view YinVamp.cpp @ 137:109c3a2ad930 vamp-fft-revision

Make use of new Vamp FFT interface. This reduces the runtime of the regression test from 5.7 to 2.2 seconds on this machine, but it does need the right version of the SDK, which is currently only available in the vampipe branch.

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */

/*
    pYIN - A fundamental frequency estimator for monophonic audio
    Centre for Digital Music, Queen Mary, University of London.
    
    This program is free software; you can redistribute it and/or
    modify it under the terms of the GNU General Public License as
    published by the Free Software Foundation; either version 2 of the
    License, or (at your option) any later version.  See the file
    COPYING included with this distribution for more information.
*/

#include "YinVamp.h"
#include "MonoNote.h"

#include "vamp-sdk/FFT.h"

#include <vector>
#include <algorithm>

#include <cstdio>
#include <cmath>
#include <complex>

using std::string;
using std::vector;
using Vamp::RealTime;


YinVamp::YinVamp(float inputSampleRate) :
    Plugin(inputSampleRate),
    m_channels(0),
    m_stepSize(256),
    m_blockSize(2048),
    m_fmin(40),
    m_fmax(1600),
    m_yin(2048, inputSampleRate, 0.0),
    m_outNoF0(0),
    m_outNoPeriodicity(0),
    m_outNoRms(0),
    m_outNoSalience(0),
    m_yinParameter(0.15f),
    m_outputUnvoiced(2.0f)
{
}

YinVamp::~YinVamp()
{
}

string
YinVamp::getIdentifier() const
{
    return "yin";
}

string
YinVamp::getName() const
{
    return "Yin";
}

string
YinVamp::getDescription() const
{
    return "A vamp implementation of the Yin algorithm for monophonic frequency estimation.";
}

string
YinVamp::getMaker() const
{
    return "Matthias Mauch";
}

int
YinVamp::getPluginVersion() const
{
    // Increment this each time you release a version that behaves
    // differently from the previous one
    return 2;
}

string
YinVamp::getCopyright() const
{
    return "GPL";
}

YinVamp::InputDomain
YinVamp::getInputDomain() const
{
    return TimeDomain;
}

size_t
YinVamp::getPreferredBlockSize() const
{
    return 2048;
}

size_t 
YinVamp::getPreferredStepSize() const
{
    return 256;
}

size_t
YinVamp::getMinChannelCount() const
{
    return 1;
}

size_t
YinVamp::getMaxChannelCount() const
{
    return 1;
}

YinVamp::ParameterList
YinVamp::getParameterDescriptors() const
{
    ParameterList list;
    
    ParameterDescriptor d;
    d.identifier = "yinThreshold";
    d.name = "Yin threshold";
    d.description = "The greedy Yin search for a low value difference function is done once a dip lower than this threshold is reached.";
    d.unit = "";
    d.minValue = 0.025f;
    d.maxValue = 1.0f;
    d.defaultValue = 0.15f;
    d.isQuantized = true;
    d.quantizeStep = 0.025f;
        
    list.push_back(d);

    d.identifier = "outputunvoiced";
    d.valueNames.clear();
    d.name = "Output estimates classified as unvoiced?";
    d.description = ".";
    d.unit = "";
    d.minValue = 0.0f;
    d.maxValue = 2.0f;
    d.defaultValue = 2.0f;
    d.isQuantized = true;
    d.quantizeStep = 1.0f;
    d.valueNames.push_back("No");
    d.valueNames.push_back("Yes");
    d.valueNames.push_back("Yes, as negative frequencies");
    list.push_back(d);

    return list;
}

float
YinVamp::getParameter(string identifier) const
{
    if (identifier == "yinThreshold") {
        return m_yinParameter;
    }
    if (identifier == "outputunvoiced") {
        return m_outputUnvoiced;
    }
    return 0.f;
}

void
YinVamp::setParameter(string identifier, float value) 
{
    if (identifier == "yinThreshold")
    {
        m_yinParameter = value;
    }
    if (identifier == "outputunvoiced")
    {
        m_outputUnvoiced = value;
    }
}

YinVamp::ProgramList
YinVamp::getPrograms() const
{
    ProgramList list;
    return list;
}

string
YinVamp::getCurrentProgram() const
{
    return ""; // no programs
}

void
YinVamp::selectProgram(string name)
{
}

YinVamp::OutputList
YinVamp::getOutputDescriptors() const
{
    OutputList outputs;

    OutputDescriptor d;
    
    int outputNumber = 0;

    d.identifier = "f0";
    d.name = "Estimated f0";
    d.description = "Estimated fundamental frequency";
    d.unit = "Hz";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = m_fmin;
    d.maxValue = 500;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = false;
    outputs.push_back(d);
    m_outNoF0 = outputNumber++;

    d.identifier = "periodicity";
    d.name = "Periodicity";
    d.description = "by-product of Yin f0 estimation";
    d.unit = "";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = 0;
    d.maxValue = 1;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = false;
    outputs.push_back(d);
    m_outNoPeriodicity = outputNumber++;

    d.identifier = "rms";
    d.name = "Root mean square";
    d.description = "Root mean square of the waveform.";
    d.unit = "";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = 0;
    d.maxValue = 1;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = false;
    outputs.push_back(d);
    m_outNoRms = outputNumber++;

    d.identifier = "salience";
    d.name = "Salience";
    d.description = "Yin Salience";
    d.hasFixedBinCount = true;
    d.binCount = m_blockSize / 2;
    d.hasKnownExtents = true;
    d.minValue = 0;
    d.maxValue = 1;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = false;
    outputs.push_back(d);
    m_outNoSalience = outputNumber++;

    return outputs;
}

bool
YinVamp::initialise(size_t channels, size_t stepSize, size_t blockSize)
{
    if (channels < getMinChannelCount() ||
	channels > getMaxChannelCount()) return false;

/*
    std::cerr << "YinVamp::initialise: channels = " << channels
          << ", stepSize = " << stepSize << ", blockSize = " << blockSize
          << std::endl;
*/
    m_channels = channels;
    m_stepSize = stepSize;
    m_blockSize = blockSize;
    
    reset();

    return true;
}

void
YinVamp::reset()
{    
    m_yin.setThreshold(m_yinParameter);
    m_yin.setFrameSize(m_blockSize);
/*        
    std::cerr << "YinVamp::reset: yin threshold set to " << (m_yinParameter)
          << ", blockSize = " << m_blockSize
          << std::endl;
*/
}

YinVamp::FeatureSet
YinVamp::process(const float *const *inputBuffers, RealTime timestamp)
{
    timestamp = timestamp + Vamp::RealTime::frame2RealTime(m_blockSize/2, lrintf(m_inputSampleRate));
    FeatureSet fs;
    
    double *dInputBuffers = new double[m_blockSize];
    for (size_t i = 0; i < m_blockSize; ++i) dInputBuffers[i] = inputBuffers[0][i];
    
    Yin::YinOutput yo = m_yin.process(dInputBuffers);
    // std::cerr << "f0 in YinVamp: " << yo.f0 << std::endl;
    Feature f;
    f.hasTimestamp = true;
    f.timestamp = timestamp;
    if (m_outputUnvoiced == 0.0f)
    {
        // std::cerr << "f0 in YinVamp: " << yo.f0 << std::endl;
        if (yo.f0 > 0 && yo.f0 < m_fmax && yo.f0 > m_fmin) {
            f.values.push_back(yo.f0);
            fs[m_outNoF0].push_back(f);
        }
    } else if (m_outputUnvoiced == 1.0f)
    {
        if (fabs(yo.f0) < m_fmax && fabs(yo.f0) > m_fmin) {
            f.values.push_back(fabs(yo.f0));
            fs[m_outNoF0].push_back(f);
        }
    } else
    {
        if (fabs(yo.f0) < m_fmax && fabs(yo.f0) > m_fmin) {
            f.values.push_back(yo.f0);
            fs[m_outNoF0].push_back(f);
        }
    }

    f.values.clear();
    f.values.push_back(yo.rms);
    fs[m_outNoRms].push_back(f);
    
    f.values.clear();
    for (size_t iBin = 0; iBin < yo.salience.size(); ++iBin)
    {
        f.values.push_back(yo.salience[iBin]);
    }
    fs[m_outNoSalience].push_back(f);
    
    f.values.clear();
    // f.values[0] = yo.periodicity;
    f.values.push_back(yo.periodicity);
    fs[m_outNoPeriodicity].push_back(f);
    
    delete [] dInputBuffers;

    return fs;
}

YinVamp::FeatureSet
YinVamp::getRemainingFeatures()
{
    FeatureSet fs;
    return fs;
}