FFmpeg [1] (at least r22291, 0.6 is fine), FFTW3 [2] or if you are
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on iOS or OS X, you can use the Accelerate/vDSP framework. See the next
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section for details.
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The tools included in the package require FFmpeg (can be older), TagLib [3]
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and Boost Filesystem [4].
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In order to build the test suite, you will need the Google Test library [5].
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[1] http://www.ffmpeg.org/
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[2] http://www.fftw.org/
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[3] http://developer.kde.org/~wheeler/taglib.html
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[4] http://www.boost.org/
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[5] http://code.google.com/p/googletest/
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Installing
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----------
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The most common way to build Chromaprint is like this:
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$ cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_EXAMPLES=ON .
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$ make
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$ sudo make install
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This will build Chromaprint as a shared library and also include the fpcalc
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utility (which is used by MusicBrainz Picard, for example).
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See below for other options.
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FFT Library
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-----------
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Chromaprint can use three FFT libraries, FFmpeg, FFTW3 and vDSP. FFmpeg is
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preffered, as it's a little faster for our purposes and it's LGPL-licensed,
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so it doesn't impact the license of Chromaprint. The FFT interface was added
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only recently though, so it might not be available in Linux distributions yet.
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FFTW3 can be used in this case, but this library is released under the GPL
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license, which makes also the resulting Chromaprint binary GPL licensed.
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If you run simple `cmake .`, it will try to find both FFmpeg and FFTW3 and
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select the first one it finds. If you have new FFmpeg installed in a separate
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location, you can let CMake know using the `FFMPEG_ROOT` option:
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$ cmake -DFFMPEG_ROOT=/path/to/local/ffmpeg/install .
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If you have new FFmpeg installed, but for some reason prefer to use FFTW3, you
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can use the `WITH_FFTW3` option:
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$ cmake -DWITH_FFTW3=ON .
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There is also a `WITH_AVFFT` option, but the script will select the FFmpeg FFT
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automatically if it's available, so it shouldn't be necessary to use it.
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If you are on Mac, you can use the standard Accelerate framework with the vDSP
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library. This requires you to install no external libraries. It will use
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vDSP by default on OS X (but there still is a `WITH_VDSP` option).
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Unit Tests
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----------
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The test suite can be built and run using the following commands:
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$ cmake -DBUILD_TESTS=ON .
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$ make check
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Related Projects
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----------------
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* pyacoustid - https://github.com/sampsyo/pyacoustid
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* gst-chromaprint - https://github.com/lalinsky/gst-chromaprint
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Standing on the Shoulder of Giants
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----------------------------------
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I've learned a lot while working on this project, which would not be possible
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without having information from past research. I've read many papers, but the
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concrete ideas implemented in this library are based on the following papers:
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* Yan Ke, Derek Hoiem, Rahul Sukthankar. Computer Vision for Music
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Identification, Proceedings of Computer Vision and Pattern Recognition,
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2005. http://www.cs.cmu.edu/~yke/musicretrieval/
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* Frank Kurth, Meinard Müller. Efficient Index-Based Audio Matching, 2008.
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http://dx.doi.org/10.1109/TASL.2007.911552
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* Dalwon Jang, Chang D. Yoo, Sunil Lee, Sungwoong Kim, Ton Kalker.
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Pairwise Boosted Audio Fingerprint, 2009.
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http://dx.doi.org/10.1109/TIFS.2009.2034452
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